MLIR 22.0.0git
NVVMDialect.cpp
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1//===- NVVMDialect.cpp - NVVM IR Ops and Dialect registration -------------===//
2//
3// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4// See https://llvm.org/LICENSE.txt for license information.
5// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6//
7//===----------------------------------------------------------------------===//
8//
9// This file defines the types and operation details for the NVVM IR dialect in
10// MLIR, and the LLVM IR dialect. It also registers the dialect.
11//
12// The NVVM dialect only contains GPU specific additions on top of the general
13// LLVM dialect.
14//
15//===----------------------------------------------------------------------===//
16
18
22#include "mlir/IR/Builders.h"
25#include "mlir/IR/Diagnostics.h"
27#include "mlir/IR/MLIRContext.h"
28#include "mlir/IR/Operation.h"
30#include "mlir/IR/Types.h"
31#include "llvm/ADT/STLExtras.h"
32#include "llvm/ADT/TypeSwitch.h"
33#include "llvm/IR/IRBuilder.h"
34#include "llvm/IR/NVVMIntrinsicUtils.h"
35#include "llvm/Support/Casting.h"
36#include "llvm/Support/FormatVariadic.h"
37#include "llvm/Support/NVPTXAddrSpace.h"
38#include "llvm/Support/raw_ostream.h"
39#include <cassert>
40#include <optional>
41#include <string>
42
43using namespace mlir;
44using namespace NVVM;
45
46#include "mlir/Dialect/LLVMIR/NVVMOpsDialect.cpp.inc"
47#include "mlir/Dialect/LLVMIR/NVVMOpsEnums.cpp.inc"
48
49static constexpr unsigned notIntrinsic = llvm::Intrinsic::not_intrinsic;
50
51//===----------------------------------------------------------------------===//
52// Helper/Utility methods
53//===----------------------------------------------------------------------===//
54
55static bool isPtrInAddrSpace(mlir::Value ptr, NVVMMemorySpace targetAS) {
56 auto ptrTy = llvm::cast<LLVM::LLVMPointerType>(ptr.getType());
57 return ptrTy.getAddressSpace() == static_cast<unsigned>(targetAS);
58}
59
61 return isPtrInAddrSpace(ptr, NVVMMemorySpace::Generic);
62}
63
65 return isPtrInAddrSpace(ptr, NVVMMemorySpace::Shared);
66}
67
69 return isPtrInAddrSpace(ptr, NVVMMemorySpace::SharedCluster);
70}
71
72static llvm::Value *castPtrToAddrSpace(llvm::IRBuilderBase &builder,
73 llvm::Value *ptr,
74 NVVMMemorySpace targetAS) {
75 unsigned AS = static_cast<unsigned>(targetAS);
76 return builder.CreateAddrSpaceCast(
77 ptr, llvm::PointerType::get(builder.getContext(), AS));
78}
79
80// Helper method to convert CtaGroupKind in NVVM Dialect to CtaGroupKind in LLVM
81static llvm::nvvm::CTAGroupKind
82getNVVMCtaGroupKind(NVVM::CTAGroupKind ctaGroup) {
83 switch (ctaGroup) {
84 case NVVM::CTAGroupKind::CTA_1:
85 return llvm::nvvm::CTAGroupKind::CG_1;
86 case NVVM::CTAGroupKind::CTA_2:
87 return llvm::nvvm::CTAGroupKind::CG_2;
88 }
89 llvm_unreachable("unsupported cta_group value");
90}
91
92//===----------------------------------------------------------------------===//
93// Verifier methods
94//===----------------------------------------------------------------------===//
95
96// This verifier is shared among the following Ops:
97// CpAsyncBulkTensorSharedCTAToGlobalOp (TMA Store)
98// CpAsyncBulkTensorReduceOp (TMA Store-Reduce)
99static LogicalResult cpAsyncBulkTensorCommonVerifier(size_t tensorDims,
100 bool isIm2Col,
101 size_t numIm2ColOffsets,
102 Location loc) {
103 if (tensorDims < 1 || tensorDims > 5)
104 return emitError(loc, "expects coordinates between 1 to 5 dimension");
105
106 // For Im2Col mode, there are two constraints:
107 if (isIm2Col) {
108 // 1. Tensor must always be at least 3-d.
109 if (tensorDims < 3)
110 return emitError(
111 loc,
112 "to use im2col mode, the tensor has to be at least 3-dimensional");
113 // 2. When there are Im2ColOffsets, they must be (Dims - 2) in number.
114 if (numIm2ColOffsets && (tensorDims != (numIm2ColOffsets + 2)))
115 return emitError(
116 loc, "im2col offsets must be 2 less than number of coordinates");
117 }
118 return success();
119}
120
121LogicalResult CpAsyncBulkTensorSharedCTAToGlobalOp::verify() {
122 TMAStoreMode mode = getMode();
123 // We lower through inline-ptx when getPredicate() is true.
124 // a) Only TILE mode is supported
125 // b) Cache-hint is not supported
126 if (getPredicate()) {
127 if (mode != TMAStoreMode::TILE)
128 return emitError("Inline-ptx lowering supported only for Tile mode.");
129 if (getL2CacheHint())
130 return emitError("Inline-ptx lowering unsupported with L2 cache-hint.");
131 }
132
133 size_t dims = getCoordinates().size();
134 switch (mode) {
135 case TMAStoreMode::TILE:
136 return cpAsyncBulkTensorCommonVerifier(dims, false, 0, getLoc());
137 case TMAStoreMode::IM2COL:
138 return cpAsyncBulkTensorCommonVerifier(dims, true, 0, getLoc());
139 case TMAStoreMode::TILE_SCATTER4:
140 if (dims != 5)
141 return emitError("Scatter4 mode expects 5 coordinates");
142 }
143 return success();
144}
145
146LogicalResult CpAsyncOp::verify() {
147 if (getModifier() != LoadCacheModifierKind::CG &&
148 getModifier() != LoadCacheModifierKind::CA)
149 return emitError("Only CG and CA cache modifiers are supported.");
150 if (getSize() != 4 && getSize() != 8 && getSize() != 16)
151 return emitError("expected byte size to be either 4, 8 or 16.");
152 if (getModifier() == LoadCacheModifierKind::CG && getSize() != 16)
153 return emitError("CG cache modifier is only support for 16 bytes copy.");
154 return success();
155}
156
157// This verify params can be shared across TMA Load and Prefetch Ops.
158static LogicalResult verifyTMALoadParams(size_t tensorDims, size_t numIm2colOff,
159 TMALoadMode mode, Location loc) {
160 if (tensorDims < 1 || tensorDims > 5)
161 return emitError(loc, "expects coordinates between 1 to 5 dimension");
162
163 auto checkTMALoadParams = [&](TMALoadMode mode, bool isIm2col,
164 size_t expectedIm2colOff) -> LogicalResult {
165 if (isIm2col && (tensorDims < 3))
166 return emitError(loc)
167 << "to use " << stringifyEnum(mode)
168 << " mode, the tensor has to be at least 3-dimensional";
169
170 if (numIm2colOff != expectedIm2colOff)
171 return emitError(loc) << " im2col offsets expected " << expectedIm2colOff
172 << " (provided " << numIm2colOff << ")";
173
174 return success();
175 };
176
177 switch (mode) {
178 case TMALoadMode::TILE:
179 return checkTMALoadParams(mode, false, 0);
180 case TMALoadMode::IM2COL:
181 return checkTMALoadParams(mode, true, tensorDims - 2);
182 case TMALoadMode::IM2COL_W:
183 case TMALoadMode::IM2COL_W_128:
184 return checkTMALoadParams(mode, true, 2);
185 case TMALoadMode::TILE_GATHER4:
186 return (tensorDims == 5)
187 ? checkTMALoadParams(mode, false, 0)
188 : emitError(loc, "Gather4 mode expects 5 coordinates");
189 }
190 return success();
191}
192
193LogicalResult CpAsyncBulkTensorPrefetchOp::verify() {
194 return verifyTMALoadParams(getCoordinates().size(), getIm2colOffsets().size(),
195 getMode(), getLoc());
196}
197
198LogicalResult CpAsyncBulkTensorGlobalToSharedClusterOp::verify() {
199 TMALoadMode mode = getMode();
200 bool isCTAOnly = getIsCTAOnly();
201 if (getPredicate()) { // Inline-asm based lowering
202 if (isCTAOnly)
203 return emitError("Predicate is supported only for shared::cluster mode.");
204 if (mode != TMALoadMode::TILE && mode != TMALoadMode::IM2COL)
205 return emitError(
206 "Predicate is supported only for Tile and Im2col modes.");
207 } else { // Intrinsics-based lowering
208 NVVMMemorySpace expectedAS =
209 isCTAOnly ? NVVMMemorySpace::Shared : NVVMMemorySpace::SharedCluster;
210 unsigned AS = llvm::cast<LLVM::LLVMPointerType>(getDstMem().getType())
211 .getAddressSpace();
212 if (AS != expectedAS)
213 return emitError()
214 << (isCTAOnly
215 ? "Shared::cta destination requires address-space 3."
216 : "Shared::cluster destination requires address-space 7.");
217 // Checks specific to shared::cta mode
218 if (isCTAOnly) {
219 if (getMulticastMask())
220 return emitError("Multicast is not supported with shared::cta mode.");
221 if (getGroup())
222 return emitError("CTAGroup is not supported with shared::cta mode.");
223 }
224 }
225
226 return verifyTMALoadParams(getCoordinates().size(), getIm2colOffsets().size(),
227 getMode(), getLoc());
228}
229
230LogicalResult CpAsyncBulkTensorReduceOp::verify() {
231 TMAStoreMode mode = getMode();
232 size_t dims = getCoordinates().size();
233 switch (mode) {
234 case TMAStoreMode::TILE:
235 return cpAsyncBulkTensorCommonVerifier(dims, false, 0, getLoc());
236 case TMAStoreMode::IM2COL:
237 return cpAsyncBulkTensorCommonVerifier(dims, true, 0, getLoc());
238 case TMAStoreMode::TILE_SCATTER4:
239 return emitError("Scatter mode unsupported for CpAsyncBulkTensorReduceOp");
240 }
241 return success();
242}
243
244LogicalResult CpAsyncBulkGlobalToSharedClusterOp::verify() {
245 bool isSharedCTA = isPtrInSharedCTASpace(getDstMem());
246 if (isSharedCTA && getMulticastMask())
247 return emitError("Multicast is not supported with shared::cta mode.");
248
249 return success();
250}
251
252static LogicalResult verifyMBarrierArriveLikeOp(Operation *op, Value addr,
253 NVVM::MemScopeKind scope,
254 Value retVal = nullptr) {
255 if (scope != NVVM::MemScopeKind::CTA && scope != NVVM::MemScopeKind::CLUSTER)
256 return op->emitError("mbarrier scope must be either CTA or Cluster");
257
258 bool isSharedCluster = isPtrInSharedClusterSpace(addr);
259 bool hasRetValue = static_cast<bool>(retVal);
260 if (isSharedCluster && hasRetValue)
261 return op->emitError(
262 "mbarrier in shared_cluster space cannot return any value");
263
264 return success();
265}
266
267LogicalResult MBarrierArriveOp::verify() {
268 return verifyMBarrierArriveLikeOp(getOperation(), getAddr(), getScope(),
269 getRes());
270}
271
272LogicalResult MBarrierArriveDropOp::verify() {
273 return verifyMBarrierArriveLikeOp(getOperation(), getAddr(), getScope(),
274 getRes());
275}
276
277LogicalResult MBarrierArriveExpectTxOp::verify() {
278 // The inline-ptx version of this Op does not support all features.
279 // With predicate, this Op lowers to inline-ptx. So, verify and
280 // error-out if there are unsupported features.
281 if (getPredicate()) {
282 if (getScope() != NVVM::MemScopeKind::CTA)
283 return emitError("mbarrier scope must be CTA when using predicate");
284
285 if (isPtrInSharedClusterSpace(getAddr()))
286 return emitError("mbarrier in shared_cluster space is not supported when "
287 "using predicate");
288
289 if (getRes())
290 return emitError("return-value is not supported when using predicate");
291
292 if (getRelaxed() == true)
293 return emitError("mbarrier with relaxed semantics is not supported when "
294 "using predicate");
295 }
296 return verifyMBarrierArriveLikeOp(getOperation(), getAddr(), getScope(),
297 getRes());
298}
299
300LogicalResult MBarrierArriveDropExpectTxOp::verify() {
301 return verifyMBarrierArriveLikeOp(getOperation(), getAddr(), getScope(),
302 getRes());
303}
304
305LogicalResult MBarrierExpectTxOp::verify() {
306 return verifyMBarrierArriveLikeOp(getOperation(), getAddr(), getScope());
307}
308
309LogicalResult MBarrierCompleteTxOp::verify() {
310 return verifyMBarrierArriveLikeOp(getOperation(), getAddr(), getScope());
311}
312
313LogicalResult MBarrierTestWaitOp::verify() {
314 return verifyMBarrierArriveLikeOp(getOperation(), getAddr(), getScope());
315}
316
317LogicalResult MBarrierTryWaitOp::verify() {
318 return verifyMBarrierArriveLikeOp(getOperation(), getAddr(), getScope());
319}
320
321LogicalResult ConvertFloatToTF32Op::verify() {
322 using RndMode = NVVM::FPRoundingMode;
323 switch (getRnd()) {
324 case RndMode::RNA:
325 if (getRelu())
326 return emitError("Relu not supported with rna rounding mode.");
327 break;
328 case RndMode::RN:
329 case RndMode::RZ:
330 break;
331 default:
332 return emitError(
333 "Only {rn,rz,rna} rounding modes supported for ConvertFloatToTF32Op.");
334 }
335 return success();
336}
337
338LogicalResult ConvertF32x2ToF6x2Op::verify() {
340
341 if (!llvm::isa<mlir::Float6E2M3FNType, mlir::Float6E3M2FNType>(getDstTy())) {
342 return emitOpError("Only ")
343 << mlir::Float6E2M3FNType::get(ctx) << " and "
344 << mlir::Float6E3M2FNType::get(ctx)
345 << " types are supported for conversions from f32x2 to f6x2.";
346 }
347 return success();
348}
349
350LogicalResult ConvertF32x2ToF8x2Op::verify() {
351 using RndMode = NVVM::FPRoundingMode;
352 using SatMode = NVVM::SaturationMode;
353
354 bool isRoundingModeRN = getRnd() == RndMode::RN;
355 bool isRoundingModeRZ = getRnd() == RndMode::RZ;
356 bool isRoundingModeRP = getRnd() == RndMode::RP;
357 bool isSatFinite = getSat() == SatMode::SATFINITE;
358
359 bool hasRelu = getRelu();
360
362
364 .Case<mlir::Float8E4M3FNType, mlir::Float8E5M2Type>(
365 [&](mlir::Type) -> LogicalResult {
366 if (!isRoundingModeRN) {
367 return emitOpError("Only RN rounding mode is supported for "
368 "conversions from f32x2 to ")
369 << mlir::Float8E4M3FNType::get(ctx) << " and "
370 << mlir::Float8E5M2Type::get(ctx) << " types";
371 }
372 if (!isSatFinite) {
373 return emitOpError("Only SATFINITE saturation mode is supported "
374 "for conversions "
375 "from f32x2 to ")
376 << mlir::Float8E4M3FNType::get(ctx) << " and "
377 << mlir::Float8E5M2Type::get(ctx) << " types";
378 }
379 return success();
380 })
381 .Case<mlir::Float8E8M0FNUType>([&](mlir::Type) -> LogicalResult {
382 if (!(isRoundingModeRZ || isRoundingModeRP)) {
383 return emitOpError("Only RZ and RP rounding modes are supported for "
384 "conversions from f32x2 to ")
385 << mlir::Float8E8M0FNUType::get(ctx) << " type";
386 }
387 if (hasRelu) {
388 return emitOpError("relu not supported for conversions to ")
389 << mlir::Float8E8M0FNUType::get(ctx) << " type";
390 }
391 return success();
392 })
393 .Default([&](mlir::Type) {
394 return emitOpError("Only ")
395 << mlir::Float8E4M3FNType::get(ctx) << ", "
396 << mlir::Float8E5M2Type::get(ctx) << ", and "
397 << mlir::Float8E8M0FNUType::get(ctx)
398 << " types are "
399 "supported for conversions from f32x2 to f8x2";
400 });
401}
402
403LogicalResult ConvertF16x2ToF8x2Op::verify() {
405
406 if (!llvm::isa<mlir::Float8E4M3FNType, mlir::Float8E5M2Type>(getDstTy())) {
407 return emitOpError("Only ")
408 << mlir::Float8E4M3FNType::get(ctx) << " and "
409 << mlir::Float8E5M2Type::get(ctx)
410 << " types are supported for conversions from f16x2 to f8x2.";
411 }
412 return success();
413}
414
415LogicalResult ConvertBF16x2ToF8x2Op::verify() {
416 using RndMode = NVVM::FPRoundingMode;
417
418 if (!llvm::isa<mlir::Float8E8M0FNUType>(getDstTy()))
419 return emitOpError("Only ") << mlir::Float8E8M0FNUType::get(getContext())
420 << " type is supported for conversions from "
421 "bf16x2 to f8x2.";
422
423 auto rnd = getRnd();
424 if (rnd != RndMode::RZ && rnd != RndMode::RP)
425 return emitOpError("Only RZ and RP rounding modes are supported for "
426 "conversions from bf16x2 to f8x2.");
427
428 return success();
429}
430
431LogicalResult ConvertF32x2ToF4x2Op::verify() {
433
434 if (!llvm::isa<mlir::Float4E2M1FNType>(getDstTy()))
435 return emitOpError("Only ")
436 << mlir::Float4E2M1FNType::get(ctx)
437 << " type is supported for conversions from f32x2 to f4x2.";
438
439 return success();
440}
441
442LogicalResult ConvertF8x2ToF16x2Op::verify() {
444
445 if (!llvm::isa<Float8E4M3FNType, Float8E5M2Type>(getSrcType()))
446 return emitOpError("Only ")
447 << mlir::Float8E4M3FNType::get(ctx) << " and "
448 << mlir::Float8E5M2Type::get(ctx)
449 << " types are supported for conversions from f8x2 to f16x2.";
450
451 return success();
452}
453
454LogicalResult ConvertF8x2ToBF16x2Op::verify() {
456 if (!llvm::isa<Float8E8M0FNUType>(getSrcType()))
457 return emitOpError("Only ")
458 << mlir::Float8E8M0FNUType::get(ctx)
459 << " type is supported for conversions from f8x2 to bf16x2.";
460
461 return success();
462}
463
464LogicalResult ConvertF6x2ToF16x2Op::verify() {
466
467 if (!llvm::isa<Float6E2M3FNType, Float6E3M2FNType>(getSrcType()))
468 return emitOpError("Only ")
469 << mlir::Float6E2M3FNType::get(ctx) << " and "
470 << mlir::Float6E3M2FNType::get(ctx)
471 << " types are supported for conversions from f6x2 to f16x2.";
472
473 return success();
474}
475
476LogicalResult ConvertF4x2ToF16x2Op::verify() {
478
479 if (!llvm::isa<Float4E2M1FNType>(getSrcType()))
480 return emitOpError("Only ")
481 << mlir::Float4E2M1FNType::get(ctx)
482 << " type is supported for conversions from f4x2 to f16x2.";
483
484 return success();
485}
486
487LogicalResult PermuteOp::verify() {
488 using Mode = NVVM::PermuteMode;
489 bool hasHi = static_cast<bool>(getHi());
490
491 switch (getMode()) {
492 case Mode::DEFAULT:
493 case Mode::F4E:
494 case Mode::B4E:
495 if (!hasHi)
496 return emitError("mode '")
497 << stringifyPermuteMode(getMode()) << "' requires 'hi' operand.";
498 break;
499 case Mode::RC8:
500 case Mode::ECL:
501 case Mode::ECR:
502 case Mode::RC16:
503 if (hasHi)
504 return emitError("mode '") << stringifyPermuteMode(getMode())
505 << "' does not accept 'hi' operand.";
506 break;
507 }
508
509 return success();
510}
511
512//===----------------------------------------------------------------------===//
513// Stochastic Rounding Conversion Ops
514//===----------------------------------------------------------------------===//
515
516static LogicalResult verifyConvertF32x2ToFP16x2Op(Twine dstType,
517 FPRoundingMode rnd,
518 bool hasRandomBits,
519 Operation *op) {
520 static constexpr FPRoundingMode validRndModes[] = {
521 FPRoundingMode::RN, FPRoundingMode::RZ, FPRoundingMode::RS};
522
523 if (!llvm::is_contained(validRndModes, rnd)) {
524 return op->emitOpError(
525 "Only RN, RZ, and RS rounding modes are supported for "
526 "conversions from f32x2 to ")
527 << dstType << ".";
528 }
529
530 if (rnd == FPRoundingMode::RS) {
531 if (!hasRandomBits) {
532 return op->emitOpError("random_bits is required for RS rounding mode.");
533 }
534 } else {
535 if (hasRandomBits) {
536 return op->emitOpError(
537 "random_bits not supported for RN and RZ rounding modes.");
538 }
539 }
540
541 return success();
542}
543
544LogicalResult ConvertF32x2ToF16x2Op::verify() {
545 return verifyConvertF32x2ToFP16x2Op("f16x2", getRnd(),
546 getRandomBits() ? true : false, *this);
547}
548
549LogicalResult ConvertF32x2ToBF16x2Op::verify() {
550 return verifyConvertF32x2ToFP16x2Op("bf16x2", getRnd(),
551 getRandomBits() ? true : false, *this);
552}
553
554LogicalResult ConvertF32x4ToF8x4Op::verify() {
556
557 if (!llvm::isa<mlir::Float8E4M3FNType, mlir::Float8E5M2Type>(getDstTy()))
558 return emitOpError("Only ")
559 << mlir::Float8E4M3FNType::get(ctx) << " and "
560 << mlir::Float8E5M2Type::get(ctx)
561 << " types are supported for conversions from f32x4 to f8x4.";
562
563 return success();
564}
565
566LogicalResult ConvertF32x4ToF6x4Op::verify() {
568
569 if (!llvm::isa<mlir::Float6E2M3FNType, mlir::Float6E3M2FNType>(getDstTy()))
570 return emitOpError("Only ")
571 << mlir::Float6E2M3FNType::get(ctx) << " and "
572 << mlir::Float6E3M2FNType::get(ctx)
573 << " types are supported for conversions from f32x4 to f6x4.";
574
575 return success();
576}
577
578LogicalResult ConvertF32x4ToF4x4Op::verify() {
580
581 if (!llvm::isa<mlir::Float4E2M1FNType>(getDstTy()))
582 return emitOpError("Only ") << mlir::Float4E2M1FNType::get(ctx)
583 << " type is supported for conversions from "
584 "f32x4 to f4x4.";
585
586 return success();
587}
588
589LogicalResult BulkStoreOp::verify() {
590 if (getInitVal() != 0)
591 return emitOpError("only 0 is supported for initVal, got ") << getInitVal();
592 return success();
593}
594
595LogicalResult PMEventOp::verify() {
596 auto eventId = getEventId();
597 auto maskedEventId = getMaskedEventId();
598 if (!maskedEventId && !eventId) {
599 return emitOpError() << "either `id` or `mask` must be set";
600 }
601
602 if (maskedEventId && eventId) {
603 return emitOpError() << "`id` and `mask` cannot be set at the same time";
604 }
605
606 if (eventId) {
607 if (eventId < 0 || eventId > 15) {
608 return emitOpError() << "`id` must be between 0 and 15";
609 }
610 }
611
612 return llvm::success();
613}
614
615// Given the element type of an operand and whether or not it is an accumulator,
616// this function returns the PTX type (`NVVM::MMATypes`) that corresponds to the
617// operand's element type.
618std::optional<mlir::NVVM::MMATypes>
619MmaOp::inferOperandMMAType(Type operandElType, bool isAccumulator) {
620 auto half2Type =
621 VectorType::get(2, Float16Type::get(operandElType.getContext()));
622 if (operandElType.isF64())
623 return NVVM::MMATypes::f64;
624 if (operandElType.isF16() || operandElType == half2Type)
625 return NVVM::MMATypes::f16;
626 if (operandElType.isF32() && isAccumulator)
627 return NVVM::MMATypes::f32;
628 if (operandElType.isF32() && !isAccumulator)
629 return NVVM::MMATypes::tf32;
630 if (llvm::isa<IntegerType>(operandElType)) {
631 if (isAccumulator)
632 return NVVM::MMATypes::s32;
633 return std::nullopt;
634 }
635
636 if (auto structType = llvm::dyn_cast<LLVM::LLVMStructType>(operandElType)) {
637 if (structType.getBody().empty())
638 return std::nullopt;
639 return inferOperandMMAType(structType.getBody()[0], isAccumulator);
640 }
641
642 return std::nullopt;
643}
644
645static bool isInt4PtxType(MMATypes type) {
646 return (type == MMATypes::u4 || type == MMATypes::s4);
647}
648
649static bool isInt8PtxType(MMATypes type) {
650 return (type == MMATypes::u8 || type == MMATypes::s8);
651}
652
653static bool isIntegerPtxType(MMATypes type) {
654 return isInt4PtxType(type) || isInt8PtxType(type) || type == MMATypes::b1 ||
655 type == MMATypes::s32;
656}
657
658MMATypes MmaOp::accumPtxType() {
659 std::optional<mlir::NVVM::MMATypes> val = inferOperandMMAType(
660 getODSOperands(2).getTypes().front(), /*isAccumulator=*/true);
661 assert(val.has_value() && "accumulator PTX type should always be inferrable");
662 return val.value();
663}
664
665MMATypes MmaOp::resultPtxType() {
666 std::optional<mlir::NVVM::MMATypes> val =
667 inferOperandMMAType(getResult().getType(), /*isAccumulator=*/true);
668 assert(val.has_value() && "result PTX type should always be inferrable");
669 return val.value();
670}
671
672void MmaOp::print(OpAsmPrinter &p) {
673 SmallVector<Type, 4> regTypes;
674 struct MMAOperandFragment {
675 StringRef operandName;
676 StringRef ptxTypeAttr;
677 SmallVector<Value, 4> regs;
678 explicit MMAOperandFragment(StringRef name, StringRef ptxTypeName)
679 : operandName(name), ptxTypeAttr(ptxTypeName) {}
680 };
681
682 std::array<MMAOperandFragment, 3> frags{
683 MMAOperandFragment("A", getMultiplicandAPtxTypeAttrName()),
684 MMAOperandFragment("B", getMultiplicandBPtxTypeAttrName()),
685 MMAOperandFragment("C", "")};
686 SmallVector<StringRef, 4> ignoreAttrNames{
687 mlir::NVVM::MmaOp::getOperandSegmentSizeAttr()};
688
689 for (unsigned fragIdx = 0; fragIdx < frags.size(); fragIdx++) {
690 auto &frag = frags[fragIdx];
691 auto varOperandSpec = getODSOperandIndexAndLength(fragIdx);
692 for (auto operandIdx = varOperandSpec.first;
693 operandIdx < varOperandSpec.first + varOperandSpec.second;
694 operandIdx++) {
695 frag.regs.push_back(this->getOperand(operandIdx));
696 if (operandIdx == 0) {
697 regTypes.push_back(this->getOperand(operandIdx).getType());
698 }
699 }
700 std::optional<MMATypes> inferredType = MmaOp::inferOperandMMAType(
701 regTypes.back(), /*isAccumulator=*/fragIdx >= 2);
702 if (inferredType)
703 ignoreAttrNames.push_back(frag.ptxTypeAttr);
704 }
705
706 auto printMmaOperand = [&](const MMAOperandFragment &frag) -> void {
707 p << " " << frag.operandName;
708 p << "[";
709 p.printOperands(frag.regs);
710 p << "] ";
711 };
712
713 for (const auto &frag : frags) {
714 printMmaOperand(frag);
715 }
716
717 p.printOptionalAttrDict(this->getOperation()->getAttrs(), ignoreAttrNames);
718
719 // Print the types of the operands and result.
720 p << " : "
721 << "(";
722 llvm::interleaveComma(SmallVector<Type, 3>{frags[0].regs[0].getType(),
723 frags[1].regs[0].getType(),
724 frags[2].regs[0].getType()},
725 p);
726 p << ")";
727 p.printArrowTypeList(TypeRange{this->getRes().getType()});
728}
729
730void MmaOp::build(OpBuilder &builder, OperationState &result, Type resultType,
731 ValueRange operandA, ValueRange operandB, ValueRange operandC,
732 ArrayRef<int64_t> shape, std::optional<MMAB1Op> b1Op,
733 std::optional<MMAIntOverflow> intOverflow,
734 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes,
735 std::optional<std::array<MMALayout, 2>> multiplicandLayouts) {
736
737 assert(shape.size() == 3 && "expected shape to have size 3 (m, n, k)");
738 MLIRContext *ctx = builder.getContext();
739 result.addAttribute(
740 "shape", builder.getAttr<MMAShapeAttr>(shape[0], shape[1], shape[2]));
741
742 result.addOperands(operandA);
743 result.addOperands(operandB);
744 result.addOperands(operandC);
745
746 if (multiplicandPtxTypes) {
747 result.addAttribute("multiplicandAPtxType",
748 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[0]));
749 result.addAttribute("multiplicandBPtxType",
750 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[1]));
751 } else {
752 if (auto res = inferOperandMMAType(operandA[0].getType(), false))
753 result.addAttribute("multiplicandAPtxType", MMATypesAttr::get(ctx, *res));
754 if (auto res = inferOperandMMAType(operandB[0].getType(), false))
755 result.addAttribute("multiplicandBPtxType", MMATypesAttr::get(ctx, *res));
756 }
757
758 if (multiplicandLayouts) {
759 result.addAttribute("layoutA",
760 MMALayoutAttr::get(ctx, (*multiplicandLayouts)[0]));
761 result.addAttribute("layoutB",
762 MMALayoutAttr::get(ctx, (*multiplicandLayouts)[1]));
763 } else {
764 result.addAttribute("layoutA", MMALayoutAttr::get(ctx, MMALayout::row));
765 result.addAttribute("layoutB", MMALayoutAttr::get(ctx, MMALayout::col));
766 }
767
768 if (intOverflow.has_value())
769 result.addAttribute("intOverflowBehavior",
770 MMAIntOverflowAttr::get(ctx, *intOverflow));
771 if (b1Op.has_value())
772 result.addAttribute("b1Op", MMAB1OpAttr::get(ctx, *b1Op));
773
774 result.addTypes(resultType);
775 result.addAttribute(
776 MmaOp::getOperandSegmentSizeAttr(),
777 builder.getDenseI32ArrayAttr({static_cast<int32_t>(operandA.size()),
778 static_cast<int32_t>(operandB.size()),
779 static_cast<int32_t>(operandC.size())}));
780}
781
782// <operation> :=
783// A `[` $operandA `]` B `[` $operandB `]` C `[` $operandC `]`
784// attr-dict : (type($operandA[0]), type($operandB[0]), type($operandC[0]))
785// `->` type($res)
786ParseResult MmaOp::parse(OpAsmParser &parser, OperationState &result) {
787 struct MMAOperandFragment {
788 std::optional<MMATypes> elemtype;
789 SmallVector<OpAsmParser::UnresolvedOperand, 4> regs;
790 SmallVector<Type> regTypes;
791 };
792
793 Builder &builder = parser.getBuilder();
794 std::array<MMAOperandFragment, 4> frags;
795
796 NamedAttrList namedAttributes;
797
798 // A helper to parse the operand segments.
799 auto parseMmaOperand = [&](StringRef operandName,
800 MMAOperandFragment &frag) -> LogicalResult {
801 if (parser.parseKeyword(operandName).failed())
802 return failure();
803 if (parser
804 .parseOperandList(frag.regs, OpAsmParser::Delimiter::OptionalSquare)
805 .failed())
806 return failure();
807 return success();
808 };
809
810 // Parse the operand segments.
811 if (parseMmaOperand("A", frags[0]).failed())
812 return failure();
813 if (parseMmaOperand("B", frags[1]).failed())
814 return failure();
815 if (parseMmaOperand("C", frags[2]).failed())
816 return failure();
817
818 if (parser.parseOptionalAttrDict(namedAttributes).failed())
819 return failure();
820
821 // Parse the type specification and resolve operands.
822 SmallVector<Type, 3> operandTypes;
823 if (failed(parser.parseColon()))
824 return failure();
825 if (failed(parser.parseLParen()))
826 return failure();
827 if (failed(parser.parseTypeList(operandTypes)))
828 return failure();
829 if (failed(parser.parseRParen()))
830 if (operandTypes.size() != 3)
831 return parser.emitError(
832 parser.getNameLoc(),
833 "expected one type for each operand segment but got " +
834 Twine(operandTypes.size()) + " types");
835 for (const auto &iter : llvm::enumerate(operandTypes)) {
836 auto &frag = frags[iter.index()];
837 frag.regTypes.resize(frag.regs.size(), iter.value());
838 if (failed(parser.resolveOperands(frag.regs, frag.regTypes,
839 parser.getNameLoc(), result.operands)))
840 return failure();
841 frag.elemtype = inferOperandMMAType(frag.regTypes[0],
842 /*isAccumulator*/ iter.index() < 2);
843 }
844
845 Type resultType;
846 if (parser.parseArrow() || parser.parseType(resultType))
847 return failure();
848 frags[3].elemtype = inferOperandMMAType(resultType, /*isAccumulator*/ true);
849
850 std::array<StringRef, 2> names{"multiplicandAPtxType",
851 "multiplicandBPtxType"};
852 for (unsigned idx = 0; idx < names.size(); idx++) {
853 const auto &frag = frags[idx];
854 std::optional<NamedAttribute> attr = namedAttributes.getNamed(names[idx]);
855 if (!frag.elemtype.has_value() && !attr.has_value()) {
856 return parser.emitError(
857 parser.getNameLoc(),
858 "attribute " + names[idx] +
859 " is not provided explicitly and cannot be inferred");
860 }
861 if (!attr.has_value())
862 result.addAttribute(
863 names[idx], MMATypesAttr::get(parser.getContext(), *frag.elemtype));
864 }
865
866 result.addTypes(resultType);
867 if (!namedAttributes.empty())
868 result.addAttributes(namedAttributes);
869 result.addAttribute(MmaOp::getOperandSegmentSizeAttr(),
870 builder.getDenseI32ArrayAttr({
871 static_cast<int32_t>(frags[0].regs.size()),
872 static_cast<int32_t>(frags[1].regs.size()),
873 static_cast<int32_t>(frags[2].regs.size()),
874 }));
875 return success();
876}
877
878LogicalResult MmaOp::verify() {
879 MLIRContext *context = getContext();
880 auto f16Ty = Float16Type::get(context);
881 auto i32Ty = IntegerType::get(context, 32);
882 auto f16x2Ty = VectorType::get(2, f16Ty);
883 auto f32Ty = Float32Type::get(context);
884 auto f16x2x4StructTy = LLVM::LLVMStructType::getLiteral(
885 context, {f16x2Ty, f16x2Ty, f16x2Ty, f16x2Ty});
886
887 auto s32x4StructTy =
888 LLVM::LLVMStructType::getLiteral(context, {i32Ty, i32Ty, i32Ty, i32Ty});
889 auto f32x8StructTy =
890 LLVM::LLVMStructType::getLiteral(context, SmallVector<Type>(8, f32Ty));
891 auto f16x2x2StructTy =
892 LLVM::LLVMStructType::getLiteral(context, {f16x2Ty, f16x2Ty});
893 auto f32x4StructTy =
894 LLVM::LLVMStructType::getLiteral(context, {f32Ty, f32Ty, f32Ty, f32Ty});
895 auto s32x2StructTy =
896 LLVM::LLVMStructType::getLiteral(context, {i32Ty, i32Ty});
897
898 std::array<int64_t, 3> mmaShape{getShapeAttr().getM(), getShapeAttr().getN(),
899 getShapeAttr().getK()};
900
901 // These variables define the set of allowed data types for matrices A, B, C,
902 // and result.
903 using AllowedShapes = SmallVector<std::array<int64_t, 3>, 2>;
904 using AllowedTypes = SmallVector<SmallVector<Type, 4>, 2>;
905 AllowedShapes allowedShapes;
906 AllowedTypes expectedA;
907 AllowedTypes expectedB;
908 AllowedTypes expectedC;
909 SmallVector<Type> expectedResult;
910
911 // When M = 16, we just need to calculate the number of 8xk tiles, where
912 // k is a factor that depends on the data type.
913 if (mmaShape[0] == 16) {
914 int64_t kFactor;
915 Type multiplicandFragType;
916 switch (*getMultiplicandAPtxType()) {
917 case MMATypes::tf32:
918 kFactor = 4;
919 multiplicandFragType = i32Ty;
920 expectedResult.push_back(LLVM::LLVMStructType::getLiteral(
921 context, {f32Ty, f32Ty, f32Ty, f32Ty}));
922 break;
923 case MMATypes::bf16:
924 kFactor = 8;
925 multiplicandFragType = i32Ty;
926 expectedResult.push_back(LLVM::LLVMStructType::getLiteral(
927 context, {f32Ty, f32Ty, f32Ty, f32Ty}));
928 break;
929 case MMATypes::f16:
930 kFactor = 8;
931 multiplicandFragType = f16x2Ty;
932 expectedResult.push_back(f16x2x2StructTy);
933 expectedResult.push_back(f32x4StructTy);
934 break;
935 case MMATypes::s4:
936 case MMATypes::u4:
937 kFactor = 32;
938 break;
939 case MMATypes::b1:
940 kFactor = 128;
941 break;
942 case MMATypes::s8:
943 case MMATypes::u8:
944 kFactor = 16;
945 break;
946 default:
947 return emitError("invalid shape or multiplicand type: " +
948 stringifyEnum(getMultiplicandAPtxType().value()));
949 }
950
951 if (isIntegerPtxType(getMultiplicandAPtxType().value())) {
952 expectedResult.push_back(s32x4StructTy);
953 expectedC.emplace_back(4, i32Ty);
954 multiplicandFragType = i32Ty;
955 } else {
956 expectedC.emplace_back(2, f16x2Ty);
957 expectedC.emplace_back(4, f32Ty);
958 }
959
960 int64_t unitA = (mmaShape[0] / 8) * (mmaShape[2] / kFactor);
961 int64_t unitB = (mmaShape[1] / 8) * (mmaShape[2] / kFactor);
962 expectedA.emplace_back(unitA, multiplicandFragType);
963 expectedB.emplace_back(unitB, multiplicandFragType);
964 allowedShapes.push_back({16, 8, kFactor});
965 allowedShapes.push_back({16, 8, kFactor * 2});
966
967 if (resultPtxType() != accumPtxType())
968 return emitOpError("ctype does not match dtype");
969 }
970
971 // In the M=8 case, there is only 1 possible case per data type.
972 if (mmaShape[0] == 8) {
973 if (*getMultiplicandAPtxType() == MMATypes::f16) {
974 expectedA.emplace_back(2, f16x2Ty);
975 expectedB.emplace_back(2, f16x2Ty);
976 expectedResult.push_back(f16x2x4StructTy);
977 expectedResult.push_back(f32x8StructTy);
978 expectedC.emplace_back(4, f16x2Ty);
979 expectedC.emplace_back(8, f32Ty);
980 allowedShapes.push_back({8, 8, 4});
981 }
982 if (*getMultiplicandAPtxType() == MMATypes::f64) {
983 Type f64Ty = Float64Type::get(context);
984 expectedA.emplace_back(1, f64Ty);
985 expectedB.emplace_back(1, f64Ty);
986 expectedC.emplace_back(2, f64Ty);
987 expectedResult.emplace_back(LLVM::LLVMStructType::getLiteral(
988 context, SmallVector<Type>(2, f64Ty)));
989 allowedShapes.push_back({8, 8, 4});
990 }
991 if (isIntegerPtxType(getMultiplicandAPtxType().value())) {
992 expectedA.push_back({i32Ty});
993 expectedB.push_back({i32Ty});
994 expectedC.push_back({i32Ty, i32Ty});
995 expectedResult.push_back(s32x2StructTy);
996 if (isInt4PtxType(getMultiplicandAPtxType().value()))
997 allowedShapes.push_back({8, 8, 32});
998 if (isInt8PtxType(getMultiplicandAPtxType().value()))
999 allowedShapes.push_back({8, 8, 16});
1000 if (getMultiplicandAPtxType().value() == MMATypes::b1)
1001 allowedShapes.push_back({8, 8, 128});
1002 }
1003 }
1004
1005 std::string errorMessage;
1006 llvm::raw_string_ostream errorStream(errorMessage);
1007
1008 // Check that we matched an existing shape/dtype combination.
1009 if (expectedA.empty() || expectedB.empty() || expectedC.empty() ||
1010 !llvm::is_contained(allowedShapes, mmaShape)) {
1011 errorStream << "unimplemented variant for MMA shape <";
1012 llvm::interleaveComma(mmaShape, errorStream);
1013 errorStream << ">";
1014 return emitOpError(errorMessage);
1015 }
1016
1017 // Verify the operand types for segments of A, B, and C operands.
1018 std::array<StringRef, 3> operandNames{"A", "B", "C"};
1019 for (const auto &iter : llvm::enumerate(
1020 SmallVector<AllowedTypes, 3>{expectedA, expectedB, expectedC})) {
1021 auto spec = this->getODSOperandIndexAndLength(iter.index());
1022 SmallVector<Type, 4> operandTySeg(operand_type_begin() + spec.first,
1023 operand_type_begin() + spec.first +
1024 spec.second);
1025 bool match = llvm::is_contained(iter.value(), operandTySeg);
1026
1027 if (!match) {
1028 errorStream << "Could not match types for the "
1029 << operandNames[iter.index()]
1030 << " operands; expected one of ";
1031 for (const auto &x : iter.value()) {
1032 errorStream << x.size() << "x" << x[0] << " ";
1033 }
1034 errorStream << "but got ";
1035 llvm::interleaveComma(operandTySeg, errorStream);
1036 return emitOpError(errorMessage);
1037 }
1038 }
1039
1040 // Check the result type
1041 if (!llvm::any_of(expectedResult, [&](Type expectedResultType) {
1042 return expectedResultType == getResult().getType();
1043 })) {
1044 errorStream
1045 << "Could not match allowed types for the result; expected one of ";
1046 llvm::interleaveComma(expectedResult, errorStream);
1047 errorStream << " but got " << getResult().getType();
1048 return emitOpError(errorMessage);
1049 }
1050
1051 // Ensure that binary MMA variants have a b1 MMA operation defined.
1052 if (getMultiplicandAPtxType() == MMATypes::b1 && !getB1Op()) {
1053 return emitOpError("op requires " + getB1OpAttrName().strref() +
1054 " attribute");
1055 }
1056
1057 // Ensure int4/int8 MMA variants specify the accum overflow behavior
1058 // attribute.
1059 if (isInt4PtxType(*getMultiplicandAPtxType()) ||
1060 isInt8PtxType(*getMultiplicandAPtxType())) {
1061 if (!getIntOverflowBehavior())
1062 return emitOpError("op requires " +
1063 getIntOverflowBehaviorAttrName().strref() +
1064 " attribute");
1065 }
1066
1067 // Validate layout combinations. According to the operation description, most
1068 // MMA operations require layoutA=row and layoutB=col. Only m8n8k4 with f16
1069 // can use other layout combinations.
1070 bool isM8N8K4_F16 =
1071 (mmaShape[0] == 8 && mmaShape[1] == 8 && mmaShape[2] == 4 &&
1072 getMultiplicandAPtxType() == MMATypes::f16);
1073
1074 if (!isM8N8K4_F16) {
1075 // For all other shapes/types, layoutA must be row and layoutB must be col
1076 if (getLayoutA() != MMALayout::row || getLayoutB() != MMALayout::col) {
1077 return emitOpError("requires layoutA = #nvvm.mma_layout<row> and "
1078 "layoutB = #nvvm.mma_layout<col> for shape <")
1079 << mmaShape[0] << ", " << mmaShape[1] << ", " << mmaShape[2]
1080 << "> with element types "
1081 << stringifyEnum(*getMultiplicandAPtxType()) << " and "
1082 << stringifyEnum(*getMultiplicandBPtxType())
1083 << ". Only m8n8k4 with f16 supports other layouts.";
1084 }
1085 }
1086
1087 return success();
1088}
1089
1090MMATypes MmaSpOp::accumPtxType() {
1091 std::optional<mlir::NVVM::MMATypes> val = MmaOp::inferOperandMMAType(
1092 getODSOperands(2).getTypes().front(), /*isAccumulator=*/true);
1093 assert(val.has_value() && "accumulator PTX type should always be inferrable");
1094 return val.value();
1095}
1096
1097MMATypes MmaSpOp::resultPtxType() {
1098 std::optional<mlir::NVVM::MMATypes> val =
1099 MmaOp::inferOperandMMAType(getResult().getType(), /*isAccumulator=*/true);
1100 assert(val.has_value() && "result PTX type should always be inferrable");
1101 return val.value();
1102}
1103
1105MmaSpOp::getIntrinsicIDAndArgs(Operation &op, LLVM::ModuleTranslation &mt,
1106 llvm::IRBuilderBase &builder) {
1107 auto thisOp = cast<NVVM::MmaSpOp>(op);
1108
1109 // Get operands
1111 for (mlir::Value v : thisOp.getOperands())
1112 args.push_back(mt.lookupValue(v));
1113
1114 // Get intrinsic ID using the existing getIntrinsicID method
1115 auto intId = MmaSpOp::getIntrinsicID(
1116 thisOp.getShape().getM(), thisOp.getShape().getN(),
1117 thisOp.getShape().getK(), thisOp.getIntOverflowBehavior(),
1118 thisOp.getOrderedMetadata(), thisOp.getKind(),
1119 *thisOp.getMultiplicandAPtxType(), *thisOp.getMultiplicandBPtxType(),
1120 thisOp.accumPtxType(), thisOp.resultPtxType());
1121
1122 return {intId, args};
1123}
1124
1125void MmaSpOp::print(OpAsmPrinter &p) {
1126 SmallVector<Type, 4> regTypes;
1127 struct MMAOperandFragment {
1128 StringRef operandName;
1129 StringRef ptxTypeAttr;
1130 SmallVector<Value, 4> regs;
1131 explicit MMAOperandFragment(StringRef name, StringRef ptxTypeName)
1132 : operandName(name), ptxTypeAttr(ptxTypeName) {}
1133 };
1134
1135 std::array<MMAOperandFragment, 5> frags{
1136 MMAOperandFragment("A", getMultiplicandAPtxTypeAttrName()),
1137 MMAOperandFragment("B", getMultiplicandBPtxTypeAttrName()),
1138 MMAOperandFragment("C", ""), MMAOperandFragment("sparseMetadata", ""),
1139 MMAOperandFragment("selector", "")};
1140 SmallVector<StringRef, 4> ignoreAttrNames{
1141 mlir::NVVM::MmaSpOp::getOperandSegmentSizeAttr()};
1142
1143 // Handle variadic operands A, B, C
1144 for (unsigned fragIdx = 0; fragIdx < 3; fragIdx++) {
1145 auto &frag = frags[fragIdx];
1146 auto varOperandSpec = getODSOperandIndexAndLength(fragIdx);
1147 for (auto operandIdx = varOperandSpec.first;
1148 operandIdx < varOperandSpec.first + varOperandSpec.second;
1149 operandIdx++) {
1150 frag.regs.push_back(this->getOperand(operandIdx));
1151 if (operandIdx == varOperandSpec.first) {
1152 regTypes.push_back(this->getOperand(operandIdx).getType());
1153 }
1154 }
1155 std::optional<MMATypes> inferredType = MmaOp::inferOperandMMAType(
1156 regTypes.back(), /*isAccumulator=*/fragIdx >= 2);
1157 if (inferredType)
1158 ignoreAttrNames.push_back(frag.ptxTypeAttr);
1159 }
1160
1161 // Handle sparse metadata and selector (single operands)
1162 frags[3].regs.push_back(getSparseMetadata());
1163 frags[4].regs.push_back(getSparsitySelector());
1164
1165 auto printMmaSpOperand = [&](const MMAOperandFragment &frag) -> void {
1166 p << " " << frag.operandName;
1167 p << "[";
1168 p.printOperands(frag.regs);
1169 p << "]";
1170 };
1171
1172 for (const auto &frag : frags)
1173 printMmaSpOperand(frag);
1174
1175 p.printOptionalAttrDict((*this)->getAttrs(), ignoreAttrNames);
1176 p << " : ";
1177 p << "(";
1178 for (int i = 0; i < 3; ++i) {
1179 p << regTypes[i];
1180 if (i < 2)
1181 p << ", ";
1182 }
1183 p << ") -> " << getResult().getType();
1184}
1185
1186void MmaSpOp::build(
1187 OpBuilder &builder, OperationState &result, Type resultType,
1188 ValueRange operandA, ValueRange operandB, ValueRange operandC,
1189 Value sparseMetadata, Value sparsitySelector, ArrayRef<int64_t> shape,
1190 std::optional<MMAIntOverflow> intOverflow,
1191 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes) {
1192
1193 assert(shape.size() == 3 && "expected shape to have size 3 (m, n, k)");
1194 MLIRContext *ctx = builder.getContext();
1195 result.addAttribute(
1196 "shape", builder.getAttr<MMAShapeAttr>(shape[0], shape[1], shape[2]));
1197
1198 result.addOperands(operandA);
1199 result.addOperands(operandB);
1200 result.addOperands(operandC);
1201 result.addOperands(sparseMetadata);
1202 result.addOperands(sparsitySelector);
1203
1204 if (multiplicandPtxTypes) {
1205 result.addAttribute("multiplicandAPtxType",
1206 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[0]));
1207 result.addAttribute("multiplicandBPtxType",
1208 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[1]));
1209 } else {
1210 if (auto res = MmaOp::inferOperandMMAType(operandA[0].getType(), false))
1211 result.addAttribute("multiplicandAPtxType", MMATypesAttr::get(ctx, *res));
1212 if (auto res = MmaOp::inferOperandMMAType(operandB[0].getType(), false))
1213 result.addAttribute("multiplicandBPtxType", MMATypesAttr::get(ctx, *res));
1214 }
1215
1216 if (intOverflow.has_value())
1217 result.addAttribute("intOverflowBehavior",
1218 MMAIntOverflowAttr::get(ctx, *intOverflow));
1219
1220 result.addTypes(resultType);
1221 result.addAttribute(
1222 MmaSpOp::getOperandSegmentSizeAttr(),
1223 builder.getDenseI32ArrayAttr({static_cast<int32_t>(operandA.size()),
1224 static_cast<int32_t>(operandB.size()),
1225 static_cast<int32_t>(operandC.size()), 1,
1226 1})); // sparseMetadata and sparsitySelector
1227}
1228
1229ParseResult MmaSpOp::parse(OpAsmParser &parser, OperationState &result) {
1230 struct MMAOperandFragment {
1231 std::optional<MMATypes> elemtype;
1232 SmallVector<OpAsmParser::UnresolvedOperand, 4> regs;
1233 SmallVector<Type> regTypes;
1234 };
1235
1236 Builder &builder = parser.getBuilder();
1237 std::array<MMAOperandFragment, 6> frags; // A, B, C, sparseMetadata, selector
1238
1239 NamedAttrList namedAttributes;
1240
1241 // A helper to parse the operand segments.
1242 auto parseMmaSpOperand = [&](StringRef operandName,
1243 MMAOperandFragment &frag) -> LogicalResult {
1244 if (parser.parseKeyword(operandName).failed())
1245 return failure();
1246 if (parser
1247 .parseOperandList(frag.regs, OpAsmParser::Delimiter::OptionalSquare)
1248 .failed())
1249 return failure();
1250 return success();
1251 };
1252
1253 // Parse the operand segments.
1254 if (parseMmaSpOperand("A", frags[0]).failed())
1255 return failure();
1256 if (parseMmaSpOperand("B", frags[1]).failed())
1257 return failure();
1258 if (parseMmaSpOperand("C", frags[2]).failed())
1259 return failure();
1260 if (parseMmaSpOperand("sparseMetadata", frags[3]).failed())
1261 return failure();
1262 if (parseMmaSpOperand("selector", frags[4]).failed())
1263 return failure();
1264
1265 if (parser.parseOptionalAttrDict(namedAttributes).failed())
1266 return failure();
1267
1268 // Parse the type specification and resolve operands.
1269 SmallVector<Type, 3> operandTypes;
1270 if (failed(parser.parseColon()))
1271 return failure();
1272 if (failed(parser.parseLParen()))
1273 return failure();
1274 if (failed(parser.parseTypeList(operandTypes)))
1275 return failure();
1276 if (failed(parser.parseRParen()))
1277 return failure();
1278 if (operandTypes.size() != 3)
1279 return parser.emitError(
1280 parser.getNameLoc(),
1281 "expected one type for each operand segment but got " +
1282 Twine(operandTypes.size()) + " types");
1283 for (const auto &iter : llvm::enumerate(operandTypes)) {
1284 auto &frag = frags[iter.index()];
1285 frag.regTypes.resize(frag.regs.size(), iter.value());
1286 if (failed(parser.resolveOperands(frag.regs, frag.regTypes,
1287 parser.getNameLoc(), result.operands)))
1288 return failure();
1289 frag.elemtype =
1290 MmaOp::inferOperandMMAType(frag.regTypes[0],
1291 /*isAccumulator*/ iter.index() >= 2);
1292 }
1293
1294 Type resultType;
1295 if (parser.parseArrow() || parser.parseType(resultType))
1296 return failure();
1297 frags[5].elemtype =
1298 MmaOp::inferOperandMMAType(resultType, /*isAccumulator*/ true);
1299
1300 // Resolve sparse metadata and selector (assume i32 type)
1301 Type i32Type = builder.getIntegerType(32);
1302 if (parser
1303 .resolveOperands(frags[3].regs, i32Type, parser.getCurrentLocation(),
1304 result.operands)
1305 .failed())
1306 return failure();
1307 if (parser
1308 .resolveOperands(frags[4].regs, i32Type, parser.getCurrentLocation(),
1309 result.operands)
1310 .failed())
1311 return failure();
1312
1313 std::array<StringRef, 2> names{"multiplicandAPtxType",
1314 "multiplicandBPtxType"};
1315 for (unsigned idx = 0; idx < names.size(); idx++) {
1316 const auto &frag = frags[idx];
1317 std::optional<NamedAttribute> attr = namedAttributes.getNamed(names[idx]);
1318 if (!frag.elemtype.has_value() && !attr.has_value()) {
1319 return parser.emitError(
1320 parser.getNameLoc(),
1321 "attribute " + names[idx] +
1322 " is not provided explicitly and cannot be inferred");
1323 }
1324 if (!attr.has_value())
1325 result.addAttribute(
1326 names[idx], MMATypesAttr::get(parser.getContext(), *frag.elemtype));
1327 }
1328
1329 result.addTypes(resultType);
1330 if (!namedAttributes.empty())
1331 result.addAttributes(namedAttributes);
1332 result.addAttribute(MmaSpOp::getOperandSegmentSizeAttr(),
1333 builder.getDenseI32ArrayAttr({
1334 static_cast<int32_t>(frags[0].regs.size()),
1335 static_cast<int32_t>(frags[1].regs.size()),
1336 static_cast<int32_t>(frags[2].regs.size()),
1337 1, // sparseMetadata
1338 1 // sparsitySelector
1339 }));
1340 return success();
1341}
1342
1343LogicalResult MmaSpOp::verify() {
1344 MLIRContext *context = getContext();
1345 auto f16Ty = Float16Type::get(context);
1346 auto i32Ty = IntegerType::get(context, 32);
1347 auto f16x2Ty = VectorType::get(2, f16Ty);
1348 auto f32Ty = Float32Type::get(context);
1349 auto f16x2x4StructTy = LLVM::LLVMStructType::getLiteral(
1350 context, {f16x2Ty, f16x2Ty, f16x2Ty, f16x2Ty});
1351
1352 auto s32x4StructTy =
1353 LLVM::LLVMStructType::getLiteral(context, {i32Ty, i32Ty, i32Ty, i32Ty});
1354 auto f32x8StructTy =
1355 LLVM::LLVMStructType::getLiteral(context, SmallVector<Type>(8, f32Ty));
1356 auto f16x2x2StructTy =
1357 LLVM::LLVMStructType::getLiteral(context, {f16x2Ty, f16x2Ty});
1358 auto f32x4StructTy =
1359 LLVM::LLVMStructType::getLiteral(context, {f32Ty, f32Ty, f32Ty, f32Ty});
1360 auto s32x2StructTy =
1361 LLVM::LLVMStructType::getLiteral(context, {i32Ty, i32Ty});
1362
1363 std::array<int64_t, 3> mmaShape{getShapeAttr().getM(), getShapeAttr().getN(),
1364 getShapeAttr().getK()};
1365
1366 // These variables define the set of allowed data types for matrices A, B, C,
1367 // and result.
1368 using AllowedShapes = SmallVector<std::array<int64_t, 3>, 2>;
1369 using AllowedTypes = SmallVector<SmallVector<Type, 4>, 2>;
1370 AllowedShapes allowedShapes;
1371 AllowedTypes expectedA;
1372 AllowedTypes expectedB;
1373 AllowedTypes expectedC;
1374 SmallVector<Type> expectedResult;
1375
1376 // When M = 16, we just need to calculate the number of 8xk tiles, where
1377 // k is a factor that depends on the data type.
1378 if (mmaShape[0] == 16) {
1379 int64_t kFactor;
1380 Type multiplicandFragType;
1381 switch (*getMultiplicandAPtxType()) {
1382 case MMATypes::tf32:
1383 kFactor = 4;
1384 multiplicandFragType = i32Ty;
1385 expectedResult.push_back(LLVM::LLVMStructType::getLiteral(
1386 context, {f32Ty, f32Ty, f32Ty, f32Ty}));
1387 // Sparse MMA supports m16n8k8 and m16n8k16 for tf32
1388 allowedShapes.push_back({16, 8, 8});
1389 allowedShapes.push_back({16, 8, 16});
1390 break;
1391 case MMATypes::bf16:
1392 kFactor = 8;
1393 multiplicandFragType = i32Ty;
1394 expectedResult.push_back(LLVM::LLVMStructType::getLiteral(
1395 context, {f32Ty, f32Ty, f32Ty, f32Ty}));
1396 // Sparse MMA supports m16n8k16 and m16n8k32 for bf16
1397 allowedShapes.push_back({16, 8, 16});
1398 allowedShapes.push_back({16, 8, 32});
1399 break;
1400 case MMATypes::f16:
1401 kFactor = 8;
1402 multiplicandFragType = f16x2Ty;
1403 expectedResult.push_back(f16x2x2StructTy);
1404 expectedResult.push_back(f32x4StructTy);
1405 // Sparse MMA supports m16n8k16 and m16n8k32 for f16
1406 allowedShapes.push_back({16, 8, 16});
1407 allowedShapes.push_back({16, 8, 32});
1408 break;
1409 case MMATypes::s4:
1410 case MMATypes::u4:
1411 kFactor = 32;
1412 // Sparse MMA supports m16n8k64 and m16n8k128 for s4/u4
1413 allowedShapes.push_back({16, 8, 64});
1414 allowedShapes.push_back({16, 8, 128});
1415 break;
1416 case MMATypes::s8:
1417 case MMATypes::u8:
1418 kFactor = 16;
1419 // Sparse MMA supports m16n8k32 and m16n8k64 for s8/u8
1420 allowedShapes.push_back({16, 8, 32});
1421 allowedShapes.push_back({16, 8, 64});
1422 break;
1423 case MMATypes::e4m3:
1424 case MMATypes::e5m2:
1425 case MMATypes::e3m2:
1426 case MMATypes::e2m3:
1427 case MMATypes::e2m1:
1428 kFactor = 32;
1429 multiplicandFragType = i32Ty;
1430 expectedResult.push_back(f16x2x2StructTy);
1431 expectedResult.push_back(f32x4StructTy);
1432 // Sparse MMA supports m16n8k64 for FP8 types
1433 allowedShapes.push_back({16, 8, 64});
1434 break;
1435 default:
1436 return emitError("invalid shape or multiplicand type: " +
1437 stringifyEnum(getMultiplicandAPtxType().value()));
1438 }
1439
1440 if (isIntegerPtxType(getMultiplicandAPtxType().value())) {
1441 expectedResult.push_back(s32x4StructTy);
1442 expectedC.emplace_back(4, i32Ty);
1443 multiplicandFragType = i32Ty;
1444 } else if (*getMultiplicandAPtxType() >= MMATypes::e4m3 &&
1445 *getMultiplicandAPtxType() <= MMATypes::e2m1) {
1446 // FP8 types
1447 expectedC.emplace_back(2, f16x2Ty);
1448 expectedC.emplace_back(4, f32Ty);
1449 } else {
1450 expectedC.emplace_back(2, f16x2Ty);
1451 expectedC.emplace_back(4, f32Ty);
1452 }
1453
1454 // For sparse MMA, A operand is compressed (2:4 sparsity means half the
1455 // elements)
1456 int64_t unitA = (mmaShape[0] / 8) * (mmaShape[2] / kFactor) / 2;
1457 int64_t unitB = (mmaShape[1] / 8) * (mmaShape[2] / kFactor);
1458 expectedA.emplace_back(unitA, multiplicandFragType);
1459 expectedB.emplace_back(unitB, multiplicandFragType);
1460
1461 if (resultPtxType() != accumPtxType())
1462 return emitOpError("ctype does not match dtype");
1463 }
1464
1465 // In the M=8 case, there is only 1 possible case per data type.
1466 if (mmaShape[0] == 8) {
1467 if (*getMultiplicandAPtxType() == MMATypes::f16) {
1468 expectedA.emplace_back(2, f16x2Ty);
1469 expectedB.emplace_back(2, f16x2Ty);
1470 expectedResult.push_back(f16x2x4StructTy);
1471 expectedResult.push_back(f32x8StructTy);
1472 expectedC.emplace_back(4, f16x2Ty);
1473 expectedC.emplace_back(8, f32Ty);
1474 allowedShapes.push_back({8, 8, 4});
1475 }
1476 if (*getMultiplicandAPtxType() == MMATypes::f64) {
1477 Type f64Ty = Float64Type::get(context);
1478 expectedA.emplace_back(1, f64Ty);
1479 expectedB.emplace_back(1, f64Ty);
1480 expectedC.emplace_back(2, f64Ty);
1481 expectedResult.emplace_back(LLVM::LLVMStructType::getLiteral(
1482 context, SmallVector<Type>(2, f64Ty)));
1483 allowedShapes.push_back({8, 8, 4});
1484 }
1485 if (isIntegerPtxType(getMultiplicandAPtxType().value())) {
1486 expectedA.push_back({i32Ty});
1487 expectedB.push_back({i32Ty});
1488 expectedC.push_back({i32Ty, i32Ty});
1489 expectedResult.push_back(s32x2StructTy);
1490 if (isInt4PtxType(getMultiplicandAPtxType().value()))
1491 allowedShapes.push_back({8, 8, 32});
1492 if (isInt8PtxType(getMultiplicandAPtxType().value()))
1493 allowedShapes.push_back({8, 8, 16});
1494 }
1495 }
1496
1497 std::string errorMessage;
1498 llvm::raw_string_ostream errorStream(errorMessage);
1499
1500 // Check that we matched an existing shape/dtype combination.
1501 if (expectedA.empty() || expectedB.empty() || expectedC.empty() ||
1502 !llvm::is_contained(allowedShapes, mmaShape)) {
1503 errorStream << "unimplemented variant for MMA shape <";
1504 llvm::interleaveComma(mmaShape, errorStream);
1505 errorStream << ">";
1506 return emitOpError(errorMessage);
1507 }
1508
1509 // Verify the operand types for segments of A, B, and C operands.
1510 std::array<StringRef, 3> operandNames{"A", "B", "C"};
1511 for (const auto &iter : llvm::enumerate(
1512 SmallVector<AllowedTypes, 3>{expectedA, expectedB, expectedC})) {
1513 auto spec = this->getODSOperandIndexAndLength(iter.index());
1514 SmallVector<Type, 4> operandTySeg(operand_type_begin() + spec.first,
1515 operand_type_begin() + spec.first +
1516 spec.second);
1517 bool match = llvm::is_contained(iter.value(), operandTySeg);
1518
1519 if (!match) {
1520 errorStream << "Could not match types for the "
1521 << operandNames[iter.index()]
1522 << " operands; expected one of ";
1523 for (const auto &x : iter.value()) {
1524 errorStream << x.size() << "x" << x[0] << " ";
1525 }
1526 errorStream << "but got ";
1527 llvm::interleaveComma(operandTySeg, errorStream);
1528 return emitOpError(errorMessage);
1529 }
1530 }
1531
1532 // Check the result type
1533 if (!llvm::any_of(expectedResult, [&](Type expectedResultType) {
1534 return expectedResultType == getResult().getType();
1535 })) {
1536 errorStream
1537 << "Could not match allowed types for the result; expected one of ";
1538 llvm::interleaveComma(expectedResult, errorStream);
1539 errorStream << " but got " << getResult().getType();
1540 return emitOpError(errorMessage);
1541 }
1542
1543 // Ensure int4/int8 MMA variants specify the accum overflow behavior
1544 // attribute.
1545 if (isInt4PtxType(*getMultiplicandAPtxType()) ||
1546 isInt8PtxType(*getMultiplicandAPtxType())) {
1547 if (!getIntOverflowBehavior())
1548 return emitOpError("op requires " +
1549 getIntOverflowBehaviorAttrName().strref() +
1550 " attribute");
1551 }
1552
1553 // Validate sparse metadata type (should be i32)
1554 if (!getSparseMetadata().getType().isInteger(32)) {
1555 return emitOpError() << "sparse metadata must be i32 type";
1556 }
1557
1558 // Validate sparsity selector type (should be i32)
1559 if (!getSparsitySelector().getType().isInteger(32)) {
1560 return emitOpError() << "sparsity selector must be i32 type";
1561 }
1562
1563 return success();
1564}
1565
1566//===----------------------------------------------------------------------===//
1567// MMA Block Scale Operations - Shared Helpers
1568//===----------------------------------------------------------------------===//
1569
1570namespace {
1571// Shared structure for MMA operand fragments (A, B, C)
1572struct MMAOperandFragment {
1573 StringRef operandName;
1574 StringRef ptxTypeAttr;
1575 SmallVector<Value, 4> regs;
1576 explicit MMAOperandFragment(StringRef name, StringRef ptxTypeName)
1577 : operandName(name), ptxTypeAttr(ptxTypeName) {}
1578};
1579} // namespace
1580
1581// Helper to print operand list in the format: name[operands]
1582static void printOperandList(OpAsmPrinter &p, StringRef name,
1583 ArrayRef<Value> operands) {
1584 p << " " << name << "[";
1585 p.printOperands(operands);
1586 p << "]";
1587}
1588
1589// Helper to parse operand list in the format: name[operands]
1590static LogicalResult
1591parseMmaOperand(OpAsmParser &parser, StringRef operandName,
1593 if (parser.parseKeyword(operandName).failed())
1594 return failure();
1596 .failed())
1597 return failure();
1598 return success();
1599}
1600
1601// Helper to process operand fragments and determine which attributes can be
1602// inferred
1603template <typename Op>
1604static void
1605processOperandFragments(Op &op, std::array<MMAOperandFragment, 3> &frags,
1606 SmallVectorImpl<Type> &regTypes,
1607 SmallVectorImpl<StringRef> &ignoreAttrNames) {
1608 for (unsigned fragIdx = 0; fragIdx < frags.size(); fragIdx++) {
1609 auto &frag = frags[fragIdx];
1610 auto varOperandSpec = op.getODSOperandIndexAndLength(fragIdx);
1611 for (auto operandIdx = varOperandSpec.first;
1612 operandIdx < varOperandSpec.first + varOperandSpec.second;
1613 operandIdx++) {
1614 frag.regs.push_back(op.getOperand(operandIdx));
1615 if (fragIdx == 0 && operandIdx == varOperandSpec.first) {
1616 regTypes.push_back(op.getOperand(operandIdx).getType());
1617 }
1618 }
1619 if (fragIdx < 2) {
1620 regTypes.push_back(frag.regs[0].getType());
1621 }
1622 std::optional<MMATypes> inferredType =
1623 MmaOp::inferOperandMMAType(regTypes.back(),
1624 /*isAccumulator=*/fragIdx >= 2);
1625 if (inferredType)
1626 ignoreAttrNames.push_back(frag.ptxTypeAttr);
1627 }
1628}
1629
1630// Helper to parse type signature: (A_type, B_type, C_type)
1631static LogicalResult
1633 SmallVectorImpl<Type> &operandTypes) {
1634 if (parser.parseColon().failed() || parser.parseLParen().failed())
1635 return failure();
1636
1637 auto typeParser = [&]() {
1638 Type ty;
1639 if (parser.parseType(ty).failed())
1640 return failure();
1641 operandTypes.push_back(ty);
1642 return success();
1643 };
1644 if (parser.parseCommaSeparatedList(typeParser))
1645 return failure();
1646
1647 if (operandTypes.size() != 3)
1648 return parser.emitError(parser.getCurrentLocation(),
1649 "expected exactly 3 types");
1650
1651 return parser.parseRParen();
1652}
1653
1654// Helper to infer and set multiplicand PTX type attributes
1655static void
1657 const SmallVectorImpl<Type> &operandTypes) {
1658 if (!attrs.get("multiplicandAPtxType")) {
1659 if (auto inferredType =
1660 MmaOp::inferOperandMMAType(operandTypes[0], false)) {
1661 attrs.set("multiplicandAPtxType", MMATypesAttr::get(ctx, *inferredType));
1662 }
1663 }
1664 if (!attrs.get("multiplicandBPtxType")) {
1665 if (auto inferredType =
1666 MmaOp::inferOperandMMAType(operandTypes[1], false)) {
1667 attrs.set("multiplicandBPtxType", MMATypesAttr::get(ctx, *inferredType));
1668 }
1669 }
1670}
1671
1672// Helper to add common block scale properties
1673template <typename OpType>
1676 ScaleVecSize scaleVecSize,
1677 BlockScaleFormat blockScaleFormat,
1678 MMABlockScaleKind kind) {
1679 MLIRContext *ctx = builder.getContext();
1680 auto &properties = result.getOrAddProperties<typename OpType::Properties>();
1681 properties.setShape(
1682 builder.getAttr<MMAShapeAttr>(shape[0], shape[1], shape[2]));
1683 properties.setScaleVecSize(ScaleVecSizeAttr::get(ctx, scaleVecSize));
1684 properties.setBlockScaleFormat(
1685 BlockScaleFormatAttr::get(ctx, blockScaleFormat));
1686 properties.setKind(MMABlockScaleKindAttr::get(ctx, kind));
1687}
1688
1689// Helper to infer and add multiplicand PTX types to builder
1692 ValueRange operandB,
1693 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes) {
1694 if (multiplicandPtxTypes) {
1695 result.addAttribute("multiplicandAPtxType",
1696 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[0]));
1697 result.addAttribute("multiplicandBPtxType",
1698 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[1]));
1699 } else {
1700 if (auto res = MmaOp::inferOperandMMAType(operandA[0].getType(), false))
1701 result.addAttribute("multiplicandAPtxType", MMATypesAttr::get(ctx, *res));
1702 if (auto res = MmaOp::inferOperandMMAType(operandB[0].getType(), false))
1703 result.addAttribute("multiplicandBPtxType", MMATypesAttr::get(ctx, *res));
1704 }
1705}
1706
1707// Template helper for common accumPtxType/resultPtxType implementation
1708template <typename OpTy>
1709static MMATypes inferPtxTypeFromResult(OpTy op) {
1710 return *MmaOp::inferOperandMMAType(
1711 cast<LLVM::LLVMStructType>(op.getRes().getType()).getBody()[0],
1712 /*isAccumulator=*/true);
1713}
1714
1715//===----------------------------------------------------------------------===//
1716// MmaBlockScaleOp
1717//===----------------------------------------------------------------------===//
1718
1719void MmaBlockScaleOp::print(OpAsmPrinter &p) {
1720 SmallVector<Type, 4> regTypes;
1721 std::array<MMAOperandFragment, 3> frags{
1722 MMAOperandFragment("A", getMultiplicandAPtxTypeAttrName()),
1723 MMAOperandFragment("B", getMultiplicandBPtxTypeAttrName()),
1724 MMAOperandFragment("C", "")};
1725 SmallVector<StringRef, 4> ignoreAttrNames{
1726 mlir::NVVM::MmaBlockScaleOp::getOperandSegmentSizeAttr()};
1727
1728 processOperandFragments(*this, frags, regTypes, ignoreAttrNames);
1729
1730 // Print A, B, C operands
1731 for (const auto &frag : frags)
1732 printOperandList(p, frag.operandName, frag.regs);
1733
1734 // Print scale operands
1735 printOperandList(p, "scaleA",
1736 {getScaleAData(), getByteIdA(), getThreadIdA()});
1737 printOperandList(p, "scaleB",
1738 {getScaleBData(), getByteIdB(), getThreadIdB()});
1739
1740 p.printOptionalAttrDict(this->getOperation()->getAttrs(), ignoreAttrNames);
1741
1742 // Print type signature
1743 p << " : (";
1744 llvm::interleaveComma(SmallVector<Type, 3>{frags[0].regs[0].getType(),
1745 frags[1].regs[0].getType(),
1746 frags[2].regs[0].getType()},
1747 p);
1748 p << ")";
1749 p.printArrowTypeList(TypeRange{this->getRes().getType()});
1750}
1751
1752ParseResult MmaBlockScaleOp::parse(OpAsmParser &parser,
1754 struct LocalOperandFragment {
1755 std::optional<MMATypes> elemtype;
1756 SmallVector<OpAsmParser::UnresolvedOperand, 4> regs;
1757 };
1758
1759 Builder &builder = parser.getBuilder();
1760 std::array<LocalOperandFragment, 3> frags;
1761 NamedAttrList namedAttributes;
1762
1763 // Parse A[...] B[...] C[...]
1764 if (parseMmaOperand(parser, "A", frags[0].regs).failed() ||
1765 parseMmaOperand(parser, "B", frags[1].regs).failed() ||
1766 parseMmaOperand(parser, "C", frags[2].regs).failed())
1767 return failure();
1768
1769 // Parse scale operands: scaleA[...] scaleB[...]
1770 SmallVector<OpAsmParser::UnresolvedOperand, 3> scaleAOperands, scaleBOperands;
1771 if (parseMmaOperand(parser, "scaleA", scaleAOperands).failed() ||
1772 parseMmaOperand(parser, "scaleB", scaleBOperands).failed())
1773 return failure();
1774
1775 if (parser.parseOptionalAttrDict(namedAttributes).failed())
1776 return failure();
1777
1778 // Parse type signature
1779 SmallVector<Type, 3> operandTypes;
1780 if (parseMmaTypeSignature(parser, operandTypes).failed())
1781 return failure();
1782
1783 // Parse result type
1784 SmallVector<Type, 1> resultTypes;
1785 if (parser.parseArrowTypeList(resultTypes).failed())
1786 return failure();
1787
1788 // Infer element types and resolve operands
1789 for (const auto &[idx, frag] : llvm::enumerate(frags)) {
1790 frag.elemtype = MmaOp::inferOperandMMAType(operandTypes[idx],
1791 /*isAccumulator=*/idx >= 2);
1792 if (parser
1793 .resolveOperands(frag.regs, operandTypes[idx], parser.getNameLoc(),
1794 result.operands)
1795 .failed())
1796 return failure();
1797 }
1798
1799 // Resolve scale operands
1800 SmallVector<Type, 3> scaleTypes = {builder.getI32Type(), builder.getI16Type(),
1801 builder.getI16Type()};
1802 if (parser
1803 .resolveOperands(scaleAOperands, scaleTypes, parser.getNameLoc(),
1804 result.operands)
1805 .failed() ||
1806 parser
1807 .resolveOperands(scaleBOperands, scaleTypes, parser.getNameLoc(),
1808 result.operands)
1809 .failed())
1810 return failure();
1811
1812 // Add attributes
1813 result.addAttributes(namedAttributes);
1814 inferAndSetMultiplicandTypes(parser.getContext(), result.attributes,
1815 operandTypes);
1816
1817 result.addTypes(resultTypes);
1818 result.addAttribute(MmaBlockScaleOp::getOperandSegmentSizeAttr(),
1819 builder.getDenseI32ArrayAttr({
1820 static_cast<int32_t>(frags[0].regs.size()),
1821 static_cast<int32_t>(frags[1].regs.size()),
1822 static_cast<int32_t>(frags[2].regs.size()),
1823 1, // scaleAData
1824 1, // byteIdA
1825 1, // threadIdA
1826 1, // scaleBData
1827 1, // byteIdB
1828 1 // threadIdB
1829 }));
1830 return success();
1831}
1832
1833void MmaBlockScaleOp::build(
1834 OpBuilder &builder, OperationState &result, Type resultType,
1835 ValueRange operandA, ValueRange operandB, ValueRange operandC,
1836 Value scaleAData, Value byteIdA, Value threadIdA, Value scaleBData,
1837 Value byteIdB, Value threadIdB, ArrayRef<int64_t> shape,
1838 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes,
1839 ScaleVecSize scaleVecSize, BlockScaleFormat blockScaleFormat,
1840 MMABlockScaleKind kind) {
1841 assert(shape.size() == 3 && "expected shape to have size 3 (m, n, k)");
1842
1844 blockScaleFormat, kind);
1845
1846 result.addOperands(operandA);
1847 result.addOperands(operandB);
1848 result.addOperands(operandC);
1849 result.addOperands(
1850 {scaleAData, byteIdA, threadIdA, scaleBData, byteIdB, threadIdB});
1851
1852 addInferredMultiplicandTypes(builder.getContext(), result, operandA, operandB,
1853 multiplicandPtxTypes);
1854
1855 result.addTypes(resultType);
1856 result.addAttribute(MmaBlockScaleOp::getOperandSegmentSizeAttr(),
1857 builder.getDenseI32ArrayAttr({
1858 static_cast<int32_t>(operandA.size()),
1859 static_cast<int32_t>(operandB.size()),
1860 static_cast<int32_t>(operandC.size()),
1861 1, // scaleAData
1862 1, // byteIdA
1863 1, // threadIdA
1864 1, // scaleBData
1865 1, // byteIdB
1866 1 // threadIdB
1867 }));
1868}
1869
1870NVVM::IDArgPair MmaBlockScaleOp::getIntrinsicIDAndArgs(
1871 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
1872 auto curOp = cast<NVVM::MmaBlockScaleOp>(op);
1873
1875 // Add A, B, C operands
1876 for (Value operand : curOp.getOperandA())
1877 args.push_back(mt.lookupValue(operand));
1878 for (Value operand : curOp.getOperandB())
1879 args.push_back(mt.lookupValue(operand));
1880 for (Value operand : curOp.getOperandC())
1881 args.push_back(mt.lookupValue(operand));
1882
1883 // Add scale operands
1884 args.push_back(mt.lookupValue(curOp.getScaleAData()));
1885 args.push_back(mt.lookupValue(curOp.getByteIdA()));
1886 args.push_back(mt.lookupValue(curOp.getThreadIdA()));
1887 args.push_back(mt.lookupValue(curOp.getScaleBData()));
1888 args.push_back(mt.lookupValue(curOp.getByteIdB()));
1889 args.push_back(mt.lookupValue(curOp.getThreadIdB()));
1890
1891 unsigned intId = MmaBlockScaleOp::getIntrinsicID(
1892 curOp.getShape().getM(), curOp.getShape().getN(), curOp.getShape().getK(),
1893 *curOp.getMultiplicandAPtxType(), *curOp.getMultiplicandBPtxType(),
1894 inferPtxTypeFromResult(curOp), curOp.getScaleVecSize(),
1895 curOp.getBlockScaleFormat(), curOp.getKind());
1896
1897 return {intId, args};
1898}
1899
1900LogicalResult MmaBlockScaleOp::verify() {
1901 LogicalResult result = success();
1902 int m = getShape().getM();
1903 int n = getShape().getN();
1904 int k = getShape().getK();
1905
1906 if (m == 16 && n == 8 && k == 64) {
1907 if (getMultiplicandAPtxType() != NVVM::MMATypes::e2m1 ||
1908 getMultiplicandBPtxType() != NVVM::MMATypes::e2m1)
1910 "unsupported MMATypes attribute for mma.m16n8k64.(mxf4nvf4|mxf4)");
1911 if (getKind() == NVVM::MMABlockScaleKind::MXF4) {
1912 if (getScaleVecSize() != NVVM::ScaleVecSize::X2)
1914 "unsupported ScaleVecSize attribute for mma.m16n8k64.mxf4");
1915 if (getBlockScaleFormat() != NVVM::BlockScaleFormat::UE8M0)
1917 "unsupported BlockScaleFormat attribute for mma.m16n8k64.mxf4");
1918 } else if (getKind() == NVVM::MMABlockScaleKind::MXF4NVF4) {
1919 if (!((getScaleVecSize() == NVVM::ScaleVecSize::X2 &&
1920 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0) ||
1921 (getScaleVecSize() == NVVM::ScaleVecSize::X4 &&
1922 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE4M3)))
1923 result = emitOpError("unsupported ScaleVecSize and BlockScaleFormat "
1924 "attributes for mma.m16n8k64.mxf4nvf4");
1925 } else {
1926 result = emitOpError("unsupported Kind attribute for mma.m16n8k64");
1927 }
1928 } else if (m == 16 && n == 8 && k == 32) {
1929 if (!(getKind() == NVVM::MMABlockScaleKind::MXF8F6F4 &&
1930 getScaleVecSize() == NVVM::ScaleVecSize::X1 &&
1931 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0))
1932 result =
1933 emitOpError("unsupported Kind, ScaleVecSize and BlockScaleFormat "
1934 "attributes for mma.m16n8k32");
1935 } else {
1936 result = emitOpError("unsupported Geom for mma with block scaling");
1937 }
1938 return result;
1939}
1940
1941//===----------------------------------------------------------------------===//
1942// MmaSpBlockScaleOp
1943//===----------------------------------------------------------------------===//
1944
1945void MmaSpBlockScaleOp::print(OpAsmPrinter &p) {
1946 SmallVector<Type, 4> regTypes;
1947 std::array<MMAOperandFragment, 3> frags{
1948 MMAOperandFragment("A", getMultiplicandAPtxTypeAttrName()),
1949 MMAOperandFragment("B", getMultiplicandBPtxTypeAttrName()),
1950 MMAOperandFragment("C", "")};
1951 SmallVector<StringRef, 4> ignoreAttrNames{
1952 mlir::NVVM::MmaSpBlockScaleOp::getOperandSegmentSizeAttr()};
1953
1954 processOperandFragments(*this, frags, regTypes, ignoreAttrNames);
1955
1956 // Print A, B, C operands
1957 for (const auto &frag : frags)
1958 printOperandList(p, frag.operandName, frag.regs);
1959
1960 // Print sparse-specific operands
1961 printOperandList(p, "sparseMetadata", {getSparseMetadata()});
1962 printOperandList(p, "selector", {getSparsitySelector()});
1963
1964 // Print scale operands
1965 printOperandList(p, "scaleA",
1966 {getScaleAData(), getByteIdA(), getThreadIdA()});
1967 printOperandList(p, "scaleB",
1968 {getScaleBData(), getByteIdB(), getThreadIdB()});
1969
1970 p.printOptionalAttrDict(this->getOperation()->getAttrs(), ignoreAttrNames);
1971
1972 // Print type signature
1973 p << " : (";
1974 llvm::interleaveComma(SmallVector<Type, 3>{frags[0].regs[0].getType(),
1975 frags[1].regs[0].getType(),
1976 frags[2].regs[0].getType()},
1977 p);
1978 p << ")";
1979 p.printArrowTypeList(TypeRange{this->getRes().getType()});
1980}
1981
1982ParseResult MmaSpBlockScaleOp::parse(OpAsmParser &parser,
1984 struct LocalOperandFragment {
1985 std::optional<MMATypes> elemtype;
1986 SmallVector<OpAsmParser::UnresolvedOperand, 4> regs;
1987 };
1988
1989 Builder &builder = parser.getBuilder();
1990 std::array<LocalOperandFragment, 3> frags;
1991 NamedAttrList namedAttributes;
1992
1993 // Parse A[...] B[...] C[...]
1994 if (parseMmaOperand(parser, "A", frags[0].regs).failed() ||
1995 parseMmaOperand(parser, "B", frags[1].regs).failed() ||
1996 parseMmaOperand(parser, "C", frags[2].regs).failed())
1997 return failure();
1998
1999 // Parse sparse-specific operands
2001 selectorOperands;
2002 if (parseMmaOperand(parser, "sparseMetadata", metadataOperands).failed() ||
2003 parseMmaOperand(parser, "selector", selectorOperands).failed())
2004 return failure();
2005
2006 // Parse scale operands
2007 SmallVector<OpAsmParser::UnresolvedOperand, 3> scaleAOperands, scaleBOperands;
2008 if (parseMmaOperand(parser, "scaleA", scaleAOperands).failed() ||
2009 parseMmaOperand(parser, "scaleB", scaleBOperands).failed())
2010 return failure();
2011
2012 if (parser.parseOptionalAttrDict(namedAttributes).failed())
2013 return failure();
2014
2015 // Parse type signature
2016 SmallVector<Type, 3> operandTypes;
2017 if (parseMmaTypeSignature(parser, operandTypes).failed())
2018 return failure();
2019
2020 // Parse result type
2021 SmallVector<Type, 1> resultTypes;
2022 if (parser.parseArrowTypeList(resultTypes).failed())
2023 return failure();
2024
2025 // Infer element types and resolve operands
2026 for (const auto &[idx, frag] : llvm::enumerate(frags)) {
2027 frag.elemtype = MmaOp::inferOperandMMAType(operandTypes[idx],
2028 /*isAccumulator=*/idx >= 2);
2029 if (parser
2030 .resolveOperands(frag.regs, operandTypes[idx], parser.getNameLoc(),
2031 result.operands)
2032 .failed())
2033 return failure();
2034 }
2035
2036 // Resolve sparse metadata and selector
2037 Type i32Type = builder.getI32Type();
2038 if (parser
2039 .resolveOperands(metadataOperands, i32Type, parser.getNameLoc(),
2040 result.operands)
2041 .failed() ||
2042 parser
2043 .resolveOperands(selectorOperands, i32Type, parser.getNameLoc(),
2044 result.operands)
2045 .failed())
2046 return failure();
2047
2048 // Resolve scale operands
2049 SmallVector<Type, 3> scaleTypes = {i32Type, builder.getI16Type(),
2050 builder.getI16Type()};
2051 if (parser
2052 .resolveOperands(scaleAOperands, scaleTypes, parser.getNameLoc(),
2053 result.operands)
2054 .failed() ||
2055 parser
2056 .resolveOperands(scaleBOperands, scaleTypes, parser.getNameLoc(),
2057 result.operands)
2058 .failed())
2059 return failure();
2060
2061 // Add attributes
2062 result.addAttributes(namedAttributes);
2063 inferAndSetMultiplicandTypes(parser.getContext(), result.attributes,
2064 operandTypes);
2065
2066 // orderedMetadata is mandatory
2067 if (!result.attributes.get("orderedMetadata"))
2068 result.addAttribute("orderedMetadata", builder.getUnitAttr());
2069
2070 result.addTypes(resultTypes);
2071 result.addAttribute(MmaSpBlockScaleOp::getOperandSegmentSizeAttr(),
2072 builder.getDenseI32ArrayAttr({
2073 static_cast<int32_t>(frags[0].regs.size()),
2074 static_cast<int32_t>(frags[1].regs.size()),
2075 static_cast<int32_t>(frags[2].regs.size()),
2076 1, // sparseMetadata
2077 1, // sparsitySelector
2078 1, // scaleAData
2079 1, // byteIdA
2080 1, // threadIdA
2081 1, // scaleBData
2082 1, // byteIdB
2083 1 // threadIdB
2084 }));
2085 return success();
2086}
2087
2088void MmaSpBlockScaleOp::build(
2089 OpBuilder &builder, OperationState &result, Type resultType,
2090 ValueRange operandA, ValueRange operandB, ValueRange operandC,
2091 Value sparseMetadata, Value sparsitySelector, Value scaleAData,
2092 Value byteIdA, Value threadIdA, Value scaleBData, Value byteIdB,
2093 Value threadIdB, ArrayRef<int64_t> shape,
2094 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes,
2095 ScaleVecSize scaleVecSize, BlockScaleFormat blockScaleFormat,
2096 MMABlockScaleKind kind) {
2097 assert(shape.size() == 3 && "expected shape to have size 3 (m, n, k)");
2098
2100 builder, result, shape, scaleVecSize, blockScaleFormat, kind);
2101 result.addAttribute("orderedMetadata", builder.getUnitAttr());
2102
2103 result.addOperands(operandA);
2104 result.addOperands(operandB);
2105 result.addOperands(operandC);
2106 result.addOperands({sparseMetadata, sparsitySelector, scaleAData, byteIdA,
2107 threadIdA, scaleBData, byteIdB, threadIdB});
2108
2109 addInferredMultiplicandTypes(builder.getContext(), result, operandA, operandB,
2110 multiplicandPtxTypes);
2111
2112 result.addTypes(resultType);
2113 result.addAttribute(MmaSpBlockScaleOp::getOperandSegmentSizeAttr(),
2114 builder.getDenseI32ArrayAttr({
2115 static_cast<int32_t>(operandA.size()),
2116 static_cast<int32_t>(operandB.size()),
2117 static_cast<int32_t>(operandC.size()),
2118 1, // sparseMetadata
2119 1, // sparsitySelector
2120 1, // scaleAData
2121 1, // byteIdA
2122 1, // threadIdA
2123 1, // scaleBData
2124 1, // byteIdB
2125 1 // threadIdB
2126 }));
2127}
2128
2129NVVM::IDArgPair MmaSpBlockScaleOp::getIntrinsicIDAndArgs(
2130 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
2131 auto curOp = cast<NVVM::MmaSpBlockScaleOp>(op);
2132
2134 // Add A, B, C operands
2135 for (Value operand : curOp.getOperandA())
2136 args.push_back(mt.lookupValue(operand));
2137 for (Value operand : curOp.getOperandB())
2138 args.push_back(mt.lookupValue(operand));
2139 for (Value operand : curOp.getOperandC())
2140 args.push_back(mt.lookupValue(operand));
2141
2142 // Add sparse metadata and selector
2143 args.push_back(mt.lookupValue(curOp.getSparseMetadata()));
2144 args.push_back(mt.lookupValue(curOp.getSparsitySelector()));
2145
2146 // Add scale operands
2147 args.push_back(mt.lookupValue(curOp.getScaleAData()));
2148 args.push_back(mt.lookupValue(curOp.getByteIdA()));
2149 args.push_back(mt.lookupValue(curOp.getThreadIdA()));
2150 args.push_back(mt.lookupValue(curOp.getScaleBData()));
2151 args.push_back(mt.lookupValue(curOp.getByteIdB()));
2152 args.push_back(mt.lookupValue(curOp.getThreadIdB()));
2153
2154 unsigned intId = MmaSpBlockScaleOp::getIntrinsicID(
2155 curOp.getShape().getM(), curOp.getShape().getN(), curOp.getShape().getK(),
2156 *curOp.getMultiplicandAPtxType(), *curOp.getMultiplicandBPtxType(),
2157 inferPtxTypeFromResult(curOp), curOp.getScaleVecSize(),
2158 curOp.getBlockScaleFormat(), curOp.getKind());
2159
2160 return {intId, args};
2161}
2162
2163LogicalResult MmaSpBlockScaleOp::verify() {
2164 // Check that orderedMetadata is present
2165 if (!getOrderedMetadata()) {
2166 return emitOpError("'orderedMetadata' attribute is mandatory");
2167 }
2168
2169 LogicalResult result = success();
2170 int m = getShape().getM();
2171 int n = getShape().getN();
2172 int k = getShape().getK();
2173
2174 if (m == 16 && n == 8 && k == 128) {
2175 if (getMultiplicandAPtxType() != NVVM::MMATypes::e2m1 ||
2176 getMultiplicandBPtxType() != NVVM::MMATypes::e2m1)
2178 "unsupported MMATypes attribute for mma.m16n8k128.(mxf4nvf4|mxf4)");
2179 if (getKind() == NVVM::MMABlockScaleKind::MXF4) {
2180 if (getScaleVecSize() != NVVM::ScaleVecSize::X2)
2182 "unsupported ScaleVecSize attribute for mma.m16n8k128.mxf4");
2183 if (getBlockScaleFormat() != NVVM::BlockScaleFormat::UE8M0)
2185 "unsupported BlockScaleFormat attribute for mma.m16n8k128.mxf4");
2186 } else if (getKind() == NVVM::MMABlockScaleKind::MXF4NVF4) {
2187 if (!((getScaleVecSize() == NVVM::ScaleVecSize::X2 &&
2188 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0) ||
2189 (getScaleVecSize() == NVVM::ScaleVecSize::X4 &&
2190 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE4M3)))
2191 result = emitOpError("unsupported ScaleVecSize and BlockScaleFormat "
2192 "attributes for mma.m16n8k128.mxf4nvf4");
2193 } else {
2194 result = emitOpError("unsupported Kind attribute for mma.m16n8k128");
2195 }
2196 } else if (m == 16 && n == 8 && k == 64) {
2197 if (!(getKind() == NVVM::MMABlockScaleKind::MXF8F6F4 &&
2198 getScaleVecSize() == NVVM::ScaleVecSize::X1 &&
2199 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0))
2200 result =
2201 emitOpError("unsupported Kind, ScaleVecSize and BlockScaleFormat "
2202 "attributes for mma.m16n8k64");
2203 } else {
2204 result = emitOpError("unsupported Geom for sparse mma with block scaling");
2205 }
2206 return result;
2207}
2208
2209LogicalResult ShflOp::verify() {
2210 auto returnStructType = llvm::dyn_cast<LLVM::LLVMStructType>(getType());
2211
2212 auto verifyTypeError = [&](Twine desc, Type expectedType,
2213 Type actualType) -> LogicalResult {
2214 return emitOpError("expected " + desc + " to be of type ")
2215 << expectedType << " but got " << actualType << " instead";
2216 };
2217
2218 if (returnStructType) {
2219 if (!getReturnValueAndIsValid())
2220 return emitOpError("\"return_value_and_is_valid\" attribute must be "
2221 "specified when the return type is a struct type");
2222
2223 if (returnStructType.getBody().size() != 2)
2224 return emitOpError("expected return type to be a two-element struct");
2225
2226 llvm::ArrayRef<Type> returnStruct = returnStructType.getBody();
2227 auto resultType = returnStruct[0];
2228 if (resultType != getVal().getType())
2229 return verifyTypeError("first element in the returned struct",
2230 getVal().getType(), resultType);
2231
2232 auto predicateType = returnStruct[1];
2233 if (!predicateType.isInteger(1))
2234 return verifyTypeError("second element in the returned struct",
2235 mlir::IntegerType::get(getContext(), 1),
2236 predicateType);
2237 } else {
2238 if (getReturnValueAndIsValid())
2239 return emitOpError("expected return type to be a two-element struct");
2240
2241 if (getType() != getVal().getType())
2242 return verifyTypeError("return type", getVal().getType(), getType());
2243 }
2244 return success();
2245}
2246
2247std::pair<mlir::Type, unsigned> NVVM::inferMMAType(NVVM::MMATypes type,
2248 NVVM::MMAFrag frag, int nRow,
2249 int nCol,
2250 MLIRContext *context) {
2251 unsigned numberElements = 0;
2252 Type elementType;
2253 OpBuilder builder(context);
2254 Type f16x2 = VectorType::get(2, builder.getF16Type());
2255 if (type == NVVM::MMATypes::f16) {
2256 elementType = f16x2;
2257 if (frag == NVVM::MMAFrag::a || frag == NVVM::MMAFrag::b)
2258 numberElements = 8;
2259 else
2260 numberElements = 4;
2261 } else if (type == NVVM::MMATypes::f32) {
2262 elementType = builder.getF32Type();
2263 numberElements = 8;
2264 } else if (type == NVVM::MMATypes::f64) {
2265 elementType = builder.getF64Type();
2266 if (frag == NVVM::MMAFrag::a || frag == NVVM::MMAFrag::b)
2267 numberElements = 1;
2268 else
2269 numberElements = 2;
2270 } else if (type == NVVM::MMATypes::tf32) {
2271 elementType = builder.getI32Type();
2272 numberElements = 4;
2273 } else if (type == NVVM::MMATypes::s8 || type == NVVM::MMATypes::u8) {
2274 elementType = builder.getI32Type();
2275 int parallelSize = 0;
2276 if (frag == NVVM::MMAFrag::a)
2277 parallelSize = nRow;
2278 if (frag == NVVM::MMAFrag::b)
2279 parallelSize = nCol;
2280
2281 // m == 16 && n == 16 && k == 16
2282 if (parallelSize == 16)
2283 numberElements = 2;
2284 // m == 8 && n == 32 && k == 16 or m == 32 && n == 8 && k == 16
2285 else if (parallelSize == 8)
2286 numberElements = 1;
2287 else if (parallelSize == 32)
2288 numberElements = 4;
2289 } else if (type == NVVM::MMATypes::s32) {
2290 elementType = builder.getI32Type();
2291 numberElements = 8;
2292 }
2293 assert(numberElements != 0 && elementType != nullptr);
2294 return std::make_pair(elementType, numberElements);
2295}
2296
2297static std::pair<mlir::Type, unsigned>
2298inferMMATypeFromMNK(NVVM::MMATypes type, NVVM::MMAFrag frag, int m, int n,
2299 int k, MLIRContext *context) {
2300 int nRow, nCol;
2301 if (frag == NVVM::MMAFrag::a) {
2302 nRow = m;
2303 nCol = k;
2304 } else if (frag == NVVM::MMAFrag::b) {
2305 nRow = k;
2306 nCol = n;
2307 } else {
2308 nRow = m;
2309 nCol = n;
2310 }
2311 assert(nRow && nCol);
2312 return inferMMAType(type, frag, nRow, nCol, context);
2313}
2314
2315LogicalResult NVVM::WMMALoadOp::verify() {
2316 unsigned addressSpace =
2317 llvm::cast<LLVM::LLVMPointerType>(getPtr().getType()).getAddressSpace();
2318 if (addressSpace != 0 && addressSpace != NVVMMemorySpace::Global &&
2319 addressSpace != NVVMMemorySpace::Shared)
2320 return emitOpError("expected source pointer in memory "
2321 "space 0, 1, 3");
2322
2323 if (NVVM::WMMALoadOp::getIntrinsicID(getM(), getN(), getK(), getLayout(),
2324 getEltype(), getFrag()) == 0)
2325 return emitOpError() << "invalid attribute combination";
2326 std::pair<Type, unsigned> typeInfo = inferMMATypeFromMNK(
2327 getEltype(), getFrag(), getM(), getN(), getK(), getContext());
2328 // Special case for f64 fragments
2329 Type f64Ty = Float64Type::get(getContext());
2330 if (typeInfo.first == f64Ty && typeInfo.second == 1) {
2331 if (getType() != f64Ty)
2332 return emitOpError("expected destination type to be f64");
2333 return success();
2334 }
2335 // Everything else is a struct
2336 Type dstType = LLVM::LLVMStructType::getLiteral(
2337 getContext(), SmallVector<Type, 8>(typeInfo.second, typeInfo.first));
2338 if (getType() != dstType)
2339 return emitOpError("expected destination type is a structure of ")
2340 << typeInfo.second << " elements of type " << typeInfo.first;
2341 return success();
2342}
2343
2344LogicalResult NVVM::WMMAStoreOp::verify() {
2345 unsigned addressSpace =
2346 llvm::cast<LLVM::LLVMPointerType>(getPtr().getType()).getAddressSpace();
2347 if (addressSpace != 0 && addressSpace != NVVMMemorySpace::Global &&
2348 addressSpace != NVVMMemorySpace::Shared)
2349 return emitOpError("expected operands to be a source pointer in memory "
2350 "space 0, 1, 3");
2351
2352 if (NVVM::WMMAStoreOp::getIntrinsicID(getM(), getN(), getK(), getLayout(),
2353 getEltype()) == 0)
2354 return emitOpError() << "invalid attribute combination";
2355 std::pair<Type, unsigned> typeInfo = inferMMATypeFromMNK(
2356 getEltype(), NVVM::MMAFrag::c, getM(), getN(), getK(), getContext());
2357 if (getArgs().size() != typeInfo.second)
2358 return emitOpError() << "expected " << typeInfo.second << " data operands";
2359 if (llvm::any_of(getArgs(), [&typeInfo](Value operands) {
2360 return operands.getType() != typeInfo.first;
2361 }))
2362 return emitOpError() << "expected data operands of type " << typeInfo.first;
2363 return success();
2364}
2365
2366LogicalResult NVVM::WMMAMmaOp::verify() {
2367 if (NVVM::WMMAMmaOp::getIntrinsicID(getM(), getN(), getK(), getLayoutA(),
2368 getLayoutB(), getEltypeA(),
2369 getEltypeB()) == 0)
2370 return emitOpError() << "invalid attribute combination";
2371 std::pair<Type, unsigned> typeInfoA = inferMMATypeFromMNK(
2372 getEltypeA(), NVVM::MMAFrag::a, getM(), getN(), getK(), getContext());
2373 std::pair<Type, unsigned> typeInfoB = inferMMATypeFromMNK(
2374 getEltypeA(), NVVM::MMAFrag::b, getM(), getN(), getK(), getContext());
2375 std::pair<Type, unsigned> typeInfoC = inferMMATypeFromMNK(
2376 getEltypeB(), NVVM::MMAFrag::c, getM(), getN(), getK(), getContext());
2377 SmallVector<Type, 32> arguments;
2378 arguments.append(typeInfoA.second, typeInfoA.first);
2379 arguments.append(typeInfoB.second, typeInfoB.first);
2380 arguments.append(typeInfoC.second, typeInfoC.first);
2381 unsigned numArgs = arguments.size();
2382 if (getArgs().size() != numArgs)
2383 return emitOpError() << "expected " << numArgs << " arguments";
2384 for (unsigned i = 0; i < numArgs; i++) {
2385 if (getArgs()[i].getType() != arguments[i])
2386 return emitOpError() << "expected argument " << i << " to be of type "
2387 << arguments[i];
2388 }
2389 Type dstType = LLVM::LLVMStructType::getLiteral(
2390 getContext(), SmallVector<Type, 8>(typeInfoC.second, typeInfoC.first));
2391 if (getType() != dstType)
2392 return emitOpError("expected destination type is a structure of ")
2393 << typeInfoC.second << " elements of type " << typeInfoC.first;
2394 return success();
2395}
2396
2397LogicalResult NVVM::LdMatrixOp::verify() {
2398 uint32_t num = getNum(), m = getShape().getM(), n = getShape().getN();
2399 if (m == 8 && n == 8) {
2400 if (num != 1 && num != 2 && num != 4) {
2401 return emitOpError("expected num attribute to be 1, 2 or 4 for 8x8 "
2402 "matrix");
2403 }
2404 if (getEltType() != LdStMatrixEltType::B16) {
2405 return emitOpError("expected element type to be b16 for 8x8 matrix");
2406 }
2407 } else if (m == 8 && n == 16) {
2408 if (num != 1 && num != 2 && num != 4) {
2409 return emitOpError("expected num attribute to be 1, 2 or 4 for 8x16 "
2410 "matrix");
2411 }
2412 if (getLayout() != MMALayout::row) {
2413 return emitOpError("expected layout to be row for 8x16 matrix");
2414 }
2415 if (getEltType() != LdStMatrixEltType::B8X16_B4X16_P64 &&
2416 getEltType() != LdStMatrixEltType::B8X16_B6X16_P32) {
2417 return emitOpError("expected element type to be b8x16.b4x16_p64 or "
2418 "b8x16.b6x16_p32 for 8x16 matrix");
2419 }
2420 } else if (m == 16 && n == 16) {
2421 if (num != 1 && num != 2) {
2422 return emitOpError("expected num attribute to be 1 or 2 for 16x16 "
2423 "matrix");
2424 }
2425 if (getLayout() != MMALayout::col) {
2426 return emitOpError("expected layout to be col for 16x16 matrix");
2427 }
2428 if (getEltType() != LdStMatrixEltType::B8 &&
2429 getEltType() != LdStMatrixEltType::B8X16_B4X16_P64 &&
2430 getEltType() != LdStMatrixEltType::B8X16_B6X16_P32) {
2431 return emitOpError("expected element type to be b8, b8x16.b4x16_p64 or "
2432 "b8x16.b6x16_p32 for 16x16 matrix");
2433 }
2434 } else {
2435 return emitOpError("expected shape to be 8x8, 8x16 or 16x16");
2436 }
2437
2438 Type i32 = IntegerType::get(getContext(), 32);
2439 uint32_t numElements = (m == 16 && n == 16 ? num * 2 : num);
2440 if (numElements == 1 && getType() != i32)
2441 return emitOpError("expected destination type is i32");
2442 if (numElements == 2 || numElements == 4) {
2443 Type dstType = LLVM::LLVMStructType::getLiteral(
2444 getContext(), SmallVector<Type>(numElements, i32));
2445 if (getType() != dstType)
2446 return emitOpError("expected destination type is a structure of ")
2447 << numElements << " elements of type i32";
2448 }
2449
2450 return success();
2451}
2452
2453LogicalResult NVVM::StMatrixOp::verify() {
2454 int numMatrix = getSources().size();
2455 if (numMatrix != 1 && numMatrix != 2 && numMatrix != 4)
2456 return emitOpError("expected num attribute to be 1, 2 or 4");
2457
2458 int m = getShape().getM(), n = getShape().getN();
2459 if (m == 8 && n == 8) {
2460 if (getEltType() != NVVM::LdStMatrixEltType::B16) {
2461 return emitOpError("expected element type to be B16 for 8x8 matrix");
2462 }
2463 } else if (m == 16 && n == 8) {
2464 if (getEltType() != NVVM::LdStMatrixEltType::B8) {
2465 return emitOpError("expected element type to be B8 for 16x8 matrix");
2466 }
2467 if (getLayout() != NVVM::MMALayout::col) {
2468 return emitOpError("expected layout to be col for 16x8 matrix");
2469 }
2470 } else {
2471 return emitOpError("expected shape to be 8x8 or 16x8");
2472 }
2473
2474 return success();
2475}
2476
2477static FailureOr<int> getAllowedSizeK(NVVM::WGMMATypes typeA) {
2478 if (typeA == NVVM::WGMMATypes::tf32)
2479 return 8;
2480 if (typeA == NVVM::WGMMATypes::f16 || typeA == NVVM::WGMMATypes::bf16)
2481 return 16;
2482 if (typeA == NVVM::WGMMATypes::s8 || typeA == NVVM::WGMMATypes::u8)
2483 return 32;
2484 if (typeA == NVVM::WGMMATypes::e4m3 || typeA == NVVM::WGMMATypes::e5m2)
2485 return 32;
2486 if (typeA == NVVM::WGMMATypes::b1)
2487 return 256;
2488 return failure();
2489}
2490
2491static LogicalResult isAllowedWGMMADataType(NVVM::WGMMATypes typeD,
2492 NVVM::WGMMATypes typeA,
2493 NVVM::WGMMATypes typeB) {
2494 switch (typeA) {
2495 case NVVM::WGMMATypes::f16:
2496 if ((typeD == NVVM::WGMMATypes::f32 || typeD == NVVM::WGMMATypes::f16) &&
2497 typeB == NVVM::WGMMATypes::f16)
2498 return success();
2499 break;
2500 case NVVM::WGMMATypes::tf32:
2501 if (typeD == NVVM::WGMMATypes::f32 && typeB == NVVM::WGMMATypes::tf32)
2502 return success();
2503 break;
2504 case NVVM::WGMMATypes::u8:
2505 case NVVM::WGMMATypes::s8:
2506 if (typeD == NVVM::WGMMATypes::s32 &&
2507 (typeB == NVVM::WGMMATypes::u8 || typeB == NVVM::WGMMATypes::s8))
2508 return success();
2509 break;
2510 case NVVM::WGMMATypes::b1:
2511 if (typeD == NVVM::WGMMATypes::s32 && typeB == NVVM::WGMMATypes::b1)
2512 return success();
2513 break;
2514 case NVVM::WGMMATypes::bf16:
2515 if ((typeD == NVVM::WGMMATypes::f32 || typeD == NVVM::WGMMATypes::f16) &&
2516 typeB == NVVM::WGMMATypes::bf16)
2517 return success();
2518 break;
2519 case NVVM::WGMMATypes::e4m3:
2520 case NVVM::WGMMATypes::e5m2:
2521 if ((typeD == NVVM::WGMMATypes::f32 || typeD == NVVM::WGMMATypes::f16) &&
2522 (typeB == NVVM::WGMMATypes::e5m2 || typeB == NVVM::WGMMATypes::e4m3))
2523 return success();
2524 break;
2525 case WGMMATypes::f32:
2526 case WGMMATypes::s32:
2527 llvm_unreachable("unsupported input types");
2528 break;
2529 }
2530 return failure();
2531}
2532
2533static LogicalResult isAllowedSizeN(int sizeN, NVVM::WGMMATypes typeA) {
2534 SmallVector<int> allowedN = {8, 16, 24, 32, 40, 48, 56, 64,
2535 72, 80, 88, 96, 104, 112, 120, 128,
2536 136, 144, 152, 160, 168, 176, 184, 192,
2537 200, 208, 216, 224, 232, 240, 248, 256};
2538 SmallVector<int> allowedNshort = {8, 16, 24, 32, 48, 64,
2539 80, 96, 112, 128, 144, 160,
2540 176, 192, 208, 224, 240, 256};
2541 switch (typeA) {
2542 case WGMMATypes::f16:
2543 case WGMMATypes::tf32:
2544 case WGMMATypes::bf16:
2545 case WGMMATypes::e4m3:
2546 case WGMMATypes::e5m2:
2547 if (llvm::is_contained(allowedN, sizeN))
2548 return success();
2549 break;
2550 case WGMMATypes::u8:
2551 case WGMMATypes::s8:
2552 case WGMMATypes::b1:
2553 if (llvm::is_contained(allowedNshort, sizeN))
2554 return success();
2555 break;
2556 case WGMMATypes::f32:
2557 case WGMMATypes::s32:
2558 llvm_unreachable("unsupported input types");
2559 break;
2560 }
2561 return failure();
2562}
2563
2564LogicalResult NVVM::WgmmaMmaAsyncOp::verify() {
2565 Value outValue = getResults();
2566 auto stype = dyn_cast<LLVM::LLVMStructType>(outValue.getType());
2567 if (!stype)
2568 return emitOpError() << "expected results to be struct";
2569 int outputSize = stype.getBody().size();
2570 WGMMATypes typeD = getTypeD();
2571 WGMMATypes typeA = getTypeA();
2572 WGMMATypes typeB = getTypeB();
2573
2574 for (Type t : stype.getBody()) {
2575 if (t != stype.getBody().front())
2576 return emitOpError()
2577 << "all elements in struct must be same type but there is " << t;
2578 }
2579
2580 if (typeD != WGMMATypes::f32 && typeD != WGMMATypes::f16 &&
2581 typeD != WGMMATypes::s32) {
2582 return emitOpError() << "does not support the given output type "
2583 << NVVM::stringifyWGMMATypes(typeD);
2584 }
2585 if (typeD == WGMMATypes::s32 &&
2586 (getScaleA() == WGMMAScaleIn::neg || getScaleB() == WGMMAScaleIn::neg)) {
2587 return emitOpError() << "has s32 output, scaleA and scaleB cannot be neg";
2588 }
2589
2590 if (failed(isAllowedWGMMADataType(typeD, typeA, typeB))) {
2591 return emitOpError() << NVVM::stringifyWGMMATypes(typeD)
2592 << " += " << NVVM::stringifyWGMMATypes(typeA) << " * "
2593 << NVVM::stringifyWGMMATypes(typeB)
2594 << ", it is not supported.";
2595 }
2596
2597 // Check M
2598 if (getShape().getM() != 64)
2599 return emitOpError() << "shape 'm' must be 64";
2600
2601 // Check K
2602 FailureOr<int> allowedK = getAllowedSizeK(typeA);
2603 if (failed(allowedK) || allowedK.value() != getShape().getK())
2604 return emitOpError() << "shape 'k' must be " << allowedK.value()
2605 << " for input type "
2606 << NVVM::stringifyWGMMATypes(typeA);
2607
2608 // Check N
2609 if (failed(isAllowedSizeN(getShape().getN(), typeA))) {
2610 return emitOpError() << "has input type "
2611 << NVVM::stringifyWGMMATypes(typeA) << " n is set to "
2612 << getShape().getN() << ", it is not supported.";
2613 }
2614
2615 // Check transpose (only available for f16/bf16)
2616 // Matrices A should be stored in row-major and B in column-major.
2617 // Only f16/bf16 matrices can be stored in either column-major or row-major
2618 // by setting the transpose value(imm-trans-a,imm-trans-b) in PTX code.
2619 if ((typeA != WGMMATypes::f16 && typeA != WGMMATypes::bf16) &&
2620 (getLayoutA() == mlir::NVVM::MMALayout::col ||
2621 getLayoutB() == mlir::NVVM::MMALayout::row)) {
2622 return emitOpError()
2623 << "given layouts layout_a = " << stringifyMMALayout(getLayoutA())
2624 << " and layout_b = " << stringifyMMALayout(getLayoutB())
2625 << " for input types " << stringifyWGMMATypes(typeA) << " and "
2626 << stringifyWGMMATypes(typeB)
2627 << " requires transpose. However, this is only supported for: "
2628 << stringifyMMATypes(MMATypes::f16) << " and "
2629 << stringifyMMATypes(MMATypes::bf16);
2630 }
2631
2632 // Check result registers
2633 int expectedOutput = 0;
2634 if (typeD == WGMMATypes::f32 || typeD == WGMMATypes::s32)
2635 expectedOutput = getShape().getN() / 2;
2636 if (typeD == WGMMATypes::f16)
2637 expectedOutput = getShape().getN() / 4;
2638 if (outputSize != expectedOutput) {
2639 return emitOpError() << "results " << expectedOutput
2640 << ", however output struct has " << outputSize
2641 << " elements";
2642 }
2643 // Check satfinite (only available for s32 accumulator)
2644 if (typeD != WGMMATypes::s32 &&
2645 getSatfinite().value_or(NVVM::MMAIntOverflow::wrapped) ==
2646 NVVM::MMAIntOverflow::satfinite) {
2647 return emitOpError()
2648 << " `satfinite` can be only used with s32 accumulator, however "
2649 "the current accumulator is "
2650 << NVVM::stringifyWGMMATypes(typeD);
2651 }
2652
2653 return success();
2654}
2655
2656std::string NVVM::WgmmaMmaAsyncOp::getPtx() {
2657
2658 int m = getShape().getM(), n = getShape().getN(), k = getShape().getK();
2659 bool isF16 = getTypeA() == WGMMATypes::f16 || getTypeA() == WGMMATypes::bf16;
2660
2661 StringRef outputTypeName = stringifyWGMMATypes(getTypeD());
2662
2663 int expectedOutputRegisters = 0;
2664 if (getTypeD() == WGMMATypes::f16)
2665 expectedOutputRegisters = getShape().getN() / 4;
2666 else
2667 expectedOutputRegisters = getShape().getN() / 2;
2668
2669 std::string ptx;
2670 llvm::raw_string_ostream ss(ptx);
2671
2672 ss << "{\n"
2673 ".reg .pred p;\n"
2674 "setp.ne.b32 p, $"
2675 << ((expectedOutputRegisters * 2) + 2)
2676 << ", 0;\n"
2677 "wgmma.mma_async.sync.aligned.m"
2678 << m << "n" << n << "k" << k << "." << outputTypeName << "."
2679 << stringifyWGMMATypes(getTypeA()) << "."
2680 << stringifyWGMMATypes(getTypeB());
2681 if (getSatfinite().value_or(NVVM::MMAIntOverflow::wrapped) ==
2682 NVVM::MMAIntOverflow::satfinite)
2683 ss << ".satfinite";
2684 ss << " {";
2685 int regCnt = 0;
2686 for (; regCnt < expectedOutputRegisters; ++regCnt) {
2687 ss << "$" << regCnt;
2688 if (regCnt != expectedOutputRegisters - 1)
2689 ss << ", ";
2690 }
2691
2692 ss << "},";
2693 // Need to map read/write registers correctly.
2694 regCnt = (regCnt * 2);
2695 ss << " $" << (regCnt) << ","
2696 << " $" << (regCnt + 1) << ","
2697 << " p";
2698 if (getTypeD() != WGMMATypes::s32) {
2699 ss << ", $" << (regCnt + 3) << ", $" << (regCnt + 4);
2700 }
2701 // Don't add transpose parameters unless needed.
2702 if (isF16) {
2703 ss << ", $" << (regCnt + 5) << ", $" << (regCnt + 6);
2704 }
2705 ss << ";\n"
2706 << "}\n";
2707 return ptx;
2708}
2709
2710bool NVVM::WgmmaMmaAsyncOp::getAsmValues(
2711 RewriterBase &rewriter,
2712 llvm::SmallVectorImpl<std::pair<mlir::Value, mlir::NVVM::PTXRegisterMod>>
2713 &asmValues) {
2714 bool isF16 = getTypeA() == WGMMATypes::f16 || getTypeA() == WGMMATypes::bf16;
2715 if (getResults())
2716 asmValues.push_back({getResults(), mlir::NVVM::PTXRegisterMod::Write});
2717 if (getInouts())
2718 asmValues.push_back({getInouts(), mlir::NVVM::PTXRegisterMod::ReadWrite});
2719 asmValues.push_back({getDescriptorA(), mlir::NVVM::PTXRegisterMod::Read});
2720 asmValues.push_back({getDescriptorB(), mlir::NVVM::PTXRegisterMod::Read});
2721 asmValues.push_back({makeConstantI32(rewriter, static_cast<int>(getScaleD())),
2723 if (getTypeD() != WGMMATypes::s32) {
2724 asmValues.push_back(
2725 {makeConstantI32(rewriter,
2726 getScaleA() == NVVM::WGMMAScaleIn::neg ? -1 : 1),
2728 asmValues.push_back(
2729 {makeConstantI32(rewriter,
2730 getScaleB() == NVVM::WGMMAScaleIn::neg ? -1 : 1),
2732 }
2733 if (isF16) {
2734 asmValues.push_back(
2735 {makeConstantI32(rewriter, static_cast<int>(getLayoutA())),
2737 asmValues.push_back(
2738 {makeConstantI32(rewriter, 1 - static_cast<int>(getLayoutB())),
2740 }
2741 return true; // Has manual mapping
2742}
2743
2744LogicalResult NVVM::FenceSyncRestrictOp::verify() {
2745 if (getOrder() != NVVM::MemOrderKind::ACQUIRE &&
2746 getOrder() != NVVM::MemOrderKind::RELEASE)
2747 return emitOpError("only acquire and release semantics are supported");
2748 return success();
2749}
2750
2751LogicalResult NVVM::FenceProxyOp::verify() {
2752 if (getKind() == NVVM::ProxyKind::TENSORMAP)
2753 return emitOpError() << "tensormap proxy is not a supported proxy kind";
2754 if (getKind() == NVVM::ProxyKind::GENERIC)
2755 return emitOpError() << "generic proxy not a supported proxy kind";
2756 if (getKind() == NVVM::ProxyKind::async_shared && !getSpace().has_value()) {
2757 return emitOpError() << "async_shared fence requires space attribute";
2758 }
2759 if (getKind() != NVVM::ProxyKind::async_shared && getSpace().has_value()) {
2760 return emitOpError() << "only async_shared fence can have space attribute";
2761 }
2762 return success();
2763}
2764
2765LogicalResult NVVM::FenceProxyAcquireOp::verify() {
2766 if (getFromProxy() != NVVM::ProxyKind::GENERIC)
2767 return emitOpError("uni-directional proxies only support generic for "
2768 "from_proxy attribute");
2769
2770 if (getToProxy() != NVVM::ProxyKind::TENSORMAP)
2771 return emitOpError("uni-directional proxies only support tensormap "
2772 "for to_proxy attribute");
2773 return success();
2774}
2775
2776LogicalResult NVVM::FenceProxyReleaseOp::verify() {
2777 if (getFromProxy() != NVVM::ProxyKind::GENERIC)
2778 return emitOpError("uni-directional proxies only support generic for "
2779 "from_proxy attribute");
2780
2781 if (getToProxy() != NVVM::ProxyKind::TENSORMAP)
2782 return emitOpError("uni-directional proxies only support tensormap "
2783 "for to_proxy attribute");
2784 return success();
2785}
2786
2787LogicalResult NVVM::FenceProxySyncRestrictOp::verify() {
2788 if (getOrder() != NVVM::MemOrderKind::ACQUIRE &&
2789 getOrder() != NVVM::MemOrderKind::RELEASE)
2790 return emitOpError("only acquire and release semantics are supported");
2791
2792 if (getFromProxy() != NVVM::ProxyKind::GENERIC)
2793 return emitOpError("only generic is support for from_proxy attribute");
2794
2795 if (getToProxy() != NVVM::ProxyKind::async)
2796 return emitOpError("only async is supported for to_proxy attribute");
2797 return success();
2798}
2799
2800LogicalResult NVVM::SetMaxRegisterOp::verify() {
2801 if (getRegCount() % 8)
2802 return emitOpError("new register size must be multiple of 8");
2803 if (getRegCount() < 24 || getRegCount() > 256)
2804 return emitOpError("new register size must be in between 24 to 256");
2805 return success();
2806}
2807
2808LogicalResult NVVM::BarrierOp::verify() {
2809 if (getNumberOfThreads() && !getBarrierId())
2810 return emitOpError(
2811 "barrier id is missing, it should be set between 0 to 15");
2812
2813 if (getBarrierId() && (getReductionOp() || getReductionPredicate()))
2814 return emitOpError("reduction are only available when id is 0");
2815
2816 if ((getReductionOp() && !getReductionPredicate()) ||
2817 (!getReductionOp() && getReductionPredicate()))
2818 return emitOpError("reduction predicate and reduction operation must be "
2819 "specified together");
2820
2821 return success();
2822}
2823
2824LogicalResult NVVM::Tcgen05CpOp::verify() {
2825 auto mc = getMulticast();
2826
2827 using SH = Tcgen05CpShape;
2828 using MC = Tcgen05CpMulticast;
2829 switch (getShape()) {
2830 case SH::SHAPE_128x256b:
2831 case SH::SHAPE_128x128b:
2832 case SH::SHAPE_4x256b:
2833 if (mc != MC::NONE)
2834 return emitError("Invalid multicast type for tcgen05.cp Op");
2835 break;
2836 case SH::SHAPE_64x128b:
2837 if (mc != MC::WARPX2_01_23 && mc != MC::WARPX2_02_13)
2838 return emitError("Shape 64x128b requires multicast warpx2_01_23 or "
2839 "warpx2_02_13 for tcgen05.cp Op");
2840 break;
2841 case SH::SHAPE_32x128b:
2842 if (mc != MC::WARPX4)
2843 return emitError(
2844 "Shape 32x128b requires multicast warpx4 for tcgen05.cp Op");
2845 break;
2846 }
2847 return success();
2848}
2849
2850LogicalResult NVVM::MatchSyncOp::verify() {
2851 if (getKind() == NVVM::MatchSyncKind::all) {
2852 auto type = llvm::dyn_cast<LLVM::LLVMStructType>(getType());
2853 if (!type || type.getBody().size() != 2 ||
2854 !type.getBody()[0].isInteger(32) || !type.getBody()[1].isInteger(1)) {
2855 return emitOpError("match.sync 'all' returns a two element struct with "
2856 "first element as i32 and second element as i1");
2857 }
2858 } else {
2859 if (!getType().isInteger(32)) {
2860 return emitOpError("match.sync 'any' returns an i32");
2861 }
2862 }
2863 return success();
2864}
2865
2866LogicalResult NVVM::VoteSyncOp::verify() {
2867 if (getKind() == NVVM::VoteSyncKind::ballot) {
2868 if (!getType().isInteger(32)) {
2869 return emitOpError("vote.sync 'ballot' returns an i32");
2870 }
2871 } else {
2872 if (!getType().isInteger(1)) {
2873 return emitOpError("vote.sync 'any', 'all' and 'uni' returns an i1");
2874 }
2875 }
2876 return success();
2877}
2878
2879LogicalResult NVVM::PrefetchOp::verify() {
2880 using MemSpace = NVVM::NVVMMemorySpace;
2881 using CacheLevel = NVVM::PrefetchCacheLevel;
2882
2883 unsigned addressSpace =
2884 llvm::cast<LLVM::LLVMPointerType>(getAddr().getType()).getAddressSpace();
2885 std::optional<NVVM::CacheEvictionPriority> evictPriority = getEvictPriority();
2886 std::optional<NVVM::PrefetchCacheLevel> cacheLevel = getCacheLevel();
2887
2888 if (getTensormap() && cacheLevel)
2889 return emitOpError("cannot specify both tensormap and cache level");
2890
2891 if (getTensormap()) {
2892 if (addressSpace != MemSpace::Generic &&
2893 addressSpace != MemSpace::Constant) {
2894 return emitOpError(
2895 "prefetch tensormap requires a generic or constant pointer");
2896 }
2897
2898 if (evictPriority) {
2899 return emitOpError(
2900 "prefetch tensormap does not support eviction priority");
2901 }
2902
2903 if (getInParamSpace() && addressSpace != MemSpace::Generic) {
2904 return emitOpError(
2905 "in_param_space can only be specified for a generic pointer");
2906 }
2907
2908 } else if (cacheLevel) {
2909 if (addressSpace != MemSpace::Generic && addressSpace != MemSpace::Global &&
2910 addressSpace != MemSpace::Local) {
2911 return emitOpError("prefetch to cache level requires a generic, global, "
2912 "or local pointer");
2913 }
2914
2915 if (getUniform()) {
2916 if (*cacheLevel != CacheLevel::L1) {
2917 return emitOpError(
2918 "unsupported cache level, the only supported uniform "
2919 "cache level is L1");
2920 }
2921
2922 if (addressSpace != MemSpace::Generic) {
2923 return emitOpError(
2924 "prefetch to uniform cache requires a generic pointer");
2925 }
2926 }
2927
2928 if (evictPriority) {
2929 if (*cacheLevel != CacheLevel::L2)
2930 return emitOpError(
2931 "cache eviction priority supported only for cache level L2");
2932
2933 if (addressSpace != MemSpace::Global)
2934 return emitOpError("cache eviction priority requires a global pointer");
2935
2936 if (*evictPriority != NVVM::CacheEvictionPriority::EvictNormal &&
2937 *evictPriority != NVVM::CacheEvictionPriority::EvictLast)
2938 return emitOpError(
2939 "unsupported cache eviction priority, only evict_last and "
2940 "evict_normal are supported");
2941 }
2942
2943 if (getPredicate())
2944 return emitOpError("predicate supported only on prefetch tensormap");
2945
2946 } else {
2947 return emitOpError(
2948 "requires specification of either cache level or tensormap");
2949 }
2950
2951 return success();
2952}
2953
2954LogicalResult NVVM::ClusterLaunchControlQueryCancelOp::verify() {
2955 switch (getQueryType()) {
2956 case NVVM::ClusterLaunchControlQueryType::IS_CANCELED:
2957 if (!getType().isInteger(1))
2958 return emitOpError("is_canceled query type returns an i1");
2959 break;
2960 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_X:
2961 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_Y:
2962 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_Z:
2963 if (!getType().isInteger(32)) {
2964 return emitOpError("get_first_cta_id_x, get_first_cta_id_y, "
2965 "get_first_cta_id_z query types return an i32");
2966 }
2967 break;
2968 }
2969 return success();
2970}
2971
2972LogicalResult NVVM::ReduxOp::verify() {
2973 mlir::Type reduxType = getType();
2974
2975 if (!reduxType.isF32()) {
2976 if (getAbs())
2977 return emitOpError("abs attribute is supported only for f32 type");
2978 if (getNan())
2979 return emitOpError("nan attribute is supported only for f32 type");
2980 }
2981
2982 NVVM::ReduxKind kind = getKind();
2983 switch (kind) {
2984 case NVVM::ReduxKind::ADD:
2985 case NVVM::ReduxKind::AND:
2986 case NVVM::ReduxKind::OR:
2987 case NVVM::ReduxKind::XOR:
2988 case NVVM::ReduxKind::MAX:
2989 case NVVM::ReduxKind::MIN:
2990 case NVVM::ReduxKind::UMAX:
2991 case NVVM::ReduxKind::UMIN:
2992 if (!reduxType.isInteger(32))
2993 return emitOpError("'")
2994 << stringifyEnum(kind) << "' redux kind unsupported with "
2995 << reduxType << " type. Only supported type is 'i32'.";
2996 break;
2997 case NVVM::ReduxKind::FMIN:
2998 case NVVM::ReduxKind::FMAX:
2999 if (!reduxType.isF32())
3000 return emitOpError("'")
3001 << stringifyEnum(kind) << "' redux kind unsupported with "
3002 << reduxType << " type. Only supported type is 'f32'.";
3003 break;
3004 }
3005
3006 return success();
3007}
3008
3009/// Packs the given `field` into the `result`.
3010/// The `result` is 64-bits and each `field` can be 32-bits or narrower.
3011static llvm::Value *
3012packValInto64Bits(llvm::IRBuilderBase &builder,
3013 llvm::Value *result, // the `result` (unset bits are zero)
3014 llvm::Value *field, // `field` to pack into `result`
3015 unsigned sizeInBits, // Size of `field` in bits
3016 unsigned start) { // Starting bit within `result`
3017 field = builder.CreateZExtOrBitCast(field, builder.getInt32Ty());
3018
3019 unsigned mask = (sizeInBits < 32 ? ((1u << sizeInBits) - 1) : 0xffffffffu);
3020 if (mask != 0xffffffffu)
3021 field = builder.CreateAnd(field, builder.getInt32(mask));
3022
3023 field = builder.CreateZExtOrBitCast(field, builder.getInt64Ty());
3024 field = builder.CreateShl(field, start);
3025
3026 return builder.CreateOr(result, field);
3027}
3028
3029void Tcgen05MmaSmemDescOp::createSmemDescriptor(Operation &op,
3031 llvm::IRBuilderBase &builder) {
3032 auto thisOp = cast<NVVM::Tcgen05MmaSmemDescOp>(op);
3033 llvm::Value *smemDesc = builder.getInt64(0);
3034
3035 smemDesc = packValInto64Bits(builder, smemDesc,
3036 mt.lookupValue(thisOp.getStartAddr()), 14, 0);
3037 smemDesc = packValInto64Bits(
3038 builder, smemDesc, mt.lookupValue(thisOp.getLeadingDimOffset()), 14, 16);
3039 smemDesc = packValInto64Bits(
3040 builder, smemDesc, mt.lookupValue(thisOp.getStrideDimOffset()), 14, 32);
3041
3042 smemDesc = packValInto64Bits(builder, smemDesc, builder.getInt32(1), 3, 46);
3043 smemDesc = packValInto64Bits(builder, smemDesc,
3044 mt.lookupValue(thisOp.getBaseOffset()), 3, 49);
3045 smemDesc = packValInto64Bits(
3046 builder, smemDesc, mt.lookupValue(thisOp.getLeadingDimMode()), 1, 52);
3047 smemDesc = packValInto64Bits(builder, smemDesc,
3048 mt.lookupValue(thisOp.getSwizzleMode()), 3, 61);
3049
3050 mt.mapValue(thisOp.getRes()) = smemDesc;
3051}
3052
3053//===----------------------------------------------------------------------===//
3054// getPtx methods
3055//===----------------------------------------------------------------------===//
3056
3057std::string NVVM::MBarrierInitOp::getPtx() {
3058 bool isShared = isPtrInSharedCTASpace(getAddr());
3059 return isShared ? std::string("mbarrier.init.shared.b64 [%0], %1;")
3060 : std::string("mbarrier.init.b64 [%0], %1;");
3061}
3062
3063std::string NVVM::MBarrierArriveExpectTxOp::getPtx() {
3064 bool isShared = isPtrInSharedCTASpace(getAddr());
3065 return isShared
3066 ? std::string("mbarrier.arrive.expect_tx.shared.b64 _, [%0], %1;")
3067 : std::string("mbarrier.arrive.expect_tx.b64 _, [%0], %1;");
3068}
3069
3070std::string NVVM::MBarrierTryWaitParityOp::getPtx() {
3071 bool isShared = isPtrInSharedCTASpace(getAddr());
3072 llvm::StringRef space = isShared ? ".shared" : "";
3073
3074 return llvm::formatv("{\n\t"
3075 ".reg .pred P1; \n\t"
3076 "LAB_WAIT: \n\t"
3077 "mbarrier.try_wait.parity{0}.b64 P1, [%0], %1, %2; \n\t"
3078 "@P1 bra.uni DONE; \n\t"
3079 "bra.uni LAB_WAIT; \n\t"
3080 "DONE: \n\t"
3081 "}",
3082 space);
3083}
3084
3085//===----------------------------------------------------------------------===//
3086// getIntrinsicID/getIntrinsicIDAndArgs methods
3087//===----------------------------------------------------------------------===//
3088
3089mlir::NVVM::IDArgPair NVVM::BarrierOp::getIntrinsicIDAndArgs(
3090 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3091 auto thisOp = cast<NVVM::BarrierOp>(op);
3092 llvm::Value *barrierId = thisOp.getBarrierId()
3093 ? mt.lookupValue(thisOp.getBarrierId())
3094 : builder.getInt32(0);
3095 llvm::Intrinsic::ID id;
3097 if (thisOp.getNumberOfThreads()) {
3098 id = llvm::Intrinsic::nvvm_barrier_cta_sync_aligned_count;
3099 args.push_back(barrierId);
3100 args.push_back(mt.lookupValue(thisOp.getNumberOfThreads()));
3101 } else if (thisOp.getReductionOp()) {
3102 switch (*thisOp.getReductionOp()) {
3103 case NVVM::BarrierReduction::AND:
3104 id = llvm::Intrinsic::nvvm_barrier0_and;
3105 break;
3106 case NVVM::BarrierReduction::OR:
3107 id = llvm::Intrinsic::nvvm_barrier0_or;
3108 break;
3109 case NVVM::BarrierReduction::POPC:
3110 id = llvm::Intrinsic::nvvm_barrier0_popc;
3111 break;
3112 }
3113 args.push_back(mt.lookupValue(thisOp.getReductionPredicate()));
3114 } else {
3115 id = llvm::Intrinsic::nvvm_barrier_cta_sync_aligned_all;
3116 args.push_back(barrierId);
3117 }
3118
3119 return {id, std::move(args)};
3120}
3121
3123PMEventOp::getIntrinsicIDAndArgs(Operation &op, LLVM::ModuleTranslation &mt,
3124 llvm::IRBuilderBase &builder) {
3125 auto thisOp = cast<NVVM::PMEventOp>(op);
3126 llvm::Type *i16Ty = llvm::Type::getInt16Ty(mt.getLLVMContext());
3127
3128 // With event-id, mask is generated as (1 << event-id)
3129 llvm::Value *maskVal;
3130 if (auto eventAttr = thisOp.getEventIdAttr()) {
3131 uint16_t mask = static_cast<uint16_t>(1u << eventAttr.getInt());
3132 maskVal = llvm::ConstantInt::get(i16Ty, mask);
3133 } else {
3134 maskVal =
3135 llvm::ConstantInt::get(i16Ty, thisOp.getMaskedEventIdAttr().getValue());
3136 }
3137
3138 return {llvm::Intrinsic::nvvm_pm_event_mask, {maskVal}};
3139}
3140
3141mlir::NVVM::IDArgPair MBarrierInitOp::getIntrinsicIDAndArgs(
3142 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3143 auto thisOp = cast<NVVM::MBarrierInitOp>(op);
3144 bool isShared = isPtrInSharedCTASpace(thisOp.getAddr());
3145 llvm::Intrinsic::ID id = isShared ? llvm::Intrinsic::nvvm_mbarrier_init_shared
3146 : llvm::Intrinsic::nvvm_mbarrier_init;
3147
3148 // Fill the Intrinsic Args
3150 args.push_back(mt.lookupValue(thisOp.getAddr()));
3151 args.push_back(mt.lookupValue(thisOp.getCount()));
3152
3153 return {id, std::move(args)};
3154}
3155
3156mlir::NVVM::IDArgPair MBarrierInvalOp::getIntrinsicIDAndArgs(
3157 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3158 auto thisOp = cast<NVVM::MBarrierInvalOp>(op);
3159 bool isShared = isPtrInSharedCTASpace(thisOp.getAddr());
3160 llvm::Intrinsic::ID id = isShared
3161 ? llvm::Intrinsic::nvvm_mbarrier_inval_shared
3162 : llvm::Intrinsic::nvvm_mbarrier_inval;
3163
3164 return {id, {mt.lookupValue(thisOp.getAddr())}};
3165}
3166
3167mlir::NVVM::IDArgPair MBarrierExpectTxOp::getIntrinsicIDAndArgs(
3168 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3169 auto thisOp = cast<NVVM::MBarrierExpectTxOp>(op);
3170
3171 bool isClusterSpace = isPtrInSharedClusterSpace(thisOp.getAddr());
3172 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3173 // bit-0: Space
3174 // bit-1: Scope
3175 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3176
3177 static constexpr llvm::Intrinsic::ID IDs[] = {
3178 llvm::Intrinsic::nvvm_mbarrier_expect_tx_scope_cta_space_cta,
3179 llvm::Intrinsic::nvvm_mbarrier_expect_tx_scope_cta_space_cluster,
3180 llvm::Intrinsic::nvvm_mbarrier_expect_tx_scope_cluster_space_cta,
3181 llvm::Intrinsic::nvvm_mbarrier_expect_tx_scope_cluster_space_cluster};
3182
3183 // Fill the Intrinsic Args
3185 args.push_back(mt.lookupValue(thisOp.getAddr()));
3186 args.push_back(mt.lookupValue(thisOp.getTxcount()));
3187
3188 return {IDs[index], std::move(args)};
3189}
3190
3191mlir::NVVM::IDArgPair MBarrierCompleteTxOp::getIntrinsicIDAndArgs(
3192 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3193 auto thisOp = cast<NVVM::MBarrierCompleteTxOp>(op);
3194
3195 bool isClusterSpace = isPtrInSharedClusterSpace(thisOp.getAddr());
3196 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3197 // bit-0: Space
3198 // bit-1: Scope
3199 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3200
3201 static constexpr llvm::Intrinsic::ID IDs[] = {
3202 llvm::Intrinsic::nvvm_mbarrier_complete_tx_scope_cta_space_cta,
3203 llvm::Intrinsic::nvvm_mbarrier_complete_tx_scope_cta_space_cluster,
3204 llvm::Intrinsic::nvvm_mbarrier_complete_tx_scope_cluster_space_cta,
3205 llvm::Intrinsic::nvvm_mbarrier_complete_tx_scope_cluster_space_cluster};
3206
3207 // Fill the Intrinsic Args
3209 args.push_back(mt.lookupValue(thisOp.getAddr()));
3210 args.push_back(mt.lookupValue(thisOp.getTxcount()));
3211
3212 return {IDs[index], std::move(args)};
3213}
3214
3215mlir::NVVM::IDArgPair MBarrierArriveOp::getIntrinsicIDAndArgs(
3216 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3217 auto thisOp = cast<NVVM::MBarrierArriveOp>(op);
3218
3219 bool isClusterSpace = isPtrInSharedClusterSpace(thisOp.getAddr());
3220 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3221 // bit-0: Space
3222 // bit-1: Scope
3223 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3224
3225 static constexpr llvm::Intrinsic::ID IDs[] = {
3226 llvm::Intrinsic::nvvm_mbarrier_arrive_scope_cta_space_cta,
3227 llvm::Intrinsic::nvvm_mbarrier_arrive_scope_cta_space_cluster,
3228 llvm::Intrinsic::nvvm_mbarrier_arrive_scope_cluster_space_cta,
3229 llvm::Intrinsic::nvvm_mbarrier_arrive_scope_cluster_space_cluster};
3230 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3231 llvm::Intrinsic::nvvm_mbarrier_arrive_relaxed_scope_cta_space_cta,
3232 llvm::Intrinsic::nvvm_mbarrier_arrive_relaxed_scope_cta_space_cluster,
3233 llvm::Intrinsic::nvvm_mbarrier_arrive_relaxed_scope_cluster_space_cta,
3234 llvm::Intrinsic::
3235 nvvm_mbarrier_arrive_relaxed_scope_cluster_space_cluster};
3236 auto id = thisOp.getRelaxed() ? relaxedIDs[index] : IDs[index];
3237
3238 // Tidy-up the Intrinsic Args
3239 bool needCast = isPtrInGenericSpace(thisOp.getAddr());
3240 llvm::Value *mbar = mt.lookupValue(thisOp.getAddr());
3241 if (needCast)
3242 mbar = castPtrToAddrSpace(builder, mbar, NVVMMemorySpace::Shared);
3243
3244 // When count is not explicitly specified, the default is 1.
3245 llvm::LLVMContext &ctx = mt.getLLVMContext();
3246 bool hasCount = static_cast<bool>(thisOp.getCount());
3247 llvm::Value *count =
3248 hasCount ? mt.lookupValue(thisOp.getCount())
3249 : llvm::ConstantInt::get(llvm::Type::getInt32Ty(ctx), 1);
3250
3251 return {id, {mbar, count}};
3252}
3253
3254mlir::NVVM::IDArgPair MBarrierArriveDropOp::getIntrinsicIDAndArgs(
3255 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3256 auto thisOp = cast<NVVM::MBarrierArriveDropOp>(op);
3257
3258 bool isClusterSpace = isPtrInSharedClusterSpace(thisOp.getAddr());
3259 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3260 // bit-0: Space
3261 // bit-1: Scope
3262 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3263
3264 static constexpr llvm::Intrinsic::ID IDs[] = {
3265 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_scope_cta_space_cta,
3266 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_scope_cta_space_cluster,
3267 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_scope_cluster_space_cta,
3268 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_scope_cluster_space_cluster};
3269 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3270 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_relaxed_scope_cta_space_cta,
3271 llvm::Intrinsic::
3272 nvvm_mbarrier_arrive_drop_relaxed_scope_cta_space_cluster,
3273 llvm::Intrinsic::
3274 nvvm_mbarrier_arrive_drop_relaxed_scope_cluster_space_cta,
3275 llvm::Intrinsic::
3276 nvvm_mbarrier_arrive_drop_relaxed_scope_cluster_space_cluster};
3277 auto id = thisOp.getRelaxed() ? relaxedIDs[index] : IDs[index];
3278
3279 // Tidy-up the Intrinsic Args
3280 bool needCast = isPtrInGenericSpace(thisOp.getAddr());
3281 llvm::Value *mbar = mt.lookupValue(thisOp.getAddr());
3282 if (needCast)
3283 mbar = castPtrToAddrSpace(builder, mbar, NVVMMemorySpace::Shared);
3284
3285 // When count is not explicitly specified, the default is 1.
3286 llvm::LLVMContext &ctx = mt.getLLVMContext();
3287 bool hasCount = static_cast<bool>(thisOp.getCount());
3288 llvm::Value *count =
3289 hasCount ? mt.lookupValue(thisOp.getCount())
3290 : llvm::ConstantInt::get(llvm::Type::getInt32Ty(ctx), 1);
3291
3292 return {id, {mbar, count}};
3293}
3294
3295bool MBarrierArriveExpectTxOp::getAsmValues(
3296 RewriterBase &rewriter,
3297 llvm::SmallVectorImpl<std::pair<mlir::Value, mlir::NVVM::PTXRegisterMod>>
3298 &asmValues) {
3299 // Add all the operands but not the attrs to the asmValues list.
3300 // The attrs here are used to generate the right variants for
3301 // intrinsics-lowering. So, we ignore them while generating inline-PTX.
3302 for (auto val : getOperands())
3303 asmValues.push_back({val, mlir::NVVM::PTXRegisterMod::Read});
3304
3305 return false;
3306}
3307
3308mlir::NVVM::IDArgPair MBarrierArriveExpectTxOp::getIntrinsicIDAndArgs(
3309 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3310 auto thisOp = cast<NVVM::MBarrierArriveExpectTxOp>(op);
3311
3312 bool isClusterSpace = isPtrInSharedClusterSpace(thisOp.getAddr());
3313 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3314 // bit-0: Space
3315 // bit-1: Scope
3316 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3317
3318 // clang-format off
3319 static constexpr llvm::Intrinsic::ID IDs[] = {
3320 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_scope_cta_space_cta,
3321 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_scope_cta_space_cluster,
3322 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_scope_cluster_space_cta,
3323 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_scope_cluster_space_cluster};
3324 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3325 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_relaxed_scope_cta_space_cta,
3326 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_relaxed_scope_cta_space_cluster,
3327 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_relaxed_scope_cluster_space_cta,
3328 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_relaxed_scope_cluster_space_cluster};
3329 // clang-format on
3330 auto id = thisOp.getRelaxed() ? relaxedIDs[index] : IDs[index];
3331
3332 // Tidy-up the Intrinsic Args
3333 llvm::Value *txcount = mt.lookupValue(thisOp.getTxcount());
3334 llvm::Value *mbar = mt.lookupValue(thisOp.getAddr());
3335 bool needCast = isPtrInGenericSpace(thisOp.getAddr());
3336 if (needCast)
3337 mbar = castPtrToAddrSpace(builder, mbar, NVVMMemorySpace::Shared);
3338
3339 return {id, {mbar, txcount}};
3340}
3341
3342mlir::NVVM::IDArgPair MBarrierArriveDropExpectTxOp::getIntrinsicIDAndArgs(
3343 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3344 auto thisOp = cast<NVVM::MBarrierArriveDropExpectTxOp>(op);
3345
3346 bool isClusterSpace = isPtrInSharedClusterSpace(thisOp.getAddr());
3347 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3348 // bit-0: Space
3349 // bit-1: Scope
3350 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3351
3352 // clang-format off
3353 static constexpr llvm::Intrinsic::ID IDs[] = {
3354 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_scope_cta_space_cta,
3355 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_scope_cta_space_cluster,
3356 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_scope_cluster_space_cta,
3357 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_scope_cluster_space_cluster};
3358 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3359 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_relaxed_scope_cta_space_cta,
3360 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_relaxed_scope_cta_space_cluster,
3361 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_relaxed_scope_cluster_space_cta,
3362 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_relaxed_scope_cluster_space_cluster};
3363 // clang-format on
3364 auto id = thisOp.getRelaxed() ? relaxedIDs[index] : IDs[index];
3365
3366 // Tidy-up the Intrinsic Args
3367 llvm::Value *txcount = mt.lookupValue(thisOp.getTxcount());
3368 llvm::Value *mbar = mt.lookupValue(thisOp.getAddr());
3369 bool needCast = isPtrInGenericSpace(thisOp.getAddr());
3370 if (needCast)
3371 mbar = castPtrToAddrSpace(builder, mbar, NVVMMemorySpace::Shared);
3372
3373 return {id, {mbar, txcount}};
3374}
3375
3376mlir::NVVM::IDArgPair MBarrierArriveNocompleteOp::getIntrinsicIDAndArgs(
3377 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3378 auto thisOp = cast<NVVM::MBarrierArriveNocompleteOp>(op);
3379 bool isShared = isPtrInSharedCTASpace(thisOp.getAddr());
3380 llvm::Intrinsic::ID id =
3381 isShared ? llvm::Intrinsic::nvvm_mbarrier_arrive_noComplete_shared
3382 : llvm::Intrinsic::nvvm_mbarrier_arrive_noComplete;
3383 // Fill the Intrinsic Args
3385 args.push_back(mt.lookupValue(thisOp.getAddr()));
3386 args.push_back(mt.lookupValue(thisOp.getCount()));
3387
3388 return {id, std::move(args)};
3389}
3390
3391mlir::NVVM::IDArgPair MBarrierArriveDropNocompleteOp::getIntrinsicIDAndArgs(
3392 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3393 auto thisOp = cast<NVVM::MBarrierArriveDropNocompleteOp>(op);
3394 bool isShared = isPtrInSharedCTASpace(thisOp.getAddr());
3395 llvm::Intrinsic::ID id =
3396 isShared ? llvm::Intrinsic::nvvm_mbarrier_arrive_drop_noComplete_shared
3397 : llvm::Intrinsic::nvvm_mbarrier_arrive_drop_noComplete;
3398 // Fill the Intrinsic Args
3400 args.push_back(mt.lookupValue(thisOp.getAddr()));
3401 args.push_back(mt.lookupValue(thisOp.getCount()));
3402
3403 return {id, std::move(args)};
3404}
3405
3406mlir::NVVM::IDArgPair MBarrierTestWaitOp::getIntrinsicIDAndArgs(
3407 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3408 auto thisOp = cast<NVVM::MBarrierTestWaitOp>(op);
3409 bool isPhaseParity = thisOp.getStateOrPhase().getType().isInteger(32);
3410 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3411 // bit-0: isPhaseParity
3412 // bit-1: Scope
3413 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isPhaseParity ? 1 : 0);
3414
3415 // clang-format off
3416 static constexpr llvm::Intrinsic::ID IDs[] = {
3417 llvm::Intrinsic::nvvm_mbarrier_test_wait_scope_cta_space_cta,
3418 llvm::Intrinsic::nvvm_mbarrier_test_wait_parity_scope_cta_space_cta,
3419 llvm::Intrinsic::nvvm_mbarrier_test_wait_scope_cluster_space_cta,
3420 llvm::Intrinsic::nvvm_mbarrier_test_wait_parity_scope_cluster_space_cta};
3421 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3422 llvm::Intrinsic::nvvm_mbarrier_test_wait_relaxed_scope_cta_space_cta,
3423 llvm::Intrinsic::nvvm_mbarrier_test_wait_parity_relaxed_scope_cta_space_cta,
3424 llvm::Intrinsic::nvvm_mbarrier_test_wait_relaxed_scope_cluster_space_cta,
3425 llvm::Intrinsic::nvvm_mbarrier_test_wait_parity_relaxed_scope_cluster_space_cta};
3426 // clang-format on
3427 auto id = thisOp.getRelaxed() ? relaxedIDs[index] : IDs[index];
3428
3429 // Tidy-up the Intrinsic Args
3430 llvm::Value *mbar = mt.lookupValue(thisOp.getAddr());
3431 llvm::Value *input = mt.lookupValue(thisOp.getStateOrPhase());
3432 bool needCast = isPtrInGenericSpace(thisOp.getAddr());
3433 if (needCast)
3434 mbar = castPtrToAddrSpace(builder, mbar, NVVMMemorySpace::Shared);
3435
3436 return {id, {mbar, input}};
3437}
3438
3439mlir::NVVM::IDArgPair MBarrierTryWaitOp::getIntrinsicIDAndArgs(
3440 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3441 auto thisOp = cast<NVVM::MBarrierTryWaitOp>(op);
3442 bool isPhaseParity = thisOp.getStateOrPhase().getType().isInteger(32);
3443 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3444 bool hasTicks = static_cast<bool>(thisOp.getTicks());
3445 // bit-0: isPhaseParity
3446 // bit-1: Scope
3447 // bit-2: hasTicks
3448 size_t index = ((hasTicks ? 1 : 0) << 2) | ((isClusterScope ? 1 : 0) << 1) |
3449 (isPhaseParity ? 1 : 0);
3450
3451 // clang-format off
3452 static constexpr llvm::Intrinsic::ID IDs[] = {
3453 llvm::Intrinsic::nvvm_mbarrier_try_wait_scope_cta_space_cta,
3454 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_scope_cta_space_cta,
3455 llvm::Intrinsic::nvvm_mbarrier_try_wait_scope_cluster_space_cta,
3456 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_scope_cluster_space_cta,
3457 llvm::Intrinsic::nvvm_mbarrier_try_wait_tl_scope_cta_space_cta,
3458 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_tl_scope_cta_space_cta,
3459 llvm::Intrinsic::nvvm_mbarrier_try_wait_tl_scope_cluster_space_cta,
3460 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_tl_scope_cluster_space_cta};
3461 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3462 llvm::Intrinsic::nvvm_mbarrier_try_wait_relaxed_scope_cta_space_cta,
3463 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_relaxed_scope_cta_space_cta,
3464 llvm::Intrinsic::nvvm_mbarrier_try_wait_relaxed_scope_cluster_space_cta,
3465 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_relaxed_scope_cluster_space_cta,
3466 llvm::Intrinsic::nvvm_mbarrier_try_wait_tl_relaxed_scope_cta_space_cta,
3467 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_tl_relaxed_scope_cta_space_cta,
3468 llvm::Intrinsic::nvvm_mbarrier_try_wait_tl_relaxed_scope_cluster_space_cta,
3469 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_tl_relaxed_scope_cluster_space_cta};
3470 // clang-format on
3471 auto id = thisOp.getRelaxed() ? relaxedIDs[index] : IDs[index];
3472
3473 // Tidy-up the mbarrier pointer
3474 llvm::Value *mbar = mt.lookupValue(thisOp.getAddr());
3475 bool needCast = isPtrInGenericSpace(thisOp.getAddr());
3476 if (needCast)
3477 mbar = castPtrToAddrSpace(builder, mbar, NVVMMemorySpace::Shared);
3478
3479 // Fill the Intrinsic Args
3481 args.push_back(mbar);
3482 args.push_back(mt.lookupValue(thisOp.getStateOrPhase()));
3483 if (hasTicks)
3484 args.push_back(mt.lookupValue(thisOp.getTicks()));
3485
3486 return {id, std::move(args)};
3487}
3488
3489mlir::NVVM::IDArgPair CpAsyncMBarrierArriveOp::getIntrinsicIDAndArgs(
3490 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3491 auto thisOp = cast<NVVM::CpAsyncMBarrierArriveOp>(op);
3492 bool isShared = isPtrInSharedCTASpace(thisOp.getAddr());
3493
3494 llvm::Intrinsic::ID id;
3495 if (thisOp.getNoinc()) {
3496 id = isShared ? llvm::Intrinsic::nvvm_cp_async_mbarrier_arrive_noinc_shared
3497 : llvm::Intrinsic::nvvm_cp_async_mbarrier_arrive_noinc;
3498 } else {
3499 id = isShared ? llvm::Intrinsic::nvvm_cp_async_mbarrier_arrive_shared
3500 : llvm::Intrinsic::nvvm_cp_async_mbarrier_arrive;
3501 }
3502
3503 return {id, {mt.lookupValue(thisOp.getAddr())}};
3504}
3505
3506#define CP_ASYNC_ID_IMPL(mod, size, suffix) \
3507 llvm::Intrinsic::nvvm_cp_async_##mod##_shared_global_##size##suffix
3508
3509#define GET_CP_ASYNC_ID(mod, size, has_cpsize) \
3510 has_cpsize ? CP_ASYNC_ID_IMPL(mod, size, _s) : CP_ASYNC_ID_IMPL(mod, size, )
3511
3512llvm::Intrinsic::ID
3513CpAsyncOp::getIntrinsicIDAndArgs(Operation &op, LLVM::ModuleTranslation &mt,
3515 llvm::Intrinsic::ID id;
3516
3517 auto cpAsyncOp = cast<NVVM::CpAsyncOp>(op);
3518 bool hasCpSize = static_cast<bool>(cpAsyncOp.getCpSize());
3519 switch (cpAsyncOp.getSize()) {
3520 case 4:
3521 id = GET_CP_ASYNC_ID(ca, 4, hasCpSize);
3522 break;
3523 case 8:
3524 id = GET_CP_ASYNC_ID(ca, 8, hasCpSize);
3525 break;
3526 case 16:
3527 id = (cpAsyncOp.getModifier() == NVVM::LoadCacheModifierKind::CG)
3528 ? GET_CP_ASYNC_ID(cg, 16, hasCpSize)
3529 : GET_CP_ASYNC_ID(ca, 16, hasCpSize);
3530 break;
3531 default:
3532 llvm_unreachable("Invalid copy size in CpAsyncOp.");
3533 }
3534
3535 // Fill the Intrinsic Args
3536 args.push_back(mt.lookupValue(cpAsyncOp.getDst()));
3537 args.push_back(mt.lookupValue(cpAsyncOp.getSrc()));
3538 if (hasCpSize)
3539 args.push_back(mt.lookupValue(cpAsyncOp.getCpSize()));
3540
3541 return id;
3542}
3543
3544mlir::NVVM::IDArgPair CpAsyncBulkPrefetchOp::getIntrinsicIDAndArgs(
3545 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3546 auto thisOp = cast<NVVM::CpAsyncBulkPrefetchOp>(op);
3548 llvm::Intrinsic::ID id = llvm::Intrinsic::nvvm_cp_async_bulk_prefetch_L2;
3549
3550 // Fill the Intrinsic Args
3551 args.push_back(mt.lookupValue(thisOp.getSrcMem()));
3552 args.push_back(mt.lookupValue(thisOp.getSize()));
3553
3554 mlir::Value cacheHint = thisOp.getL2CacheHint();
3555 const bool hasCacheHint = static_cast<bool>(cacheHint);
3556 llvm::Value *i64Unused =
3557 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.getLLVMContext()), 0);
3558 args.push_back(hasCacheHint ? mt.lookupValue(cacheHint) : i64Unused);
3559 args.push_back(builder.getInt1(hasCacheHint));
3560
3561 return {id, std::move(args)};
3562}
3563
3564mlir::NVVM::IDArgPair CpAsyncBulkGlobalToSharedClusterOp::getIntrinsicIDAndArgs(
3565 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3566 auto thisOp = cast<NVVM::CpAsyncBulkGlobalToSharedClusterOp>(op);
3568
3569 // Fill the Intrinsic Args: dst, mbar, src, size.
3570 args.push_back(mt.lookupValue(thisOp.getDstMem()));
3571 args.push_back(mt.lookupValue(thisOp.getMbar()));
3572 args.push_back(mt.lookupValue(thisOp.getSrcMem()));
3573 args.push_back(mt.lookupValue(thisOp.getSize()));
3574
3575 // Multicast mask for shared::cluster only, if available.
3576 mlir::Value multicastMask = thisOp.getMulticastMask();
3577 const bool hasMulticastMask = static_cast<bool>(multicastMask);
3578 const bool isSharedCTA = isPtrInSharedCTASpace(thisOp.getDstMem());
3579 if (!isSharedCTA) {
3580 llvm::Value *i16Unused = llvm::ConstantInt::get(builder.getInt16Ty(), 0);
3581 args.push_back(hasMulticastMask ? mt.lookupValue(multicastMask)
3582 : i16Unused);
3583 }
3584
3585 // Cache hint, if available.
3586 mlir::Value cacheHint = thisOp.getL2CacheHint();
3587 const bool hasCacheHint = static_cast<bool>(cacheHint);
3588 llvm::Value *i64Unused = llvm::ConstantInt::get(builder.getInt64Ty(), 0);
3589 args.push_back(hasCacheHint ? mt.lookupValue(cacheHint) : i64Unused);
3590
3591 // Flag arguments for multicast and cachehint.
3592 if (!isSharedCTA)
3593 args.push_back(builder.getInt1(hasMulticastMask));
3594 args.push_back(builder.getInt1(hasCacheHint));
3595
3596 llvm::Intrinsic::ID id =
3597 isSharedCTA
3598 ? llvm::Intrinsic::nvvm_cp_async_bulk_global_to_shared_cta
3599 : llvm::Intrinsic::nvvm_cp_async_bulk_global_to_shared_cluster;
3600
3601 return {id, std::move(args)};
3602}
3603
3604mlir::NVVM::IDArgPair CpAsyncBulkSharedCTAToGlobalOp::getIntrinsicIDAndArgs(
3605 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3606 auto thisOp = cast<NVVM::CpAsyncBulkSharedCTAToGlobalOp>(op);
3608 llvm::Intrinsic::ID id =
3609 llvm::Intrinsic::nvvm_cp_async_bulk_shared_cta_to_global;
3610
3611 // Fill the Intrinsic Args
3612 args.push_back(mt.lookupValue(thisOp.getDstMem()));
3613 args.push_back(mt.lookupValue(thisOp.getSrcMem()));
3614 args.push_back(mt.lookupValue(thisOp.getSize()));
3615
3616 mlir::Value cacheHint = thisOp.getL2CacheHint();
3617 const bool hasCacheHint = static_cast<bool>(cacheHint);
3618 llvm::Value *i64Unused =
3619 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.getLLVMContext()), 0);
3620 args.push_back(hasCacheHint ? mt.lookupValue(cacheHint) : i64Unused);
3621 args.push_back(builder.getInt1(hasCacheHint));
3622
3623 // Choose the bytemask variant
3624 if (mlir::Value byteMask = thisOp.getByteMask()) {
3625 args.push_back(mt.lookupValue(byteMask));
3626 id = llvm::Intrinsic::nvvm_cp_async_bulk_shared_cta_to_global_bytemask;
3627 }
3628
3629 return {id, std::move(args)};
3630}
3631
3632bool CpAsyncBulkTensorGlobalToSharedClusterOp::getAsmValues(
3633 RewriterBase &rewriter,
3634 llvm::SmallVectorImpl<std::pair<mlir::Value, mlir::NVVM::PTXRegisterMod>>
3635 &asmValues) {
3636 // Add all the operands but not the attrs to the asmValues list.
3637 // The attrs here are used to generate the right variants for
3638 // intrinsics-lowering. So, we ignore them while generating inline-PTX.
3639 for (auto val : getOperands())
3640 asmValues.push_back({val, mlir::NVVM::PTXRegisterMod::Read});
3641
3642 return false;
3643}
3644
3646CpAsyncBulkTensorGlobalToSharedClusterOp::getIntrinsicIDAndArgs(
3647 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3648 auto thisOp = cast<NVVM::CpAsyncBulkTensorGlobalToSharedClusterOp>(op);
3649 const bool isCTAOnly = thisOp.getIsCTAOnly();
3651
3652 // Fill the Intrinsic Args
3653 args.push_back(mt.lookupValue(thisOp.getDstMem()));
3654 args.push_back(mt.lookupValue(thisOp.getMbar()));
3655 args.push_back(mt.lookupValue(thisOp.getTmaDescriptor()));
3656
3657 // Coordinates and im2col-offsets
3658 for (mlir::Value v : thisOp.getCoordinates())
3659 args.push_back(mt.lookupValue(v));
3660 for (mlir::Value v : thisOp.getIm2colOffsets())
3661 args.push_back(mt.lookupValue(v));
3662
3663 // MulticastMask, if available
3664 mlir::Value mcMask = thisOp.getMulticastMask();
3665 const bool hasMC = static_cast<bool>(mcMask);
3666 llvm::Value *i16Zero =
3667 llvm::ConstantInt::get(llvm::Type::getInt16Ty(mt.getLLVMContext()), 0);
3668
3669 // CacheHint, if available
3670 mlir::Value cacheHint = thisOp.getL2CacheHint();
3671 const bool hasCacheHint = static_cast<bool>(cacheHint);
3672 llvm::Value *i64Zero =
3673 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.getLLVMContext()), 0);
3674
3675 // Flag argument CTAGroup
3676 // CTA_1/2 is mapped to values 1 and 2 for the intrinsics.
3677 // Hence, the +1 to getGroup().
3678 const int32_t val =
3679 thisOp.getGroup() ? (static_cast<int32_t>(*thisOp.getGroup()) + 1) : 0;
3680 llvm::Value *cg =
3681 llvm::ConstantInt::get(llvm::Type::getInt32Ty(mt.getLLVMContext()), val);
3682
3683 if (!isCTAOnly) {
3684 // For shared::cluster, all the arguments that we build are applicable.
3685 args.push_back(hasMC ? mt.lookupValue(mcMask) : i16Zero);
3686 args.push_back(hasCacheHint ? mt.lookupValue(cacheHint) : i64Zero);
3687 args.push_back(builder.getInt1(hasMC));
3688 args.push_back(builder.getInt1(hasCacheHint));
3689 args.push_back(cg);
3690 } else {
3691 // For shared::cta, only cache-hint is applicable.
3692 args.push_back(hasCacheHint ? mt.lookupValue(cacheHint) : i64Zero);
3693 args.push_back(builder.getInt1(hasCacheHint));
3694 }
3695
3696 constexpr size_t numDims = 5; // 1D to 5D
3697 constexpr size_t numModes = 5; // Tile, Im2col, w, w_128, gather4
3698 using rowTy = std::array<llvm::Intrinsic::ID, numDims + 1>;
3699 using TableTy = std::array<rowTy, numModes>;
3700 static constexpr TableTy IDTable{
3701 {{notIntrinsic, llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_1d,
3702 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_2d,
3703 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_3d,
3704 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_4d,
3705 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_5d},
3707 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_3d,
3708 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_4d,
3709 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_5d},
3711 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_3d,
3712 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_4d,
3713 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_5d},
3715 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_128_3d,
3716 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_128_4d,
3717 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_128_5d},
3719 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_gather4_2d}}};
3720
3721 static constexpr TableTy IDTableCTA{
3722 {{notIntrinsic,
3723 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_1d,
3724 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_2d,
3725 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_3d,
3726 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_4d,
3727 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_5d},
3729 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_3d,
3730 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_4d,
3731 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_5d},
3733 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_3d,
3734 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_4d,
3735 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_5d},
3737 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_128_3d,
3738 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_128_4d,
3739 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_128_5d},
3741 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_gather4_2d}}};
3742
3743 static_assert(
3744 (getMaxEnumValForTMALoadMode() == std::size(IDTable) - 1) &&
3745 (getMaxEnumValForTMALoadMode() == std::size(IDTableCTA) - 1),
3746 "TMALoadModes must match number of rows in IDTable and IDTableCTA");
3747 size_t mode = static_cast<size_t>(thisOp.getMode());
3748 size_t dim = thisOp.getCoordinates().size();
3749 auto id = isCTAOnly ? IDTableCTA[mode][dim] : IDTable[mode][dim];
3750 assert(id != notIntrinsic &&
3751 "Invalid intrinsic for CpAsyncBulkTensorGlobalToSharedClusterOp.");
3752
3753 return {id, std::move(args)};
3754}
3755
3756mlir::NVVM::IDArgPair CpAsyncBulkTensorPrefetchOp::getIntrinsicIDAndArgs(
3757 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3758 auto thisOp = cast<NVVM::CpAsyncBulkTensorPrefetchOp>(op);
3760
3761 // Fill the Intrinsic Args
3762 args.push_back(mt.lookupValue(thisOp.getTmaDescriptor()));
3763
3764 for (auto v : thisOp.getCoordinates())
3765 args.push_back(mt.lookupValue(v));
3766 for (auto v : thisOp.getIm2colOffsets())
3767 args.push_back(mt.lookupValue(v));
3768
3769 mlir::Value cacheHint = thisOp.getL2CacheHint();
3770 const bool hasCacheHint = static_cast<bool>(cacheHint);
3771 llvm::Value *i64Unused =
3772 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.getLLVMContext()), 0);
3773 args.push_back(hasCacheHint ? mt.lookupValue(cacheHint) : i64Unused);
3774 args.push_back(builder.getInt1(hasCacheHint));
3775
3776 const unsigned NI = llvm::Intrinsic::not_intrinsic;
3777 static constexpr llvm::Intrinsic::ID IDTable[][6] = {
3778 {NI, llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_1d,
3779 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_2d,
3780 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_3d,
3781 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_4d,
3782 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_5d},
3783 {NI, NI, NI,
3784 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_3d,
3785 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_4d,
3786 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_5d},
3787 {NI, NI, NI,
3788 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_3d,
3789 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_4d,
3790 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_5d},
3791 {NI, NI, NI,
3792 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_128_3d,
3793 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_128_4d,
3794 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_128_5d},
3795 {NI, NI, NI, NI, NI,
3796 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_gather4_2d}};
3797
3798 static_assert(getMaxEnumValForTMALoadMode() == std::size(IDTable) - 1,
3799 "TMALoadModes must match number of rows in IDTable");
3800 size_t mode = static_cast<size_t>(thisOp.getMode());
3801 size_t dim = thisOp.getCoordinates().size();
3802 llvm::Intrinsic::ID id = IDTable[mode][dim];
3803 if (id == llvm::Intrinsic::not_intrinsic)
3804 llvm_unreachable("Invalid intrinsic for CpAsyncBulkTensorPrefetchOp.");
3805
3806 return {id, std::move(args)};
3807}
3808
3810CpAsyncBulkTensorSharedCTAToGlobalOp::getIntrinsicIDAndArgs(
3811 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3812 auto thisOp = cast<NVVM::CpAsyncBulkTensorSharedCTAToGlobalOp>(op);
3814
3815 // Fill the Intrinsic Args
3816 args.push_back(mt.lookupValue(thisOp.getSrcMem()));
3817 args.push_back(mt.lookupValue(thisOp.getTmaDescriptor()));
3818
3819 for (auto v : thisOp.getCoordinates())
3820 args.push_back(mt.lookupValue(v));
3821
3822 mlir::Value cacheHint = thisOp.getL2CacheHint();
3823 const bool hasCacheHint = static_cast<bool>(cacheHint);
3824 llvm::Value *i64Unused =
3825 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.getLLVMContext()), 0);
3826 args.push_back(hasCacheHint ? mt.lookupValue(cacheHint) : i64Unused);
3827 args.push_back(builder.getInt1(hasCacheHint));
3828
3829 const unsigned NI = llvm::Intrinsic::not_intrinsic;
3830 static constexpr llvm::Intrinsic::ID IDTable[][6] = {
3831 {NI, llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_1d,
3832 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_2d,
3833 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_3d,
3834 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_4d,
3835 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_5d},
3836 {NI, NI, NI, llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_im2col_3d,
3837 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_im2col_4d,
3838 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_im2col_5d},
3839 {NI, NI, NI, NI, NI,
3840 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_scatter4_2d}};
3841
3842 static_assert(getMaxEnumValForTMAStoreMode() == std::size(IDTable) - 1,
3843 "TMAStoreModes must match number of rows in IDTable");
3844 size_t mode = static_cast<size_t>(thisOp.getMode());
3845 size_t dim = thisOp.getCoordinates().size();
3846 llvm::Intrinsic::ID id = IDTable[mode][dim];
3847 if (id == llvm::Intrinsic::not_intrinsic)
3848 llvm_unreachable(
3849 "Invalid intrinsic for CpAsyncBulkTensorSharedCTAToGlobalOp.");
3850
3851 return {id, std::move(args)};
3852}
3853
3854NVVM::IDArgPair CpAsyncBulkTensorReduceOp::getIntrinsicIDAndArgs(
3855 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
3856 auto thisOp = cast<NVVM::CpAsyncBulkTensorReduceOp>(op);
3857 llvm::LLVMContext &ctx = mt.getLLVMContext();
3858
3860
3861 // Arguments to the intrinsic:
3862 // shared_mem_ptr, tmaDesc, tensorDims
3863 // cache_hint(if applicable) and flag(boolean)
3864 args.push_back(mt.lookupValue(thisOp.getSrcMem()));
3865 args.push_back(mt.lookupValue(thisOp.getTmaDescriptor()));
3866
3867 for (Value v : thisOp.getCoordinates())
3868 args.push_back(mt.lookupValue(v));
3869
3870 mlir::Value cacheHint = thisOp.getL2CacheHint();
3871 const bool hasCacheHint = static_cast<bool>(cacheHint);
3872 llvm::Value *i64ZeroValue =
3873 llvm::ConstantInt::get(llvm::Type::getInt64Ty(ctx), 0);
3874 args.push_back(hasCacheHint ? mt.lookupValue(cacheHint) : i64ZeroValue);
3875 args.push_back(builder.getInt1(hasCacheHint));
3876
3877 const llvm::Intrinsic::ID notIntrinsic = llvm::Intrinsic::not_intrinsic;
3878
3879 constexpr unsigned numRedKinds = 8; // ADD, MIN, MAX, INC, DEC, AND, OR, XOR
3880 constexpr unsigned numLayouts = 2; // TILE, IM2COL
3881 constexpr unsigned maxDim = 5; // 1D to 5D
3882 using row = std::array<llvm::Intrinsic::ID, maxDim + 1>;
3883 using layoutTable = std::array<row, numLayouts>;
3884 using fullTable = std::array<layoutTable, numRedKinds>;
3885 static constexpr fullTable IDTable{
3886 {// RedTy::ADD
3887 {{{{notIntrinsic,
3888 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_1d,
3889 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_2d,
3890 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_3d,
3891 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_4d,
3892 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_5d}},
3894 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_im2col_3d,
3895 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_im2col_4d,
3896 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_im2col_5d}}}},
3897 // RedTy::MIN
3898 {{{{notIntrinsic,
3899 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_1d,
3900 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_2d,
3901 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_3d,
3902 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_4d,
3903 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_5d}},
3905 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_im2col_3d,
3906 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_im2col_4d,
3907 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_im2col_5d}}}},
3908 // RedTy::MAX
3909 {{{{notIntrinsic,
3910 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_1d,
3911 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_2d,
3912 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_3d,
3913 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_4d,
3914 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_5d}},
3916 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_im2col_3d,
3917 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_im2col_4d,
3918 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_im2col_5d}}}},
3919 // RedTy::INC
3920 {{{{notIntrinsic,
3921 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_1d,
3922 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_2d,
3923 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_3d,
3924 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_4d,
3925 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_5d}},
3927 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_im2col_3d,
3928 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_im2col_4d,
3929 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_im2col_5d}}}},
3930 // RedTy::DEC
3931 {{{{notIntrinsic,
3932 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_1d,
3933 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_2d,
3934 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_3d,
3935 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_4d,
3936 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_5d}},
3938 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_im2col_3d,
3939 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_im2col_4d,
3940 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_im2col_5d}}}},
3941 // RedTy::AND
3942 {{{{notIntrinsic,
3943 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_1d,
3944 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_2d,
3945 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_3d,
3946 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_4d,
3947 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_5d}},
3949 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_im2col_3d,
3950 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_im2col_4d,
3951 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_im2col_5d}}}},
3952 // RedTy::OR
3953 {{{{notIntrinsic,
3954 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_1d,
3955 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_2d,
3956 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_3d,
3957 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_4d,
3958 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_5d}},
3960 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_im2col_3d,
3961 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_im2col_4d,
3962 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_im2col_5d}}}},
3963 // RedTy::XOR
3964 {{{{notIntrinsic,
3965 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_1d,
3966 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_2d,
3967 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_3d,
3968 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_4d,
3969 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_5d}},
3971 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_im2col_3d,
3972 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_im2col_4d,
3973 llvm::Intrinsic::
3974 nvvm_cp_async_bulk_tensor_reduce_xor_im2col_5d}}}}}};
3975
3976 static_assert(getMaxEnumValForTMAReduxKind() == std::size(IDTable) - 1,
3977 "TMAReduxKinds must match number of rows in IDTable");
3978
3979 size_t redKind = static_cast<size_t>(thisOp.getRedKind());
3980 size_t mode = static_cast<size_t>(thisOp.getMode());
3981 size_t dim = thisOp.getCoordinates().size();
3982
3983 assert(redKind < IDTable.size() &&
3984 "Invalid redKind for CpAsyncBulkTensorReduceOp");
3985 assert(mode < IDTable[redKind].size() &&
3986 "Invalid mode for CpAsyncBulkTensorReduceOp");
3987 assert(dim < IDTable[redKind][mode].size() &&
3988 "Invalid dim for CpAsyncBulkTensorReduceOp");
3989
3990 llvm::Intrinsic::ID intrinsicID = IDTable[redKind][mode][dim];
3991
3992 assert(intrinsicID != notIntrinsic &&
3993 "Invalid intrinsic for CpAsyncBulkTensorReduceOp.");
3994
3995 return {intrinsicID, std::move(args)};
3996}
3997
3998#define _none
3999
4000#define CVT_F2TF32_ID_IMPL(rnd, relu, sf) \
4001 hasRelu ? llvm::Intrinsic::nvvm_f2tf32_##rnd##relu##sf \
4002 : llvm::Intrinsic::nvvm_f2tf32_##rnd##sf
4003
4004#define GET_CVT_F2TF32_ID(rnd, relu, sf) \
4005 hasSatFinite ? CVT_F2TF32_ID_IMPL(rnd, relu, sf) \
4006 : CVT_F2TF32_ID_IMPL(rnd, relu, )
4007
4008llvm::Intrinsic::ID
4009ConvertFloatToTF32Op::getIntrinsicID(NVVM::FPRoundingMode rnd,
4010 NVVM::SaturationMode sat, bool hasRelu) {
4011 using RndMode = NVVM::FPRoundingMode;
4012 bool hasSatFinite = (sat == NVVM::SaturationMode::SATFINITE);
4013 switch (rnd) {
4014 case RndMode::RN:
4015 return GET_CVT_F2TF32_ID(rn, _relu, _satfinite);
4016 case RndMode::RZ:
4017 return GET_CVT_F2TF32_ID(rz, _relu, _satfinite);
4018 case RndMode::RNA:
4019 return GET_CVT_F2TF32_ID(rna, _none, _satfinite);
4020 default:
4021 llvm_unreachable("Invalid RoundingMode for CvtFloatToTF32Op");
4022 }
4023}
4024
4026ConvertF32x2ToF4x2Op::getIntrinsicIDAndArgs(NVVM::ConvertF32x2ToF4x2Op op,
4028 llvm::IRBuilderBase &builder) {
4030 args.push_back(mt.lookupValue(op.getA()));
4031 args.push_back(mt.lookupValue(op.getB()));
4032
4033 bool hasRelu = op.getRelu();
4034
4035 llvm::Intrinsic::ID intId =
4036 hasRelu ? llvm::Intrinsic::nvvm_ff_to_e2m1x2_rn_relu_satfinite
4037 : llvm::Intrinsic::nvvm_ff_to_e2m1x2_rn_satfinite;
4038
4039 return {intId, std::move(args)};
4040}
4041
4042#define GET_F32x2_TO_F6x2_ID(type, has_relu) \
4043 has_relu ? llvm::Intrinsic::nvvm_ff_to_##type##_rn_relu_satfinite \
4044 : llvm::Intrinsic::nvvm_ff_to_##type##_rn_satfinite
4045
4046llvm::Intrinsic::ID ConvertF32x2ToF6x2Op::getIntrinsicID(mlir::Type dstTy,
4047 bool hasRelu) {
4049 .Case<mlir::Float6E2M3FNType>([&](mlir::Float6E2M3FNType) {
4050 return GET_F32x2_TO_F6x2_ID(e2m3x2, hasRelu);
4051 })
4052 .Case<mlir::Float6E3M2FNType>([&](mlir::Float6E3M2FNType) {
4053 return GET_F32x2_TO_F6x2_ID(e3m2x2, hasRelu);
4054 })
4055 .Default([](mlir::Type) {
4056 llvm_unreachable("Invalid conversion in ConvertF32x2ToF6x2Op");
4057 return llvm::Intrinsic::not_intrinsic;
4058 });
4059}
4060
4061#define GET_F32x2_TO_F8X2_US_ID(rnd, has_satf) \
4062 has_satf ? llvm::Intrinsic::nvvm_ff_to_ue8m0x2_##rnd##_satfinite \
4063 : llvm::Intrinsic::nvvm_ff_to_ue8m0x2_##rnd
4064
4065#define GET_F32x2_TO_F8X2_S_ID(type, has_relu) \
4066 has_relu ? llvm::Intrinsic::nvvm_ff_to_##type##_rn_relu \
4067 : llvm::Intrinsic::nvvm_ff_to_##type##_rn
4068
4069llvm::Intrinsic::ID
4070ConvertF32x2ToF8x2Op::getIntrinsicID(mlir::Type dstTy, NVVM::FPRoundingMode rnd,
4071 NVVM::SaturationMode sat, bool hasRelu) {
4072 bool hasSatFinite = (sat == NVVM::SaturationMode::SATFINITE);
4073 bool hasRoundingModeRZ = (rnd == NVVM::FPRoundingMode::RZ);
4074 bool hasRoundingModeRP = (rnd == NVVM::FPRoundingMode::RP);
4075
4077 .Case<mlir::Float8E4M3FNType>([&](mlir::Float8E4M3FNType) {
4078 return GET_F32x2_TO_F8X2_S_ID(e4m3x2, hasRelu);
4079 })
4080 .Case<mlir::Float8E5M2Type>([&](mlir::Float8E5M2Type) {
4081 return GET_F32x2_TO_F8X2_S_ID(e5m2x2, hasRelu);
4082 })
4083 .Case<mlir::Float8E8M0FNUType>([&](mlir::Float8E8M0FNUType) {
4084 if (hasRoundingModeRZ)
4085 return GET_F32x2_TO_F8X2_US_ID(rz, hasSatFinite);
4086 else if (hasRoundingModeRP)
4087 return GET_F32x2_TO_F8X2_US_ID(rp, hasSatFinite);
4088
4089 llvm_unreachable("Invalid conversion in ConvertF32x2ToF8x2Op");
4090 })
4091 .Default([](mlir::Type) {
4092 llvm_unreachable("Invalid conversion in ConvertF32x2ToF8x2Op");
4093 return llvm::Intrinsic::not_intrinsic;
4094 });
4095}
4096
4097#define GET_F16x2_TO_F8X2_ID(type, has_relu) \
4098 has_relu ? llvm::Intrinsic::nvvm_f16x2_to_##type##_rn_relu \
4099 : llvm::Intrinsic::nvvm_f16x2_to_##type##_rn
4100
4101llvm::Intrinsic::ID ConvertF16x2ToF8x2Op::getIntrinsicID(mlir::Type dstTy,
4102 bool hasRelu) {
4104 .Case<mlir::Float8E4M3FNType>([&](mlir::Float8E4M3FNType) {
4105 return GET_F16x2_TO_F8X2_ID(e4m3x2, hasRelu);
4106 })
4107 .Case<mlir::Float8E5M2Type>([&](mlir::Float8E5M2Type) {
4108 return GET_F16x2_TO_F8X2_ID(e5m2x2, hasRelu);
4109 })
4110 .Default([](mlir::Type) {
4111 llvm_unreachable("Invalid conversion in ConvertF16x2ToF8x2Op");
4112 return llvm::Intrinsic::not_intrinsic;
4113 });
4114}
4115
4116#define GET_BF16X2_TO_F8X2_ID(rnd, has_satf) \
4117 has_satf ? llvm::Intrinsic::nvvm_bf16x2_to_ue8m0x2_##rnd##_satfinite \
4118 : llvm::Intrinsic::nvvm_bf16x2_to_ue8m0x2_##rnd
4119
4120llvm::Intrinsic::ID
4121ConvertBF16x2ToF8x2Op::getIntrinsicID(NVVM::FPRoundingMode rnd,
4122 NVVM::SaturationMode sat) {
4123 bool hasSatFinite = (sat == NVVM::SaturationMode::SATFINITE);
4124 switch (rnd) {
4125 case NVVM::FPRoundingMode::RZ:
4126 return GET_BF16X2_TO_F8X2_ID(rz, hasSatFinite);
4127 case NVVM::FPRoundingMode::RP:
4128 return GET_BF16X2_TO_F8X2_ID(rp, hasSatFinite);
4129 default:
4130 llvm_unreachable("Invalid rounding mode for CvtBF16x2ToF8x2Op");
4131 }
4132}
4133
4134NVVM::IDArgPair ConvertF8x2ToF16x2Op::getIntrinsicIDAndArgs(
4135 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
4136 auto curOp = cast<NVVM::ConvertF8x2ToF16x2Op>(op);
4137
4138 bool hasRelu = curOp.getRelu();
4139
4140 llvm::Intrinsic::ID intId =
4142 .Case<Float8E4M3FNType>([&](Float8E4M3FNType type) {
4143 return hasRelu ? llvm::Intrinsic::nvvm_e4m3x2_to_f16x2_rn_relu
4144 : llvm::Intrinsic::nvvm_e4m3x2_to_f16x2_rn;
4145 })
4146 .Case<Float8E5M2Type>([&](Float8E5M2Type type) {
4147 return hasRelu ? llvm::Intrinsic::nvvm_e5m2x2_to_f16x2_rn_relu
4148 : llvm::Intrinsic::nvvm_e5m2x2_to_f16x2_rn;
4149 })
4150 .Default([](mlir::Type type) {
4151 llvm_unreachable("Invalid type for ConvertF8x2ToF16x2Op");
4152 return llvm::Intrinsic::not_intrinsic;
4153 });
4154
4155 llvm::Value *packedI16 =
4156 builder.CreateBitCast(mt.lookupValue(curOp.getSrc()),
4157 llvm::Type::getInt16Ty(builder.getContext()));
4158
4159 return {intId, {packedI16}};
4160}
4161
4162NVVM::IDArgPair ConvertF8x2ToBF16x2Op::getIntrinsicIDAndArgs(
4163 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
4164 auto curOp = cast<NVVM::ConvertF8x2ToBF16x2Op>(op);
4165
4166 llvm::Intrinsic::ID intId = llvm::Intrinsic::nvvm_ue8m0x2_to_bf16x2;
4167 llvm::Value *packedI16 =
4168 builder.CreateBitCast(mt.lookupValue(curOp.getSrc()),
4169 llvm::Type::getInt16Ty(builder.getContext()));
4170
4171 return {intId, {packedI16}};
4172}
4173
4174NVVM::IDArgPair ConvertF6x2ToF16x2Op::getIntrinsicIDAndArgs(
4175 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
4176 auto curOp = cast<NVVM::ConvertF6x2ToF16x2Op>(op);
4177
4178 bool hasRelu = curOp.getRelu();
4179
4180 llvm::Intrinsic::ID intId =
4182 .Case<Float6E2M3FNType>([&](Float6E2M3FNType type) {
4183 return hasRelu ? llvm::Intrinsic::nvvm_e2m3x2_to_f16x2_rn_relu
4184 : llvm::Intrinsic::nvvm_e2m3x2_to_f16x2_rn;
4185 })
4186 .Case<Float6E3M2FNType>([&](Float6E3M2FNType type) {
4187 return hasRelu ? llvm::Intrinsic::nvvm_e3m2x2_to_f16x2_rn_relu
4188 : llvm::Intrinsic::nvvm_e3m2x2_to_f16x2_rn;
4189 })
4190 .Default([](mlir::Type type) {
4191 llvm_unreachable("Invalid type for ConvertF6x2ToF16x2Op");
4192 return llvm::Intrinsic::not_intrinsic;
4193 });
4194
4195 llvm::Value *packedI16 =
4196 builder.CreateBitCast(mt.lookupValue(curOp.getSrc()),
4197 llvm::Type::getInt16Ty(builder.getContext()));
4198
4199 return {intId, {packedI16}};
4200}
4201
4202NVVM::IDArgPair ConvertF4x2ToF16x2Op::getIntrinsicIDAndArgs(
4203 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
4204 auto curOp = cast<NVVM::ConvertF4x2ToF16x2Op>(op);
4205
4206 bool hasRelu = curOp.getRelu();
4207
4208 llvm::Intrinsic::ID intId =
4210 .Case<Float4E2M1FNType>([&](Float4E2M1FNType type) {
4211 return hasRelu ? llvm::Intrinsic::nvvm_e2m1x2_to_f16x2_rn_relu
4212 : llvm::Intrinsic::nvvm_e2m1x2_to_f16x2_rn;
4213 })
4214 .Default([](mlir::Type type) {
4215 llvm_unreachable("Invalid type for ConvertF4x2ToF16x2Op");
4216 return llvm::Intrinsic::not_intrinsic;
4217 });
4218
4219 llvm::Value *extendedI16 =
4220 builder.CreateZExt(mt.lookupValue(curOp.getSrc()),
4221 llvm::Type::getInt16Ty(builder.getContext()));
4222
4223 return {intId, {extendedI16}};
4224}
4225
4226llvm::Intrinsic::ID
4227Tcgen05AllocOp::getIntrinsicIDAndArgs(Operation &op,
4230 auto curOp = cast<NVVM::Tcgen05AllocOp>(op);
4231 unsigned as = llvm::cast<LLVM::LLVMPointerType>(curOp.getAddr().getType())
4232 .getAddressSpace();
4233 bool isShared = as == NVVMMemorySpace::Shared;
4234 bool is2CTAMode = curOp.getGroup() == CTAGroupKind::CTA_2;
4235
4236 llvm::Intrinsic::ID id;
4237 if (isShared) {
4238 id = is2CTAMode ? llvm::Intrinsic::nvvm_tcgen05_alloc_shared_cg2
4239 : llvm::Intrinsic::nvvm_tcgen05_alloc_shared_cg1;
4240 } else {
4241 id = is2CTAMode ? llvm::Intrinsic::nvvm_tcgen05_alloc_cg2
4242 : llvm::Intrinsic::nvvm_tcgen05_alloc_cg1;
4243 }
4244
4245 // Fill the Intrinsic Args
4246 args.push_back(mt.lookupValue(curOp.getAddr()));
4247 args.push_back(mt.lookupValue(curOp.getNCols()));
4248
4249 return id;
4250}
4251
4252llvm::Intrinsic::ID Tcgen05DeallocOp::getIntrinsicIDAndArgs(
4255 auto curOp = cast<NVVM::Tcgen05DeallocOp>(op);
4256 auto id = (curOp.getGroup() == CTAGroupKind::CTA_1)
4257 ? llvm::Intrinsic::nvvm_tcgen05_dealloc_cg1
4258 : llvm::Intrinsic::nvvm_tcgen05_dealloc_cg2;
4259
4260 // Fill the Intrinsic Args
4261 args.push_back(mt.lookupValue(curOp.getTaddr()));
4262 args.push_back(mt.lookupValue(curOp.getNCols()));
4263
4264 return id;
4265}
4266
4267#define TCGEN05_COMMIT_IMPL(cg, is_shared, mc) \
4268 is_shared ? llvm::Intrinsic::nvvm_tcgen05_commit##mc##_shared##_##cg \
4269 : llvm::Intrinsic::nvvm_tcgen05_commit##mc##_##cg
4270
4271#define GET_TCGEN05_COMMIT_ID(cta_group, is_shared, has_mc) \
4272 has_mc ? TCGEN05_COMMIT_IMPL(cta_group, is_shared, _mc) \
4273 : TCGEN05_COMMIT_IMPL(cta_group, is_shared, )
4274
4275llvm::Intrinsic::ID
4276Tcgen05CommitOp::getIntrinsicIDAndArgs(Operation &op,
4279 auto curOp = cast<NVVM::Tcgen05CommitOp>(op);
4280 unsigned as = llvm::cast<LLVM::LLVMPointerType>(curOp.getAddr().getType())
4281 .getAddressSpace();
4282 bool isShared = as == NVVMMemorySpace::Shared;
4283 bool hasMulticast = static_cast<bool>(curOp.getMulticastMask());
4284 bool is2CTAMode = curOp.getGroup() == CTAGroupKind::CTA_2;
4285
4286 llvm::Intrinsic::ID id =
4287 is2CTAMode ? GET_TCGEN05_COMMIT_ID(cg2, isShared, hasMulticast)
4288 : GET_TCGEN05_COMMIT_ID(cg1, isShared, hasMulticast);
4289
4290 // Fill the Intrinsic Args
4291 args.push_back(mt.lookupValue(curOp.getAddr()));
4292 if (hasMulticast)
4293 args.push_back(mt.lookupValue(curOp.getMulticastMask()));
4294
4295 return id;
4296}
4297
4298#define TCGEN05_CP_IMPL(shape_mc, src_fmt, cg) \
4299 llvm::Intrinsic::nvvm_tcgen05_cp##shape_mc##src_fmt##cg
4300
4301#define TCGEN05_CP_2CTA(shape_mc, src_fmt, is_2cta) \
4302 is_2cta ? TCGEN05_CP_IMPL(shape_mc, src_fmt, _cg2) \
4303 : TCGEN05_CP_IMPL(shape_mc, src_fmt, _cg1)
4304
4305#define GET_TCGEN05_CP_ID(shape_mc, src_fmt, is_2cta) \
4306 [&]() -> auto { \
4307 if ((src_fmt) == Tcgen05CpSrcFormat::B6x16_P32) \
4308 return TCGEN05_CP_2CTA(shape_mc, _b6x16_p32, is_2cta); \
4309 if ((src_fmt) == Tcgen05CpSrcFormat::B4x16_P64) \
4310 return TCGEN05_CP_2CTA(shape_mc, _b4x16_p64, is_2cta); \
4311 return TCGEN05_CP_2CTA(shape_mc, , is_2cta); \
4312 }()
4313
4315ConvertF32x2ToF16x2Op::getIntrinsicIDAndArgs(NVVM::ConvertF32x2ToF16x2Op &op,
4317 llvm::IRBuilderBase &builder) {
4318 static constexpr llvm::Intrinsic::ID rndRNIds[] = {
4319 llvm::Intrinsic::nvvm_ff2f16x2_rn,
4320 llvm::Intrinsic::nvvm_ff2f16x2_rn_relu,
4321 llvm::Intrinsic::nvvm_ff2f16x2_rn_satfinite,
4322 llvm::Intrinsic::nvvm_ff2f16x2_rn_relu_satfinite,
4323 };
4324 static constexpr llvm::Intrinsic::ID rndRZIds[] = {
4325 llvm::Intrinsic::nvvm_ff2f16x2_rz,
4326 llvm::Intrinsic::nvvm_ff2f16x2_rz_relu,
4327 llvm::Intrinsic::nvvm_ff2f16x2_rz_satfinite,
4328 llvm::Intrinsic::nvvm_ff2f16x2_rz_relu_satfinite,
4329 };
4330 static constexpr llvm::Intrinsic::ID rndRSIds[] = {
4331 llvm::Intrinsic::nvvm_ff2f16x2_rs,
4332 llvm::Intrinsic::nvvm_ff2f16x2_rs_relu,
4333 llvm::Intrinsic::nvvm_ff2f16x2_rs_satfinite,
4334 llvm::Intrinsic::nvvm_ff2f16x2_rs_relu_satfinite,
4335 };
4336
4337 unsigned hasRelu = op.getRelu() ? 1 : 0;
4338 unsigned hasSatFinite =
4339 (op.getSat() == NVVM::SaturationMode::SATFINITE) ? 1 : 0;
4340 // idx: bit-0 - relu
4341 // bit-1 - satfinite
4342 unsigned idx = (hasSatFinite << 1) | hasRelu;
4343
4345 args.push_back(mt.lookupValue(op.getSrcHi()));
4346 args.push_back(mt.lookupValue(op.getSrcLo()));
4347 if (op.getRandomBits())
4348 args.push_back(mt.lookupValue(op.getRandomBits()));
4349
4350 switch (op.getRnd()) {
4351 case FPRoundingMode::RN:
4352 return {rndRNIds[idx], std::move(args)};
4353 case FPRoundingMode::RZ:
4354 return {rndRZIds[idx], std::move(args)};
4355 case FPRoundingMode::RS:
4356 return {rndRSIds[idx], std::move(args)};
4357 default:
4358 llvm_unreachable("Invalid rounding mode for ConvertF32x2ToF16x2Op");
4359 }
4360}
4361
4363ConvertF32x2ToBF16x2Op::getIntrinsicIDAndArgs(NVVM::ConvertF32x2ToBF16x2Op &op,
4365 llvm::IRBuilderBase &builder) {
4366 static constexpr llvm::Intrinsic::ID rndRNIds[] = {
4367 llvm::Intrinsic::nvvm_ff2bf16x2_rn,
4368 llvm::Intrinsic::nvvm_ff2bf16x2_rn_relu,
4369 llvm::Intrinsic::nvvm_ff2bf16x2_rn_satfinite,
4370 llvm::Intrinsic::nvvm_ff2bf16x2_rn_relu_satfinite,
4371 };
4372 static constexpr llvm::Intrinsic::ID rndRZIds[] = {
4373 llvm::Intrinsic::nvvm_ff2bf16x2_rz,
4374 llvm::Intrinsic::nvvm_ff2bf16x2_rz_relu,
4375 llvm::Intrinsic::nvvm_ff2bf16x2_rz_satfinite,
4376 llvm::Intrinsic::nvvm_ff2bf16x2_rz_relu_satfinite,
4377 };
4378 static constexpr llvm::Intrinsic::ID rndRSIds[] = {
4379 llvm::Intrinsic::nvvm_ff2bf16x2_rs,
4380 llvm::Intrinsic::nvvm_ff2bf16x2_rs_relu,
4381 llvm::Intrinsic::nvvm_ff2bf16x2_rs_satfinite,
4382 llvm::Intrinsic::nvvm_ff2bf16x2_rs_relu_satfinite,
4383 };
4384
4385 unsigned hasRelu = op.getRelu() ? 1 : 0;
4386 unsigned hasSatFinite =
4387 (op.getSat() == NVVM::SaturationMode::SATFINITE) ? 1 : 0;
4388 // idx: bit-0 - relu
4389 // bit-1 - satfinite
4390 unsigned idx = (hasSatFinite << 1) | hasRelu;
4391
4393 args.push_back(mt.lookupValue(op.getSrcHi()));
4394 args.push_back(mt.lookupValue(op.getSrcLo()));
4395 if (op.getRandomBits())
4396 args.push_back(mt.lookupValue(op.getRandomBits()));
4397
4398 switch (op.getRnd()) {
4399 case FPRoundingMode::RN:
4400 return {rndRNIds[idx], std::move(args)};
4401 case FPRoundingMode::RZ:
4402 return {rndRZIds[idx], std::move(args)};
4403 case FPRoundingMode::RS:
4404 return {rndRSIds[idx], std::move(args)};
4405 default:
4406 llvm_unreachable("Invalid rounding mode for ConvertF32x2ToBF16x2Op");
4407 }
4408}
4409
4410llvm::Intrinsic::ID ConvertF32x4ToF8x4Op::getIntrinsicID() {
4411 mlir::Type dstTy = getDstTy();
4412 bool hasRelu = getRelu();
4413
4415 .Case<mlir::Float8E4M3FNType>([&](mlir::Float8E4M3FNType) {
4416 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e4m3x4_rs_relu_satfinite
4417 : llvm::Intrinsic::nvvm_f32x4_to_e4m3x4_rs_satfinite;
4418 })
4419 .Case<mlir::Float8E5M2Type>([&](mlir::Float8E5M2Type) {
4420 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e5m2x4_rs_relu_satfinite
4421 : llvm::Intrinsic::nvvm_f32x4_to_e5m2x4_rs_satfinite;
4422 })
4423 .Default([](mlir::Type) {
4424 llvm_unreachable("Invalid F8 type in ConvertF32x4ToF8x4Op");
4425 return llvm::Intrinsic::not_intrinsic;
4426 });
4427}
4428
4429llvm::Intrinsic::ID ConvertF32x4ToF6x4Op::getIntrinsicID() {
4430 mlir::Type dstTy = getDstTy();
4431 bool hasRelu = getRelu();
4432
4434 .Case<mlir::Float6E2M3FNType>([&](mlir::Float6E2M3FNType) {
4435 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e2m3x4_rs_relu_satfinite
4436 : llvm::Intrinsic::nvvm_f32x4_to_e2m3x4_rs_satfinite;
4437 })
4438 .Case<mlir::Float6E3M2FNType>([&](mlir::Float6E3M2FNType) {
4439 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e3m2x4_rs_relu_satfinite
4440 : llvm::Intrinsic::nvvm_f32x4_to_e3m2x4_rs_satfinite;
4441 })
4442 .Default([](mlir::Type) {
4443 llvm_unreachable("Invalid F6 type in ConvertF32x4ToF6x4Op");
4444 return llvm::Intrinsic::not_intrinsic;
4445 });
4446}
4447
4448llvm::Intrinsic::ID ConvertF32x4ToF4x4Op::getIntrinsicID() {
4449 mlir::Type dstTy = getDstTy();
4450 bool hasRelu = getRelu();
4451
4453 .Case<mlir::Float4E2M1FNType>([&](mlir::Float4E2M1FNType) {
4454 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e2m1x4_rs_relu_satfinite
4455 : llvm::Intrinsic::nvvm_f32x4_to_e2m1x4_rs_satfinite;
4456 })
4457 .Default([](mlir::Type) {
4458 llvm_unreachable("Invalid F4 type in ConvertF32x4ToF4x4Op");
4459 return llvm::Intrinsic::not_intrinsic;
4460 });
4461}
4462
4463llvm::Intrinsic::ID Tcgen05CpOp::getIntrinsicID(Operation &op) {
4464 auto curOp = cast<NVVM::Tcgen05CpOp>(op);
4465 bool is2CTA = curOp.getGroup() == CTAGroupKind::CTA_2;
4466 auto srcFmt = curOp.getSrcFormat();
4467 auto mc = curOp.getMulticast();
4468
4469 switch (curOp.getShape()) {
4470 case Tcgen05CpShape::SHAPE_128x256b:
4471 return GET_TCGEN05_CP_ID(_128x256b, srcFmt, is2CTA);
4472 case Tcgen05CpShape::SHAPE_128x128b:
4473 return GET_TCGEN05_CP_ID(_128x128b, srcFmt, is2CTA);
4474 case Tcgen05CpShape::SHAPE_4x256b:
4475 return GET_TCGEN05_CP_ID(_4x256b, srcFmt, is2CTA);
4476 case Tcgen05CpShape::SHAPE_32x128b:
4477 return GET_TCGEN05_CP_ID(_32x128b_warpx4, srcFmt, is2CTA);
4478 case Tcgen05CpShape::SHAPE_64x128b:
4479 return (mc == Tcgen05CpMulticast::WARPX2_01_23)
4480 ? GET_TCGEN05_CP_ID(_64x128b_warpx2_01_23, srcFmt, is2CTA)
4481 : GET_TCGEN05_CP_ID(_64x128b_warpx2_02_13, srcFmt, is2CTA);
4482 }
4483 llvm_unreachable("Invalid shape in tcgen05 cp Op");
4484}
4485
4486// Returns the valid vector length for a given shape and vector length, the
4487// function models the table mentioned in the tcgen05.{ld, st} Op description
4488static unsigned isValidVectorLength(NVVM::Tcgen05LdStShape shape,
4489 unsigned vecLen) {
4490 if (shape == NVVM::Tcgen05LdStShape::SHAPE_16X128B)
4491 return vecLen >= 2;
4492 if (shape == NVVM::Tcgen05LdStShape::SHAPE_16X256B)
4493 return vecLen >= 4;
4494 return true;
4495}
4496
4497LogicalResult Tcgen05LdOp::verify() {
4498 LogicalResult result = success();
4499 if (getShape() == NVVM::Tcgen05LdStShape::SHAPE_16X32BX2 && !getOffset())
4500 result = emitError("shape 16x32bx2 requires offset argument");
4501
4502 if (getShape() != NVVM::Tcgen05LdStShape::SHAPE_16X32BX2 && getOffset())
4503 result = emitError("offset argument is only supported for shape 16x32bx2");
4504
4505 auto resTy = getRes().getType();
4506 unsigned resLen = isa<VectorType>(resTy)
4507 ? llvm::cast<VectorType>(resTy).getNumElements()
4508 : 1;
4509 if (!isValidVectorLength(getShape(), resLen))
4510 result = emitError(llvm::formatv("invalid result type length {0} for shape "
4511 "{1} in tcgen05.ld Op",
4512 resLen, stringifyEnum(getShape())));
4513
4514 return result;
4515}
4516
4517LogicalResult Tcgen05StOp::verify() {
4518 LogicalResult result = success();
4519 if (getShape() == NVVM::Tcgen05LdStShape::SHAPE_16X32BX2 && !getOffset())
4520 result = emitError("shape 16x32bx2 requires offset argument");
4521
4522 auto valTy = getVal().getType();
4523 unsigned valLen = isa<VectorType>(valTy)
4524 ? llvm::cast<VectorType>(valTy).getNumElements()
4525 : 1;
4526 if (!isValidVectorLength(getShape(), valLen))
4527 result = emitError(llvm::formatv("invalid input length {0} for shape "
4528 "{1} in tcgen05.st Op",
4529 valLen, stringifyEnum(getShape())));
4530
4531 return result;
4532}
4533
4534/// Infer the result ranges for the NVVM SpecialRangeableRegisterOp that might
4535/// have ConstantRangeAttr.
4538 SetIntRangeFn setResultRanges) {
4539 if (auto rangeAttr = op->getAttrOfType<LLVM::ConstantRangeAttr>("range")) {
4540 setResultRanges(result, {rangeAttr.getLower(), rangeAttr.getUpper(),
4541 rangeAttr.getLower(), rangeAttr.getUpper()});
4542 }
4543}
4544
4545/// Verify the range attribute satisfies LLVM ConstantRange constructor
4546/// requirements for NVVM SpecialRangeableRegisterOp.
4547static LogicalResult
4549 std::optional<LLVM::ConstantRangeAttr> rangeAttr) {
4550 if (!rangeAttr)
4551 return success();
4552
4553 const llvm::APInt &lower = rangeAttr->getLower();
4554 const llvm::APInt &upper = rangeAttr->getUpper();
4555
4556 // Check LLVM ConstantRange constructor condition
4557 if (lower == upper && !lower.isMaxValue() && !lower.isMinValue()) {
4558 unsigned bitWidth = lower.getBitWidth();
4559 llvm::APInt minVal = llvm::APInt::getMinValue(bitWidth);
4560 llvm::APInt maxVal = llvm::APInt::getMaxValue(bitWidth);
4561 return op->emitOpError(
4562 "invalid range attribute: Lower == Upper, but they aren't min (")
4563 << llvm::toString(minVal, 10, false) << ") or max ("
4564 << llvm::toString(maxVal, 10, false)
4565 << ") value! This is an invalid constant range.";
4566 }
4567
4568 return success();
4569}
4570
4571static llvm::Value *getAsPackedI32(llvm::Value *arg,
4572 llvm::IRBuilderBase &builder) {
4573 return builder.CreateBitCast(arg,
4574 llvm::Type::getInt32Ty(builder.getContext()));
4575}
4576
4577NVVM::IDArgPair DotAccumulate4WayOp::getIntrinsicIDAndArgs(
4578 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
4579 auto curOp = cast<NVVM::DotAccumulate4WayOp>(op);
4580
4582 args.push_back(getAsPackedI32(mt.lookupValue(curOp.getA()), builder));
4583 args.push_back(getAsPackedI32(mt.lookupValue(curOp.getB()), builder));
4584 args.push_back(mt.lookupValue(curOp.getC()));
4585
4586 bool isASigned = curOp.getAType() == NVVM::DotAccumulateType::SIGNED;
4587 bool isBSigned = curOp.getBType() == NVVM::DotAccumulateType::SIGNED;
4588 unsigned type = (isASigned << 1) | isBSigned;
4589 const llvm::Intrinsic::ID ids[] = {
4590 llvm::Intrinsic::nvvm_idp4a_u_u,
4591 llvm::Intrinsic::nvvm_idp4a_u_s,
4592 llvm::Intrinsic::nvvm_idp4a_s_u,
4593 llvm::Intrinsic::nvvm_idp4a_s_s,
4594 };
4595 return {ids[type], args};
4596}
4597
4598NVVM::IDArgPair DotAccumulate2WayOp::getIntrinsicIDAndArgs(
4599 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
4600 auto curOp = cast<NVVM::DotAccumulate2WayOp>(op);
4601
4603 args.push_back(getAsPackedI32(mt.lookupValue(curOp.getA()), builder));
4604 args.push_back(getAsPackedI32(mt.lookupValue(curOp.getB()), builder));
4605 args.push_back(builder.getInt1(curOp.getBHi()));
4606 args.push_back(mt.lookupValue(curOp.getC()));
4607
4608 bool isASigned = curOp.getAType() == NVVM::DotAccumulateType::SIGNED;
4609 bool isBSigned = curOp.getBType() == NVVM::DotAccumulateType::SIGNED;
4610 unsigned type = (isASigned << 1) | isBSigned;
4611 const llvm::Intrinsic::ID ids[] = {
4612 llvm::Intrinsic::nvvm_idp2a_u_u,
4613 llvm::Intrinsic::nvvm_idp2a_u_s,
4614 llvm::Intrinsic::nvvm_idp2a_s_u,
4615 llvm::Intrinsic::nvvm_idp2a_s_s,
4616 };
4617 return {ids[type], args};
4618}
4619
4620static llvm::Value *getParamCastedAddr(llvm::Value *addr,
4621 llvm::IRBuilderBase &builder) {
4622 return builder.CreateAddrSpaceCast(
4623 addr,
4624 llvm::PointerType::get(builder.getContext(),
4625 llvm::NVPTXAS::AddressSpace::ADDRESS_SPACE_PARAM));
4626}
4627
4629PrefetchOp::getIntrinsicIDAndArgs(NVVM::PrefetchOp &op,
4631 llvm::IRBuilderBase &builder) {
4632 using MemSpace = NVVM::NVVMMemorySpace;
4633 using CacheLevel = NVVM::PrefetchCacheLevel;
4634
4635 std::optional<NVVM::PrefetchCacheLevel> cacheLevel = op.getCacheLevel();
4636 std::optional<NVVM::CacheEvictionPriority> evictPriority =
4637 op.getEvictPriority();
4638 unsigned addressSpace =
4639 llvm::cast<LLVM::LLVMPointerType>(op.getAddr().getType())
4640 .getAddressSpace();
4641
4643 llvm::Value *addr = mt.lookupValue(op.getAddr());
4644 args.push_back(op.getInParamSpace() ? getParamCastedAddr(addr, builder)
4645 : addr);
4646
4647 if (op.getTensormap())
4648 return {llvm::Intrinsic::nvvm_prefetch_tensormap, args};
4649
4650 assert(cacheLevel && "expected cache level for non-tensormap prefetch");
4651
4652 if (op.getUniform() && *cacheLevel == CacheLevel::L1)
4653 return {llvm::Intrinsic::nvvm_prefetchu_L1, args};
4654
4655 if (evictPriority && *cacheLevel == CacheLevel::L2) {
4656 switch (*evictPriority) {
4657 case NVVM::CacheEvictionPriority::EvictLast:
4658 return {llvm::Intrinsic::nvvm_prefetch_global_L2_evict_last, args};
4659 case NVVM::CacheEvictionPriority::EvictNormal:
4660 return {llvm::Intrinsic::nvvm_prefetch_global_L2_evict_normal, args};
4661 default:
4662 llvm_unreachable("Invalid cache eviction priority");
4663 }
4664 }
4665
4666 switch (static_cast<MemSpace>(addressSpace)) {
4667 case MemSpace::Generic:
4668 return *cacheLevel == CacheLevel::L1
4669 ? NVVM::IDArgPair({llvm::Intrinsic::nvvm_prefetch_L1, args})
4670 : NVVM::IDArgPair({llvm::Intrinsic::nvvm_prefetch_L2, args});
4671 case MemSpace::Global:
4672 return *cacheLevel == CacheLevel::L1
4674 {llvm::Intrinsic::nvvm_prefetch_global_L1, args})
4675 : NVVM::IDArgPair(
4676 {llvm::Intrinsic::nvvm_prefetch_global_L2, args});
4677 case MemSpace::Local:
4678 return *cacheLevel == CacheLevel::L1
4680 {llvm::Intrinsic::nvvm_prefetch_local_L1, args})
4681 : NVVM::IDArgPair(
4682 {llvm::Intrinsic::nvvm_prefetch_local_L2, args});
4683 default:
4684 llvm_unreachable("Invalid pointer address space");
4685 }
4686}
4687
4688bool NVVM::InlinePtxOp::getAsmValues(
4689 RewriterBase &rewriter,
4690 llvm::SmallVectorImpl<std::pair<mlir::Value, mlir::NVVM::PTXRegisterMod>>
4691 &asmValues) {
4692 for (auto arg : getReadWriteArgs())
4693 asmValues.push_back({arg, mlir::NVVM::PTXRegisterMod::ReadWrite});
4694 for (auto arg : getResults())
4695 asmValues.push_back({arg, mlir::NVVM::PTXRegisterMod::Write});
4696 for (auto arg : getReadOnlyArgs())
4697 asmValues.push_back({arg, mlir::NVVM::PTXRegisterMod::Read});
4698 if (getPredicate())
4699 asmValues.push_back({getPredicate(), mlir::NVVM::PTXRegisterMod::Read});
4700 return false; // No manual mapping needed
4701}
4702
4703NVVM::IDArgPair ClusterLaunchControlTryCancelOp::getIntrinsicIDAndArgs(
4704 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
4705 auto curOp = cast<NVVM::ClusterLaunchControlTryCancelOp>(op);
4707 args.push_back(mt.lookupValue(curOp.getSmemAddress()));
4708 args.push_back(mt.lookupValue(curOp.getMbarrier()));
4709
4710 llvm::Intrinsic::ID intrinsicID =
4711 curOp.getMulticast()
4712 ? llvm::Intrinsic::
4713 nvvm_clusterlaunchcontrol_try_cancel_async_multicast_shared
4714 : llvm::Intrinsic::nvvm_clusterlaunchcontrol_try_cancel_async_shared;
4715
4716 return {intrinsicID, args};
4717}
4718
4719NVVM::IDArgPair ClusterLaunchControlQueryCancelOp::getIntrinsicIDAndArgs(
4720 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
4721 auto curOp = cast<NVVM::ClusterLaunchControlQueryCancelOp>(op);
4723 args.push_back(mt.lookupValue(curOp.getTryCancelResponse()));
4724
4725 llvm::Intrinsic::ID intrinsicID;
4726
4727 switch (curOp.getQueryType()) {
4728 case NVVM::ClusterLaunchControlQueryType::IS_CANCELED:
4729 intrinsicID =
4730 llvm::Intrinsic::nvvm_clusterlaunchcontrol_query_cancel_is_canceled;
4731 break;
4732 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_X:
4733 intrinsicID = llvm::Intrinsic::
4734 nvvm_clusterlaunchcontrol_query_cancel_get_first_ctaid_x;
4735 break;
4736 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_Y:
4737 intrinsicID = llvm::Intrinsic::
4738 nvvm_clusterlaunchcontrol_query_cancel_get_first_ctaid_y;
4739 break;
4740 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_Z:
4741 intrinsicID = llvm::Intrinsic::
4742 nvvm_clusterlaunchcontrol_query_cancel_get_first_ctaid_z;
4743 break;
4744 }
4745 return {intrinsicID, args};
4746}
4747
4749PermuteOp::getIntrinsicIDAndArgs(Operation &op, LLVM::ModuleTranslation &mt,
4750 llvm::IRBuilderBase &builder) {
4751 auto thisOp = cast<NVVM::PermuteOp>(op);
4752 NVVM::PermuteMode mode = thisOp.getMode();
4753
4754 static constexpr llvm::Intrinsic::ID IDs[] = {
4755 llvm::Intrinsic::nvvm_prmt, llvm::Intrinsic::nvvm_prmt_f4e,
4756 llvm::Intrinsic::nvvm_prmt_b4e, llvm::Intrinsic::nvvm_prmt_rc8,
4757 llvm::Intrinsic::nvvm_prmt_ecl, llvm::Intrinsic::nvvm_prmt_ecr,
4758 llvm::Intrinsic::nvvm_prmt_rc16};
4759
4760 unsigned modeIndex = static_cast<unsigned>(mode);
4762 args.push_back(mt.lookupValue(thisOp.getLo()));
4763
4764 // Only first 3 modes (Default, f4e, b4e) need the hi operand.
4765 if (modeIndex < 3)
4766 args.push_back(mt.lookupValue(thisOp.getHi()));
4767
4768 args.push_back(mt.lookupValue(thisOp.getSelector()));
4769
4770 return {IDs[modeIndex], args};
4771}
4772
4773//===----------------------------------------------------------------------===//
4774// NVVM tcgen05.mma functions
4775//===----------------------------------------------------------------------===//
4776
4778Tcgen05MMAOp::getIntrinsicIDAndArgs(Operation &op, LLVM::ModuleTranslation &mt,
4779 llvm::IRBuilderBase &builder) {
4780
4781 auto thisOp = cast<NVVM::Tcgen05MMAOp>(op);
4783
4784 args.push_back(mt.lookupValue(thisOp.getMatrixD()));
4785
4786 llvm::Value *A = mt.lookupValue(thisOp.getMatrixA());
4787 const bool isATensor = isa<llvm::PointerType>(A->getType());
4788 args.push_back(A);
4789
4790 args.push_back(mt.lookupValue(thisOp.getMatrixB()));
4791 args.push_back(mt.lookupValue(thisOp.getIdesc()));
4792 args.push_back(mt.lookupValue(thisOp.getEnableInputD()));
4793
4794 using EnableAShiftArray = std::array<llvm::Intrinsic::ID, 2>;
4795 using CtaGroupArray = std::array<EnableAShiftArray, 2>;
4796 using IsATensorArray = std::array<CtaGroupArray, 2>;
4797 using HasScaleInputDArray = std::array<IsATensorArray, 2>;
4798 using HasDisableOutputLaneArray = std::array<HasScaleInputDArray, 2>;
4799
4800 // [hasDisableOutputLane][hasScaleInputD][isATensor][CtaGroup][EnableAShift]
4801 static constexpr HasDisableOutputLaneArray tcgen05MMAIDs = {
4802 { // without diable output lane
4803 {{// without scale input D
4804 {{
4805 // shared
4806 {{// cg1
4807 {llvm::Intrinsic::nvvm_tcgen05_mma_shared, notIntrinsic},
4808 // cg2
4809 {llvm::Intrinsic::nvvm_tcgen05_mma_shared, notIntrinsic}}},
4810 {{// tensor
4811 {
4812 // cg1
4813 llvm::Intrinsic::nvvm_tcgen05_mma_tensor,
4814 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_ashift,
4815 },
4816 {
4817 // cg2
4818 llvm::Intrinsic::nvvm_tcgen05_mma_tensor,
4819 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_ashift,
4820 }}},
4821 }},
4822 // with scale input D
4823 {{ // shared
4824 {{// cg1
4825 {llvm::Intrinsic::nvvm_tcgen05_mma_shared_scale_d, notIntrinsic},
4826 // cg2
4827 {llvm::Intrinsic::nvvm_tcgen05_mma_shared_scale_d, notIntrinsic}}},
4828 {{// tensor
4829 {
4830 // cg1
4831 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_scale_d,
4832 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_scale_d_ashift,
4833 },
4834 {
4835 // cg2
4836 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_scale_d,
4837 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_scale_d_ashift,
4838 }}}}}}},
4839 // with disable output lane
4840 {{ // without scale input D
4841 {{ // shared
4842 {{// cg1
4843 {llvm::Intrinsic::nvvm_tcgen05_mma_shared_disable_output_lane_cg1,
4844 notIntrinsic},
4845 // cg2
4846 {llvm::Intrinsic::nvvm_tcgen05_mma_shared_disable_output_lane_cg2,
4847 notIntrinsic}}},
4848 {{// cg1
4849 {
4850 llvm::Intrinsic::
4851 nvvm_tcgen05_mma_tensor_disable_output_lane_cg1,
4852 llvm::Intrinsic::
4853 nvvm_tcgen05_mma_tensor_disable_output_lane_cg1_ashift,
4854 },
4855 // cg2
4856 {
4857 llvm::Intrinsic::
4858 nvvm_tcgen05_mma_tensor_disable_output_lane_cg2,
4859 llvm::Intrinsic::
4860 nvvm_tcgen05_mma_tensor_disable_output_lane_cg2_ashift,
4861 }}}}},
4862 // with scale input D
4863 {{ // shared
4864 {{// cg1
4865 {llvm::Intrinsic::
4866 nvvm_tcgen05_mma_shared_scale_d_disable_output_lane_cg1,
4867 notIntrinsic},
4868 // cg2
4869 {llvm::Intrinsic::
4870 nvvm_tcgen05_mma_shared_scale_d_disable_output_lane_cg2,
4871 notIntrinsic}}},
4872 // tensor
4873 {{// cg1
4874 {llvm::Intrinsic::
4875 nvvm_tcgen05_mma_tensor_scale_d_disable_output_lane_cg1,
4876 llvm::Intrinsic::
4877 nvvm_tcgen05_mma_tensor_scale_d_disable_output_lane_cg1_ashift},
4878 // cg2
4879 {
4880 llvm::Intrinsic::
4881 nvvm_tcgen05_mma_tensor_scale_d_disable_output_lane_cg2,
4882 llvm::Intrinsic::
4883 nvvm_tcgen05_mma_tensor_scale_d_disable_output_lane_cg2_ashift,
4884 }}}}}}}}};
4885
4886 llvm::Value *ScaleInputD = mt.lookupValue(thisOp.getScaleInputD());
4887 bool hasScaleInputD = ScaleInputD != nullptr;
4888
4889 llvm::Value *DisableOutputLane =
4890 mt.lookupValue(thisOp.getDisableOutputLane());
4891 bool hasDisableOutputLane = DisableOutputLane != nullptr;
4892
4893 const unsigned ctaGroup =
4894 static_cast<unsigned>(getNVVMCtaGroupKind(thisOp.getCtaGroup()));
4895
4896 llvm::Intrinsic::ID ID =
4897 tcgen05MMAIDs[hasDisableOutputLane][hasScaleInputD][isATensor]
4898 [ctaGroup - 1][thisOp.getAShift()];
4899
4900 assert(ID != notIntrinsic && "Invalid intrinsic for Tcgen05MMAOp.");
4901
4902 if (hasScaleInputD)
4903 args.push_back(ScaleInputD);
4904
4905 if (hasDisableOutputLane)
4906 args.push_back(DisableOutputLane);
4907
4908 args.push_back(builder.getInt32(static_cast<unsigned>(thisOp.getKind())));
4909
4910 if (!hasDisableOutputLane)
4911 args.push_back(builder.getInt32(ctaGroup));
4912
4913 args.push_back(
4914 builder.getInt32(static_cast<unsigned>(thisOp.getCollectorOp())));
4915
4916 return {ID, args};
4917}
4918
4919static LogicalResult
4920verifyTcgen05MMAOp(bool isATensor, mlir::Value disableOutputLane,
4921 NVVM::CTAGroupKind ctaGroup, bool hasAShift,
4922 NVVM::Tcgen05MMACollectorOp collectorOp, Location loc) {
4923
4924 if (disableOutputLane) {
4925 mlir::VectorType disableOutputLaneType =
4926 cast<mlir::VectorType>(disableOutputLane.getType());
4927 if ((ctaGroup == NVVM::CTAGroupKind::CTA_1 &&
4928 disableOutputLaneType.getNumElements() != 4) ||
4929 (ctaGroup == NVVM::CTAGroupKind::CTA_2 &&
4930 disableOutputLaneType.getNumElements() != 8))
4931 return emitError(loc) << "Disable Output Lane of length "
4932 << disableOutputLaneType.getNumElements()
4933 << " is incompatible with CtaGroupAttr";
4934 }
4935
4936 if (hasAShift && !isATensor)
4937 return emitError(
4938 loc, "A-shift can be applied only when matrix A is in tensor memory");
4939
4940 if (hasAShift == true && (collectorOp == Tcgen05MMACollectorOp::FILL ||
4941 collectorOp == Tcgen05MMACollectorOp::USE))
4942 return emitError(
4943 loc, "Cannot use collector buffer operation fill or use with ashift");
4944
4945 return success();
4946}
4947
4948LogicalResult Tcgen05MMAOp::verify() {
4949 return verifyTcgen05MMAOp(isa<LLVM::LLVMPointerType>(getMatrixA().getType()),
4950 getDisableOutputLane(), getCtaGroup(), getAShift(),
4951 getCollectorOp(), getLoc());
4952}
4953
4954//===----------------------------------------------------------------------===//
4955// NVVM tcgen05.mma.sp functions
4956//===----------------------------------------------------------------------===//
4957
4958mlir::NVVM::IDArgPair Tcgen05MMASparseOp::getIntrinsicIDAndArgs(
4959 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
4960
4961 auto thisOp = cast<NVVM::Tcgen05MMASparseOp>(op);
4963
4964 args.push_back(mt.lookupValue(thisOp.getMatrixD()));
4965
4966 llvm::Value *A = mt.lookupValue(thisOp.getMatrixA());
4967 bool isATensor = isa<llvm::PointerType>(A->getType());
4968 args.push_back(A);
4969
4970 args.push_back(mt.lookupValue(thisOp.getMatrixB()));
4971 args.push_back(mt.lookupValue(thisOp.getIdesc()));
4972 args.push_back(mt.lookupValue(thisOp.getEnableInputD()));
4973 args.push_back(mt.lookupValue(thisOp.getSparseMetadata()));
4974
4975 using EnableAShiftArray = std::array<llvm::Intrinsic::ID, 2>;
4976 using CtaGroupArray = std::array<EnableAShiftArray, 2>;
4977 using IsATensorArray = std::array<CtaGroupArray, 2>;
4978 using HasScaleInputDArray = std::array<IsATensorArray, 2>;
4979 using HasDisableOutputLaneArray = std::array<HasScaleInputDArray, 2>;
4980
4981 // [hasDisableOutputLane][hasScaleInputD][isATensor][CtaGroup][EnableAShift]
4982 static constexpr HasDisableOutputLaneArray tcgen05MMASparseIDs = {
4983 { // without diable output lane
4984 {{// without scale input D
4985 {{
4986 // shared
4987 {{// cg1
4988 {llvm::Intrinsic::nvvm_tcgen05_mma_sp_shared, notIntrinsic},
4989 // cg2
4990 {llvm::Intrinsic::nvvm_tcgen05_mma_sp_shared, notIntrinsic}}},
4991 {{// tensor
4992 {
4993 // cg1
4994 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor,
4995 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_ashift,
4996 },
4997 {
4998 // cg2
4999 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor,
5000 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_ashift,
5001 }}},
5002 }},
5003 // with scale input D
5004 {{ // shared
5005 {{// cg1
5006 {llvm::Intrinsic::nvvm_tcgen05_mma_sp_shared_scale_d,
5007 notIntrinsic},
5008 // cg2
5009 {llvm::Intrinsic::nvvm_tcgen05_mma_sp_shared_scale_d,
5010 notIntrinsic}}},
5011 {{// tensor
5012 {
5013 // cg1
5014 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_scale_d,
5015 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_scale_d_ashift,
5016 },
5017 {
5018 // cg2
5019 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_scale_d,
5020 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_scale_d_ashift,
5021 }}}}}}},
5022 // with disable output lane
5023 {{ // without scale input D
5024 {{ // shared
5025 {{// cg1
5026 {llvm::Intrinsic::
5027 nvvm_tcgen05_mma_sp_shared_disable_output_lane_cg1,
5028 notIntrinsic},
5029 // cg2
5030 {llvm::Intrinsic::
5031 nvvm_tcgen05_mma_sp_shared_disable_output_lane_cg2,
5032 notIntrinsic}}},
5033 {{// cg1
5034 {
5035 llvm::Intrinsic::
5036 nvvm_tcgen05_mma_sp_tensor_disable_output_lane_cg1,
5037 llvm::Intrinsic::
5038 nvvm_tcgen05_mma_sp_tensor_disable_output_lane_cg1_ashift,
5039 },
5040 // cg2
5041 {
5042 llvm::Intrinsic::
5043 nvvm_tcgen05_mma_sp_tensor_disable_output_lane_cg2,
5044 llvm::Intrinsic::
5045 nvvm_tcgen05_mma_sp_tensor_disable_output_lane_cg2_ashift,
5046 }}}}},
5047 // with scale input D
5048 {{ // shared
5049 {{// cg1
5050 {llvm::Intrinsic::
5051 nvvm_tcgen05_mma_sp_shared_scale_d_disable_output_lane_cg1,
5052 notIntrinsic},
5053 // cg2
5054 {llvm::Intrinsic::
5055 nvvm_tcgen05_mma_sp_shared_scale_d_disable_output_lane_cg2,
5056 notIntrinsic}}},
5057 // tensor
5058 {{// cg1
5059 {llvm::Intrinsic::
5060 nvvm_tcgen05_mma_sp_tensor_scale_d_disable_output_lane_cg1,
5061 llvm::Intrinsic::
5062 nvvm_tcgen05_mma_sp_tensor_scale_d_disable_output_lane_cg1_ashift},
5063 // cg2
5064 {
5065 llvm::Intrinsic::
5066 nvvm_tcgen05_mma_sp_tensor_scale_d_disable_output_lane_cg2,
5067 llvm::Intrinsic::
5068 nvvm_tcgen05_mma_sp_tensor_scale_d_disable_output_lane_cg2_ashift,
5069 }}}}}}}}};
5070
5071 llvm::Value *ScaleInputD = mt.lookupValue(thisOp.getScaleInputD());
5072 bool hasScaleInputD = ScaleInputD != nullptr;
5073
5074 llvm::Value *DisableOutputLane =
5075 mt.lookupValue(thisOp.getDisableOutputLane());
5076 bool hasDisableOutputLane = DisableOutputLane != nullptr;
5077
5078 unsigned ctaGroup =
5079 static_cast<unsigned>(getNVVMCtaGroupKind(thisOp.getCtaGroup()));
5080
5081 llvm::Intrinsic::ID ID =
5082 tcgen05MMASparseIDs[hasDisableOutputLane][hasScaleInputD][isATensor]
5083 [ctaGroup - 1][thisOp.getAShift()];
5084
5085 assert(ID != notIntrinsic && "Invalid intrinsic for Tcgen05MMASparseOp.");
5086
5087 if (hasScaleInputD)
5088 args.push_back(ScaleInputD);
5089
5090 if (hasDisableOutputLane)
5091 args.push_back(DisableOutputLane);
5092
5093 args.push_back(builder.getInt32(static_cast<unsigned>(thisOp.getKind())));
5094
5095 if (!hasDisableOutputLane)
5096 args.push_back(builder.getInt32(ctaGroup));
5097
5098 args.push_back(
5099 builder.getInt32(static_cast<unsigned>(thisOp.getCollectorOp())));
5100
5101 return {ID, args};
5102}
5103
5104LogicalResult Tcgen05MMASparseOp::verify() {
5105 return verifyTcgen05MMAOp(isa<LLVM::LLVMPointerType>(getMatrixA().getType()),
5106 getDisableOutputLane(), getCtaGroup(), getAShift(),
5107 getCollectorOp(), getLoc());
5108}
5109
5110//===----------------------------------------------------------------------===//
5111// NVVM tcgen05.mma.block_scale functions
5112//===----------------------------------------------------------------------===//
5113
5114mlir::NVVM::IDArgPair Tcgen05MMABlockScaleOp::getIntrinsicIDAndArgs(
5115 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
5116
5117 auto thisOp = cast<NVVM::Tcgen05MMABlockScaleOp>(op);
5119
5120 args.push_back(mt.lookupValue(thisOp.getMatrixD()));
5121
5122 llvm::Value *A = mt.lookupValue(thisOp.getMatrixA());
5123 bool isATensor = isa<llvm::PointerType>(A->getType());
5124 args.push_back(A);
5125
5126 args.push_back(mt.lookupValue(thisOp.getMatrixB()));
5127 args.push_back(mt.lookupValue(thisOp.getIdesc()));
5128 args.push_back(mt.lookupValue(thisOp.getEnableInputD()));
5129 args.push_back(mt.lookupValue(thisOp.getScaleA()));
5130 args.push_back(mt.lookupValue(thisOp.getScaleB()));
5131 args.push_back(builder.getInt32(
5132 static_cast<unsigned>(getNVVMCtaGroupKind(thisOp.getCtaGroup()))));
5133 args.push_back(
5134 builder.getInt32(static_cast<unsigned>(thisOp.getCollectorOp())));
5135
5136 auto kind = thisOp.getKind();
5137 auto blockScale = thisOp.getBlockScale();
5138 llvm::Intrinsic::ID ID = [&]() {
5139 if (kind == NVVM::MMABlockScaleKind::MXF8F6F4) {
5140 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT) {
5141 return isATensor ? llvm::Intrinsic::
5142 nvvm_tcgen05_mma_tensor_mxf8f6f4_block_scale
5143 : llvm::Intrinsic::
5144 nvvm_tcgen05_mma_shared_mxf8f6f4_block_scale;
5145 } else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5146 return isATensor
5147 ? llvm::Intrinsic::
5148 nvvm_tcgen05_mma_tensor_mxf8f6f4_block_scale_block32
5149 : llvm::Intrinsic::
5150 nvvm_tcgen05_mma_shared_mxf8f6f4_block_scale_block32;
5151 }
5152 } else if (kind == NVVM::MMABlockScaleKind::MXF4) {
5153 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT) {
5154 return isATensor
5155 ? llvm::Intrinsic::nvvm_tcgen05_mma_tensor_mxf4_block_scale
5156 : llvm::Intrinsic::nvvm_tcgen05_mma_shared_mxf4_block_scale;
5157 } else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5158 return isATensor ? llvm::Intrinsic::
5159 nvvm_tcgen05_mma_tensor_mxf4_block_scale_block32
5160 : llvm::Intrinsic::
5161 nvvm_tcgen05_mma_shared_mxf4_block_scale_block32;
5162 }
5163 } else if (kind == NVVM::MMABlockScaleKind::MXF4NVF4) {
5164 if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5165 return isATensor
5166 ? llvm::Intrinsic::
5167 nvvm_tcgen05_mma_tensor_mxf4nvf4_block_scale_block32
5168 : llvm::Intrinsic::
5169 nvvm_tcgen05_mma_shared_mxf4nvf4_block_scale_block32;
5170
5171 } else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK16) {
5172 return isATensor
5173 ? llvm::Intrinsic::
5174 nvvm_tcgen05_mma_tensor_mxf4nvf4_block_scale_block16
5175 : llvm::Intrinsic::
5176 nvvm_tcgen05_mma_shared_mxf4nvf4_block_scale_block16;
5177 }
5178 }
5179 llvm_unreachable("Invalid tcgen05.mma.block_scale attributes");
5180 }();
5181
5182 return {ID, args};
5183}
5184
5185static LogicalResult verifyTcgen05MMABlockScaleOp(
5186 NVVM::Tcgen05MMACollectorOp collectorOp, NVVM::MMABlockScaleKind kind,
5187 NVVM::Tcgen05MMABlockScale blockScale, Location loc) {
5188
5189 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT &&
5190 kind == MMABlockScaleKind::MXF4NVF4)
5191 return emitError(loc, "mxf4nvf4 requires block scale attribute");
5192
5193 if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK16 &&
5194 kind != MMABlockScaleKind::MXF4NVF4)
5195 return emitError(loc,
5196 llvm::formatv("{} kind does not support block16 attribute",
5197 stringifyEnum(kind)));
5198
5199 return success();
5200}
5201
5202LogicalResult Tcgen05MMABlockScaleOp::verify() {
5203 return verifyTcgen05MMABlockScaleOp(getCollectorOp(), getKind(),
5204 getBlockScale(), getLoc());
5205}
5206
5207//===----------------------------------------------------------------------===//
5208// NVVM tcgen05.mma.sp.block_scale functions
5209//===----------------------------------------------------------------------===//
5210
5211mlir::NVVM::IDArgPair Tcgen05MMASparseBlockScaleOp::getIntrinsicIDAndArgs(
5212 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
5213
5214 auto thisOp = cast<NVVM::Tcgen05MMASparseBlockScaleOp>(op);
5216
5217 args.push_back(mt.lookupValue(thisOp.getMatrixD()));
5218
5219 llvm::Value *A = mt.lookupValue(thisOp.getMatrixA());
5220 bool isATensor = isa<llvm::PointerType>(A->getType());
5221 args.push_back(A);
5222
5223 args.push_back(mt.lookupValue(thisOp.getMatrixB()));
5224 args.push_back(mt.lookupValue(thisOp.getIdesc()));
5225 args.push_back(mt.lookupValue(thisOp.getEnableInputD()));
5226 args.push_back(mt.lookupValue(thisOp.getSparseMetadata()));
5227 args.push_back(mt.lookupValue(thisOp.getScaleA()));
5228 args.push_back(mt.lookupValue(thisOp.getScaleB()));
5229 args.push_back(builder.getInt32(
5230 static_cast<unsigned>(getNVVMCtaGroupKind(thisOp.getCtaGroup()))));
5231 args.push_back(
5232 builder.getInt32(static_cast<unsigned>(thisOp.getCollectorOp())));
5233
5234 auto kind = thisOp.getKind();
5235 auto blockScale = thisOp.getBlockScale();
5236 llvm::Intrinsic::ID ID = [&]() {
5237 if (kind == NVVM::MMABlockScaleKind::MXF8F6F4) {
5238 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT) {
5239 return isATensor ? llvm::Intrinsic::
5240 nvvm_tcgen05_mma_sp_tensor_mxf8f6f4_block_scale
5241 : llvm::Intrinsic::
5242 nvvm_tcgen05_mma_sp_shared_mxf8f6f4_block_scale;
5243 } else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5244 return isATensor
5245 ? llvm::Intrinsic::
5246 nvvm_tcgen05_mma_sp_tensor_mxf8f6f4_block_scale_block32
5247 : llvm::Intrinsic::
5248 nvvm_tcgen05_mma_sp_shared_mxf8f6f4_block_scale_block32;
5249 }
5250 } else if (kind == NVVM::MMABlockScaleKind::MXF4) {
5251 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT) {
5252 return isATensor ? llvm::Intrinsic::
5253 nvvm_tcgen05_mma_sp_tensor_mxf4_block_scale
5254 : llvm::Intrinsic::
5255 nvvm_tcgen05_mma_sp_shared_mxf4_block_scale;
5256 } else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5257 return isATensor
5258 ? llvm::Intrinsic::
5259 nvvm_tcgen05_mma_sp_tensor_mxf4_block_scale_block32
5260 : llvm::Intrinsic::
5261 nvvm_tcgen05_mma_sp_shared_mxf4_block_scale_block32;
5262 }
5263 } else if (kind == NVVM::MMABlockScaleKind::MXF4NVF4) {
5264 if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5265 return isATensor
5266 ? llvm::Intrinsic::
5267 nvvm_tcgen05_mma_sp_tensor_mxf4nvf4_block_scale_block32
5268 : llvm::Intrinsic::
5269 nvvm_tcgen05_mma_sp_shared_mxf4nvf4_block_scale_block32;
5270
5271 } else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK16) {
5272 return isATensor
5273 ? llvm::Intrinsic::
5274 nvvm_tcgen05_mma_sp_tensor_mxf4nvf4_block_scale_block16
5275 : llvm::Intrinsic::
5276 nvvm_tcgen05_mma_sp_shared_mxf4nvf4_block_scale_block16;
5277 }
5278 }
5279 llvm_unreachable("Invalid tcgen05.mma.sp.block_scale attributes");
5280 }();
5281
5282 return {ID, args};
5283}
5284
5285LogicalResult Tcgen05MMASparseBlockScaleOp::verify() {
5286 return verifyTcgen05MMABlockScaleOp(getCollectorOp(), getKind(),
5287 getBlockScale(), getLoc());
5288}
5289
5290//===----------------------------------------------------------------------===//
5291// NVVM tcgen05.mma.ws functions
5292//===----------------------------------------------------------------------===//
5293
5294mlir::NVVM::IDArgPair Tcgen05MMAWsOp::getIntrinsicIDAndArgs(
5295 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
5296
5297 auto thisOp = cast<NVVM::Tcgen05MMAWsOp>(op);
5299
5300 args.push_back(mt.lookupValue(thisOp.getMatrixD()));
5301
5302 llvm::Value *A = mt.lookupValue(thisOp.getMatrixA());
5303 bool isATensor = isa<llvm::PointerType>(A->getType());
5304 args.push_back(A);
5305
5306 args.push_back(mt.lookupValue(thisOp.getMatrixB()));
5307 args.push_back(mt.lookupValue(thisOp.getIdesc()));
5308 args.push_back(mt.lookupValue(thisOp.getEnableInputD()));
5309
5310 mlir::Value ZeroColMask = thisOp.getZeroColMask();
5311 llvm::Intrinsic::ID ID = notIntrinsic;
5312 if (ZeroColMask) {
5313 args.push_back(mt.lookupValue(ZeroColMask));
5314 ID = isATensor ? llvm::Intrinsic::nvvm_tcgen05_mma_ws_tensor_zero_col_mask
5315 : llvm::Intrinsic::nvvm_tcgen05_mma_ws_shared_zero_col_mask;
5316 } else
5317 ID = isATensor ? llvm::Intrinsic::nvvm_tcgen05_mma_ws_tensor
5318 : llvm::Intrinsic::nvvm_tcgen05_mma_ws_shared;
5319
5320 args.push_back(builder.getInt32(static_cast<unsigned>(thisOp.getKind())));
5321 args.push_back(
5322 builder.getInt32(static_cast<unsigned>(thisOp.getCollectorBBuffer())));
5323 args.push_back(
5324 builder.getInt32(static_cast<unsigned>(thisOp.getCollectorOp())));
5325
5326 return {ID, args};
5327}
5328
5329//===----------------------------------------------------------------------===//
5330// NVVM tcgen05.mma.ws.sp functions
5331//===----------------------------------------------------------------------===//
5332
5333mlir::NVVM::IDArgPair Tcgen05MMAWsSparseOp::getIntrinsicIDAndArgs(
5334 Operation &op, LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder) {
5335
5336 auto thisOp = cast<NVVM::Tcgen05MMAWsSparseOp>(op);
5338
5339 args.push_back(mt.lookupValue(thisOp.getMatrixD()));
5340
5341 llvm::Value *A = mt.lookupValue(thisOp.getMatrixA());
5342 bool isATensor = isa<llvm::PointerType>(A->getType());
5343 args.push_back(A);
5344
5345 args.push_back(mt.lookupValue(thisOp.getMatrixB()));
5346 args.push_back(mt.lookupValue(thisOp.getIdesc()));
5347 args.push_back(mt.lookupValue(thisOp.getEnableInputD()));
5348 args.push_back(mt.lookupValue(thisOp.getSparseMetadata()));
5349
5350 mlir::Value ZeroColMask = thisOp.getZeroColMask();
5351 llvm::Intrinsic::ID ID = notIntrinsic;
5352 if (ZeroColMask) {
5353 args.push_back(mt.lookupValue(ZeroColMask));
5354 ID = isATensor
5355 ? llvm::Intrinsic::nvvm_tcgen05_mma_ws_sp_tensor_zero_col_mask
5356 : llvm::Intrinsic::nvvm_tcgen05_mma_ws_sp_shared_zero_col_mask;
5357 } else
5358 ID = isATensor ? llvm::Intrinsic::nvvm_tcgen05_mma_ws_sp_tensor
5359 : llvm::Intrinsic::nvvm_tcgen05_mma_ws_sp_shared;
5360
5361 args.push_back(builder.getInt32(static_cast<unsigned>(thisOp.getKind())));
5362 args.push_back(
5363 builder.getInt32(static_cast<unsigned>(thisOp.getCollectorBBuffer())));
5364 args.push_back(
5365 builder.getInt32(static_cast<unsigned>(thisOp.getCollectorOp())));
5366
5367 return {ID, args};
5368}
5369
5370//===----------------------------------------------------------------------===//
5371// NVVMDialect initialization, type parsing, and registration.
5372//===----------------------------------------------------------------------===//
5373
5374// TODO: This should be the llvm.nvvm dialect once this is supported.
5375void NVVMDialect::initialize() {
5376 addOperations<
5377#define GET_OP_LIST
5378#include "mlir/Dialect/LLVMIR/NVVMOps.cpp.inc"
5379 >();
5380 addAttributes<
5381#define GET_ATTRDEF_LIST
5382#include "mlir/Dialect/LLVMIR/NVVMOpsAttributes.cpp.inc"
5383 >();
5384
5385 // Support unknown operations because not all NVVM operations are
5386 // registered.
5387 allowUnknownOperations();
5388 declarePromisedInterface<ConvertToLLVMPatternInterface, NVVMDialect>();
5389 declarePromisedInterface<gpu::TargetAttrInterface, NVVMTargetAttr>();
5390}
5391
5392LogicalResult NVVMDialect::verifyOperationAttribute(Operation *op,
5393 NamedAttribute attr) {
5394 StringAttr attrName = attr.getName();
5395 // Kernel function attribute should be attached to functions.
5396 if (attrName == NVVMDialect::getKernelFuncAttrName()) {
5397 if (!isa<LLVM::LLVMFuncOp>(op)) {
5398 return op->emitError() << "'" << NVVMDialect::getKernelFuncAttrName()
5399 << "' attribute attached to unexpected op";
5400 }
5401 }
5402 // If maxntid / reqntid / cluster_dim exist, it must be an array with max 3
5403 // dim
5404 if (attrName == NVVMDialect::getMaxntidAttrName() ||
5405 attrName == NVVMDialect::getReqntidAttrName() ||
5406 attrName == NVVMDialect::getClusterDimAttrName()) {
5407 auto values = llvm::dyn_cast<DenseI32ArrayAttr>(attr.getValue());
5408 if (!values || values.empty() || values.size() > 3) {
5409 return op->emitError()
5410 << "'" << attrName
5411 << "' attribute must be integer array with maximum 3 index";
5412 }
5413 }
5414 // If minctasm / maxnreg / cluster_max_blocks exist, it must be an integer
5415 // attribute
5416 if (attrName == NVVMDialect::getMinctasmAttrName() ||
5417 attrName == NVVMDialect::getMaxnregAttrName() ||
5418 attrName == NVVMDialect::getClusterMaxBlocksAttrName()) {
5419 if (!llvm::dyn_cast<IntegerAttr>(attr.getValue())) {
5420 return op->emitError()
5421 << "'" << attrName << "' attribute must be integer constant";
5422 }
5423 }
5424 // blocksareclusters must be used along with reqntid and cluster_dim
5425 if (attrName == NVVMDialect::getBlocksAreClustersAttrName()) {
5426 if (!op->hasAttr(NVVMDialect::getReqntidAttrName()) ||
5427 !op->hasAttr(NVVMDialect::getClusterDimAttrName())) {
5428 return op->emitError()
5429 << "'" << attrName << "' attribute must be used along with "
5430 << "'" << NVVMDialect::getReqntidAttrName() << "' and "
5431 << "'" << NVVMDialect::getClusterDimAttrName() << "'";
5432 }
5433 }
5434
5435 return success();
5436}
5437
5438LogicalResult NVVMDialect::verifyRegionArgAttribute(Operation *op,
5439 unsigned regionIndex,
5440 unsigned argIndex,
5441 NamedAttribute argAttr) {
5442 auto funcOp = dyn_cast<FunctionOpInterface>(op);
5443 if (!funcOp)
5444 return success();
5445
5446 bool isKernel = op->hasAttr(NVVMDialect::getKernelFuncAttrName());
5447 StringAttr attrName = argAttr.getName();
5448 if (attrName == NVVM::NVVMDialect::getGridConstantAttrName()) {
5449 if (!isKernel) {
5450 return op->emitError()
5451 << "'" << attrName
5452 << "' attribute must be present only on kernel arguments";
5453 }
5454 if (!isa<UnitAttr>(argAttr.getValue()))
5455 return op->emitError() << "'" << attrName << "' must be a unit attribute";
5456 if (!funcOp.getArgAttr(argIndex, LLVM::LLVMDialect::getByValAttrName())) {
5457 return op->emitError()
5458 << "'" << attrName
5459 << "' attribute requires the argument to also have attribute '"
5460 << LLVM::LLVMDialect::getByValAttrName() << "'";
5461 }
5462 }
5463
5464 return success();
5465}
5466
5467//===----------------------------------------------------------------------===//
5468// NVVM Address Space Attr
5469//===----------------------------------------------------------------------===//
5470
5471unsigned NVVMMemorySpaceAttr::getAddressSpace() const {
5472 return static_cast<unsigned>(getValue());
5473}
5474
5475bool NVVMMemorySpaceAttr::isValidLoad(
5476 Type type, ptr::AtomicOrdering ordering, std::optional<int64_t> alignment,
5477 const ::mlir::DataLayout *dataLayout,
5479 return LLVM::detail::isValidLoadStoreImpl(type, ordering, alignment,
5480 dataLayout, emitError);
5481}
5482
5483bool NVVMMemorySpaceAttr::isValidStore(
5484 Type type, ptr::AtomicOrdering ordering, std::optional<int64_t> alignment,
5485 const ::mlir::DataLayout *dataLayout,
5487 return LLVM::detail::isValidLoadStoreImpl(type, ordering, alignment,
5488 dataLayout, emitError);
5489}
5490
5491bool NVVMMemorySpaceAttr::isValidAtomicOp(
5492 ptr::AtomicBinOp op, Type type, ptr::AtomicOrdering ordering,
5493 std::optional<int64_t> alignment, const ::mlir::DataLayout *dataLayout,
5495 // TODO: update this method once `ptr.atomic_rmw` is implemented.
5496 assert(false && "unimplemented, see TODO in the source.");
5497 return false;
5498}
5499
5500bool NVVMMemorySpaceAttr::isValidAtomicXchg(
5501 Type type, ptr::AtomicOrdering successOrdering,
5502 ptr::AtomicOrdering failureOrdering, std::optional<int64_t> alignment,
5503 const ::mlir::DataLayout *dataLayout,
5505 // TODO: update this method once `ptr.atomic_cmpxchg` is implemented.
5506 assert(false && "unimplemented, see TODO in the source.");
5507 return false;
5508}
5509
5510bool NVVMMemorySpaceAttr::isValidAddrSpaceCast(
5511 Type tgt, Type src, function_ref<InFlightDiagnostic()> emitError) const {
5512 // TODO: update this method once the `ptr.addrspace_cast` op is added to the
5513 // dialect.
5514 assert(false && "unimplemented, see TODO in the source.");
5515 return false;
5516}
5517
5518bool NVVMMemorySpaceAttr::isValidPtrIntCast(
5519 Type intLikeTy, Type ptrLikeTy,
5521 // TODO: update this method once the int-cast ops are added to the `ptr`
5522 // dialect.
5523 assert(false && "unimplemented, see TODO in the source.");
5524 return false;
5525}
5526
5527//===----------------------------------------------------------------------===//
5528// NVVM target attribute.
5529//===----------------------------------------------------------------------===//
5530LogicalResult
5531NVVMTargetAttr::verify(function_ref<InFlightDiagnostic()> emitError,
5532 int optLevel, StringRef triple, StringRef chip,
5533 StringRef features, DictionaryAttr flags,
5534 ArrayAttr files, bool verifyTarget) {
5535 if (optLevel < 0 || optLevel > 3) {
5536 emitError() << "The optimization level must be a number between 0 and 3.";
5537 return failure();
5538 }
5539 if (triple.empty()) {
5540 emitError() << "The target triple cannot be empty.";
5541 return failure();
5542 }
5543 if (chip.empty()) {
5544 emitError() << "The target chip cannot be empty.";
5545 return failure();
5546 }
5547 if (files && !llvm::all_of(files, [](::mlir::Attribute attr) {
5548 return mlir::isa_and_nonnull<StringAttr>(attr);
5549 })) {
5550 emitError() << "All the elements in the `link` array must be strings.";
5551 return failure();
5552 }
5553 return success();
5554}
5555
5556LogicalResult NVVMTargetAttr::verifyTarget(Operation *gpuModule) {
5557 if (!getVerifyTarget())
5558 return success();
5559
5560 auto gpuModuleOp = llvm::dyn_cast<gpu::GPUModuleOp>(gpuModule);
5561 if (!gpuModuleOp) {
5562 return emitError(gpuModule->getLoc(),
5563 "NVVM target attribute must be attached to a GPU module");
5564 }
5565
5566 const NVVMCheckSMVersion targetSMVersion =
5568 if (!targetSMVersion.isMinimumSMVersion()) {
5569 return emitError(gpuModule->getLoc(),
5570 "Minimum NVVM target SM version is sm_20");
5571 }
5572
5573 if (gpuModuleOp
5574 ->walk([&](Operation *op) {
5575 if (auto reqOp = llvm::dyn_cast<NVVM::RequiresSMInterface>(op)) {
5576 const NVVMCheckSMVersion requirement =
5577 reqOp.getRequiredMinSMVersion();
5578 if (!requirement.isCompatibleWith(targetSMVersion)) {
5579 op->emitOpError() << "is not supported on " << getChip();
5580 return WalkResult::interrupt();
5581 }
5582 }
5583 return WalkResult::advance();
5584 })
5585 .wasInterrupted())
5586 return failure();
5587
5588 return success();
5589}
5590
5591#define GET_OP_CLASSES
5592#include "mlir/Dialect/LLVMIR/NVVMOps.cpp.inc"
5593
5594#define GET_ATTRDEF_CLASSES
5595#include "mlir/Dialect/LLVMIR/NVVMOpsAttributes.cpp.inc"
for(Operation *op :ops)
return success()
p<< " : "<< getMemRefType()<< ", "<< getType();}static LogicalResult verifyVectorMemoryOp(Operation *op, MemRefType memrefType, VectorType vectorType) { if(memrefType.getElementType() !=vectorType.getElementType()) return op-> emitOpError("requires memref and vector types of the same elemental type")
Given a list of lists of parsed operands, populates uniqueOperands with unique operands.
ArrayAttr()
b getContext())
#define GET_TCGEN05_CP_ID(shape_mc, src_fmt, is_2cta)
static LogicalResult verifyTMALoadParams(size_t tensorDims, size_t numIm2colOff, TMALoadMode mode, Location loc)
static LogicalResult verifyTcgen05MMAOp(bool isATensor, mlir::Value disableOutputLane, NVVM::CTAGroupKind ctaGroup, bool hasAShift, NVVM::Tcgen05MMACollectorOp collectorOp, Location loc)
#define _none
static bool isPtrInAddrSpace(mlir::Value ptr, NVVMMemorySpace targetAS)
static bool isPtrInSharedCTASpace(mlir::Value ptr)
static LogicalResult isAllowedSizeN(int sizeN, NVVM::WGMMATypes typeA)
static llvm::nvvm::CTAGroupKind getNVVMCtaGroupKind(NVVM::CTAGroupKind ctaGroup)
static void addInferredMultiplicandTypes(MLIRContext *ctx, OperationState &result, ValueRange operandA, ValueRange operandB, std::optional< std::array< MMATypes, 2 > > multiplicandPtxTypes)
#define GET_CVT_F2TF32_ID(rnd, relu, sf)
static void addBlockScaleProperties(OpBuilder &builder, OperationState &result, ArrayRef< int64_t > shape, ScaleVecSize scaleVecSize, BlockScaleFormat blockScaleFormat, MMABlockScaleKind kind)
#define GET_F32x2_TO_F8X2_US_ID(rnd, has_satf)
static llvm::Value * getParamCastedAddr(llvm::Value *addr, llvm::IRBuilderBase &builder)
static LogicalResult verifyTcgen05MMABlockScaleOp(NVVM::Tcgen05MMACollectorOp collectorOp, NVVM::MMABlockScaleKind kind, NVVM::Tcgen05MMABlockScale blockScale, Location loc)
static llvm::Value * packValInto64Bits(llvm::IRBuilderBase &builder, llvm::Value *result, llvm::Value *field, unsigned sizeInBits, unsigned start)
Packs the given field into the result.
static void printOperandList(OpAsmPrinter &p, StringRef name, ArrayRef< Value > operands)
#define GET_F32x2_TO_F6x2_ID(type, has_relu)
static llvm::Value * getAsPackedI32(llvm::Value *arg, llvm::IRBuilderBase &builder)
#define GET_F16x2_TO_F8X2_ID(type, has_relu)
static LogicalResult verifyMBarrierArriveLikeOp(Operation *op, Value addr, NVVM::MemScopeKind scope, Value retVal=nullptr)
static llvm::Value * castPtrToAddrSpace(llvm::IRBuilderBase &builder, llvm::Value *ptr, NVVMMemorySpace targetAS)
static LogicalResult isAllowedWGMMADataType(NVVM::WGMMATypes typeD, NVVM::WGMMATypes typeA, NVVM::WGMMATypes typeB)
#define GET_BF16X2_TO_F8X2_ID(rnd, has_satf)
static void inferAndSetMultiplicandTypes(MLIRContext *ctx, NamedAttrList &attrs, const SmallVectorImpl< Type > &operandTypes)
static LogicalResult parseMmaOperand(OpAsmParser &parser, StringRef operandName, SmallVectorImpl< OpAsmParser::UnresolvedOperand > &regs)
static std::pair< mlir::Type, unsigned > inferMMATypeFromMNK(NVVM::MMATypes type, NVVM::MMAFrag frag, int m, int n, int k, MLIRContext *context)
static bool isInt8PtxType(MMATypes type)
static bool isInt4PtxType(MMATypes type)
static bool isIntegerPtxType(MMATypes type)
#define GET_F32x2_TO_F8X2_S_ID(type, has_relu)
static MMATypes inferPtxTypeFromResult(OpTy op)
static LogicalResult verifyConstantRangeAttr(Operation *op, std::optional< LLVM::ConstantRangeAttr > rangeAttr)
Verify the range attribute satisfies LLVM ConstantRange constructor requirements for NVVM SpecialRang...
static LogicalResult parseMmaTypeSignature(OpAsmParser &parser, SmallVectorImpl< Type > &operandTypes)
static FailureOr< int > getAllowedSizeK(NVVM::WGMMATypes typeA)
static bool isPtrInSharedClusterSpace(mlir::Value ptr)
#define GET_CP_ASYNC_ID(mod, size, has_cpsize)
static unsigned isValidVectorLength(NVVM::Tcgen05LdStShape shape, unsigned vecLen)
#define GET_TCGEN05_COMMIT_ID(cta_group, is_shared, has_mc)
static LogicalResult verifyConvertF32x2ToFP16x2Op(Twine dstType, FPRoundingMode rnd, bool hasRandomBits, Operation *op)
static void nvvmInferResultRanges(Operation *op, Value result, ArrayRef<::mlir::ConstantIntRanges > argRanges, SetIntRangeFn setResultRanges)
Infer the result ranges for the NVVM SpecialRangeableRegisterOp that might have ConstantRangeAttr.
static LogicalResult cpAsyncBulkTensorCommonVerifier(size_t tensorDims, bool isIm2Col, size_t numIm2ColOffsets, Location loc)
static bool isPtrInGenericSpace(mlir::Value ptr)
static void processOperandFragments(Op &op, std::array< MMAOperandFragment, 3 > &frags, SmallVectorImpl< Type > &regTypes, SmallVectorImpl< StringRef > &ignoreAttrNames)
static constexpr unsigned notIntrinsic
static ArrayRef< int64_t > getShape(Type type)
Returns the shape of the given type.
Definition Traits.cpp:117
@ OptionalSquare
Square brackets supporting zero or more ops, or nothing.
virtual Builder & getBuilder() const =0
Return a builder which provides useful access to MLIRContext, global objects like types and attribute...
virtual ParseResult parseCommaSeparatedList(Delimiter delimiter, function_ref< ParseResult()> parseElementFn, StringRef contextMessage=StringRef())=0
Parse a list of comma-separated items with an optional delimiter.
virtual ParseResult parseOptionalAttrDict(NamedAttrList &result)=0
Parse a named dictionary into 'result' if it is present.
MLIRContext * getContext() const
virtual ParseResult parseRParen()=0
Parse a ) token.
virtual InFlightDiagnostic emitError(SMLoc loc, const Twine &message={})=0
Emit a diagnostic at the specified location and return failure.
virtual SMLoc getCurrentLocation()=0
Get the location of the next token and store it into the argument.
virtual ParseResult parseColon()=0
Parse a : token.
virtual SMLoc getNameLoc() const =0
Return the location of the original name token.
virtual ParseResult parseArrow()=0
Parse a '->' token.
virtual ParseResult parseLParen()=0
Parse a ( token.
virtual ParseResult parseType(Type &result)=0
Parse a type.
virtual ParseResult parseArrowTypeList(SmallVectorImpl< Type > &result)=0
Parse an arrow followed by a type list.
ParseResult parseTypeList(SmallVectorImpl< Type > &result)
Parse a type list.
ParseResult parseKeyword(StringRef keyword)
Parse a given keyword.
void printArrowTypeList(TypeRange &&types)
This class is a general helper class for creating context-global objects like types,...
Definition Builders.h:51
IntegerType getI16Type()
Definition Builders.cpp:61
UnitAttr getUnitAttr()
Definition Builders.cpp:98
DenseI32ArrayAttr getDenseI32ArrayAttr(ArrayRef< int32_t > values)
Definition Builders.cpp:163
IntegerType getI32Type()
Definition Builders.cpp:63
IntegerType getIntegerType(unsigned width)
Definition Builders.cpp:67
MLIRContext * getContext() const
Definition Builders.h:56
Attr getAttr(Args &&...args)
Get or construct an instance of the attribute Attr with provided arguments.
Definition Builders.h:98
This class represents a diagnostic that is inflight and set to be reported.
Implementation class for module translation.
llvm::Value * lookupValue(Value value) const
Finds an LLVM IR value corresponding to the given MLIR value.
void mapValue(Value mlir, llvm::Value *llvm)
Stores the mapping between an MLIR value and its LLVM IR counterpart.
llvm::LLVMContext & getLLVMContext() const
Returns the LLVM context in which the IR is being constructed.
This class defines the main interface for locations in MLIR and acts as a non-nullable wrapper around...
Definition Location.h:76
MLIRContext is the top-level object for a collection of MLIR operations.
Definition MLIRContext.h:63
NamedAttrList is array of NamedAttributes that tracks whether it is sorted and does some basic work t...
std::optional< NamedAttribute > getNamed(StringRef name) const
Return the specified named attribute if present, std::nullopt otherwise.
Attribute get(StringAttr name) const
Return the specified attribute if present, null otherwise.
Attribute set(StringAttr name, Attribute value)
If the an attribute exists with the specified name, change it to the new value.
NamedAttribute represents a combination of a name and an Attribute value.
Definition Attributes.h:164
StringAttr getName() const
Return the name of the attribute.
Attribute getValue() const
Return the value of the attribute.
Definition Attributes.h:179
The OpAsmParser has methods for interacting with the asm parser: parsing things from it,...
ParseResult resolveOperands(Operands &&operands, Type type, SmallVectorImpl< Value > &result)
Resolve a list of operands to SSA values, emitting an error on failure, or appending the results to t...
virtual ParseResult parseOperandList(SmallVectorImpl< UnresolvedOperand > &result, Delimiter delimiter=Delimiter::None, bool allowResultNumber=true, int requiredOperandCount=-1)=0
Parse zero or more SSA comma-separated operand references with a specified surrounding delimiter,...
This is a pure-virtual base class that exposes the asmprinter hooks necessary to implement a custom p...
void printOperands(const ContainerType &container)
Print a comma separated list of operands.
virtual void printOptionalAttrDict(ArrayRef< NamedAttribute > attrs, ArrayRef< StringRef > elidedAttrs={})=0
If the specified operation has attributes, print out an attribute dictionary with their values.
This class helps build Operations.
Definition Builders.h:207
This provides public APIs that all operations should have.
Operation is the basic unit of execution within MLIR.
Definition Operation.h:88
AttrClass getAttrOfType(StringAttr name)
Definition Operation.h:550
bool hasAttr(StringAttr name)
Return true if the operation has an attribute with the provided name, false otherwise.
Definition Operation.h:560
Location getLoc()
The source location the operation was defined or derived from.
Definition Operation.h:223
InFlightDiagnostic emitError(const Twine &message={})
Emit an error about fatal conditions with this operation, reporting up to any diagnostic handlers tha...
InFlightDiagnostic emitOpError(const Twine &message={})
Emit an error with the op name prefixed, like "'dim' op " which is convenient for verifiers.
This class coordinates the application of a rewrite on a set of IR, providing a way for clients to tr...
This class provides an abstraction over the various different ranges of value types.
Definition TypeRange.h:37
Instances of the Type class are uniqued, have an immutable identifier and an optional mutable compone...
Definition Types.h:74
bool isF64() const
Definition Types.cpp:41
MLIRContext * getContext() const
Return the MLIRContext in which this type was uniqued.
Definition Types.cpp:35
bool isF32() const
Definition Types.cpp:40
bool isInteger() const
Return true if this is an integer type (with the specified width).
Definition Types.cpp:56
bool isF16() const
Definition Types.cpp:38
This class provides an abstraction over the different types of ranges over Values.
Definition ValueRange.h:387
This class represents an instance of an SSA value in the MLIR system, representing a computable value...
Definition Value.h:96
Type getType() const
Return the type of this value.
Definition Value.h:105
static WalkResult advance()
Definition WalkResult.h:47
static WalkResult interrupt()
Definition WalkResult.h:46
bool isValidLoadStoreImpl(Type type, ptr::AtomicOrdering ordering, std::optional< int64_t > alignment, const ::mlir::DataLayout *dataLayout, function_ref< InFlightDiagnostic()> emitError)
Checks whether the given type is an LLVM type that can be loaded or stored.
Definition LLVMAttrs.cpp:60
SmallVector< int64_t, 4 > getCoordinates(ArrayRef< int64_t > basis, unsigned linearIndex)
@ Write
Write register with '=' modifier.
@ ReadWrite
ReadWrite register with '+' modifier.
@ Read
Read register with no modifier.
std::pair< mlir::Type, unsigned > inferMMAType(mlir::NVVM::MMATypes type, mlir::NVVM::MMAFrag frag, int nRow, int nCol, mlir::MLIRContext *context)
Return the element type and number of elements associated with a wmma matrix of given chracteristics.
std::pair< llvm::Intrinsic::ID, llvm::SmallVector< llvm::Value * > > IDArgPair
A pair type of LLVM's Intrinsic ID and args (which are llvm values).
Definition NVVMDialect.h:53
Value getReductionOp(AtomicRMWKind op, OpBuilder &builder, Location loc, Value lhs, Value rhs)
Returns the value obtained by applying the reduction operation kind associated with a binary AtomicRM...
void walk(Operation *op, function_ref< void(Region *)> callback, WalkOrder order)
Walk all of the regions, blocks, or operations nested under (and including) the given operation.
Definition Visitors.h:102
detail::InFlightRemark failed(Location loc, RemarkOpts opts)
Report an optimization remark that failed.
Definition Remarks.h:573
uint64_t getN(LevelType lt)
Definition Enums.h:442
uint64_t getM(LevelType lt)
Definition Enums.h:443
Include the generated interface declarations.
llvm::function_ref< void(Value, const ConstantIntRanges &)> SetIntRangeFn
The type of the setResultRanges callback provided to ops implementing InferIntRangeInterface.
Type getType(OpFoldResult ofr)
Returns the int type of the integer in ofr.
Definition Utils.cpp:304
InFlightDiagnostic emitError(Location loc)
Utility method to emit an error message using this location.
llvm::function_ref< Fn > function_ref
Definition LLVM.h:152
bool isCompatibleWith(const NVVMCheckSMVersion &targetSM) const
static const NVVMCheckSMVersion getTargetSMVersionFromStr(StringRef smVersionString)
This represents an operation in an abstracted form, suitable for use with the builder APIs.