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"
46#include "mlir/Dialect/LLVMIR/NVVMOpsDialect.cpp.inc"
47#include "mlir/Dialect/LLVMIR/NVVMOpsEnums.cpp.inc"
49static constexpr unsigned notIntrinsic = llvm::Intrinsic::not_intrinsic;
56 auto ptrTy = llvm::cast<LLVM::LLVMPointerType>(
ptr.getType());
57 return ptrTy.getAddressSpace() ==
static_cast<unsigned>(targetAS);
74 NVVMMemorySpace targetAS) {
75 unsigned AS =
static_cast<unsigned>(targetAS);
76 return builder.CreateAddrSpaceCast(
77 ptr, llvm::PointerType::get(builder.getContext(), AS));
81static llvm::nvvm::CTAGroupKind
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;
89 llvm_unreachable(
"unsupported cta_group value");
101 size_t numIm2ColOffsets,
103 if (tensorDims < 1 || tensorDims > 5)
104 return emitError(loc,
"expects coordinates between 1 to 5 dimension");
112 "to use im2col mode, the tensor has to be at least 3-dimensional");
114 if (numIm2ColOffsets && (tensorDims != (numIm2ColOffsets + 2)))
116 loc,
"im2col offsets must be 2 less than number of coordinates");
121LogicalResult CpAsyncBulkTensorSharedCTAToGlobalOp::verify() {
122 TMAStoreMode mode = getMode();
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.");
135 case TMAStoreMode::TILE:
137 case TMAStoreMode::IM2COL:
139 case TMAStoreMode::TILE_SCATTER4:
141 return emitError(
"Scatter4 mode expects 5 coordinates");
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.");
160 if (tensorDims < 1 || tensorDims > 5)
161 return emitError(loc,
"expects coordinates between 1 to 5 dimension");
163 auto checkTMALoadParams = [&](TMALoadMode mode,
bool isIm2col,
164 size_t expectedIm2colOff) -> LogicalResult {
165 if (isIm2col && (tensorDims < 3))
168 <<
" mode, the tensor has to be at least 3-dimensional";
170 if (numIm2colOff != expectedIm2colOff)
171 return emitError(loc) <<
" im2col offsets expected " << expectedIm2colOff
172 <<
" (provided " << numIm2colOff <<
")";
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");
193LogicalResult CpAsyncBulkTensorPrefetchOp::verify() {
195 getMode(), getLoc());
198LogicalResult CpAsyncBulkTensorGlobalToSharedClusterOp::verify() {
199 TMALoadMode mode = getMode();
200 bool isCTAOnly = getIsCTAOnly();
201 if (getPredicate()) {
203 return emitError(
"Predicate is supported only for shared::cluster mode.");
204 if (mode != TMALoadMode::TILE && mode != TMALoadMode::IM2COL)
206 "Predicate is supported only for Tile and Im2col modes.");
208 NVVMMemorySpace expectedAS =
209 isCTAOnly ? NVVMMemorySpace::Shared : NVVMMemorySpace::SharedCluster;
210 unsigned AS = llvm::cast<LLVM::LLVMPointerType>(getDstMem().
getType())
212 if (AS != expectedAS)
215 ?
"Shared::cta destination requires address-space 3."
216 :
"Shared::cluster destination requires address-space 7.");
219 if (getMulticastMask())
220 return emitError(
"Multicast is not supported with shared::cta mode.");
222 return emitError(
"CTAGroup is not supported with shared::cta mode.");
227 getMode(), getLoc());
230LogicalResult CpAsyncBulkTensorReduceOp::verify() {
231 TMAStoreMode mode = getMode();
234 case TMAStoreMode::TILE:
236 case TMAStoreMode::IM2COL:
238 case TMAStoreMode::TILE_SCATTER4:
239 return emitError(
"Scatter mode unsupported for CpAsyncBulkTensorReduceOp");
244LogicalResult CpAsyncBulkGlobalToSharedClusterOp::verify() {
246 if (isSharedCTA && getMulticastMask())
247 return emitError(
"Multicast is not supported with shared::cta mode.");
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");
259 bool hasRetValue =
static_cast<bool>(retVal);
260 if (isSharedCluster && hasRetValue)
262 "mbarrier in shared_cluster space cannot return any value");
267LogicalResult MBarrierArriveOp::verify() {
272LogicalResult MBarrierArriveDropOp::verify() {
277LogicalResult MBarrierArriveExpectTxOp::verify() {
281 if (getPredicate()) {
282 if (getScope() != NVVM::MemScopeKind::CTA)
283 return emitError(
"mbarrier scope must be CTA when using predicate");
286 return emitError(
"mbarrier in shared_cluster space is not supported when "
290 return emitError(
"return-value is not supported when using predicate");
292 if (getRelaxed() ==
true)
293 return emitError(
"mbarrier with relaxed semantics is not supported when "
300LogicalResult MBarrierArriveDropExpectTxOp::verify() {
315 inferredReturnTypes.push_back(IntegerType::get(context, 64));
320MBarrierArriveOp::inferReturnTypes(
MLIRContext *context,
321 std::optional<Location> location,
322 MBarrierArriveOp::Adaptor adaptor,
325 inferredReturnTypes);
328LogicalResult MBarrierArriveDropOp::inferReturnTypes(
329 MLIRContext *context, std::optional<Location> location,
330 MBarrierArriveDropOp::Adaptor adaptor,
333 inferredReturnTypes);
336LogicalResult MBarrierArriveExpectTxOp::inferReturnTypes(
337 MLIRContext *context, std::optional<Location> location,
338 MBarrierArriveExpectTxOp::Adaptor adaptor,
342 if (adaptor.getPredicate())
345 inferredReturnTypes);
348LogicalResult MBarrierArriveDropExpectTxOp::inferReturnTypes(
349 MLIRContext *context, std::optional<Location> location,
350 MBarrierArriveDropExpectTxOp::Adaptor adaptor,
353 inferredReturnTypes);
363 return inferred == actual;
372bool MBarrierArriveExpectTxOp::isCompatibleReturnTypes(
TypeRange l,
376bool MBarrierArriveDropExpectTxOp::isCompatibleReturnTypes(
TypeRange l,
381LogicalResult MBarrierExpectTxOp::verify() {
385LogicalResult MBarrierCompleteTxOp::verify() {
389LogicalResult MBarrierTestWaitOp::verify() {
393LogicalResult MBarrierTryWaitOp::verify() {
397LogicalResult ConvertFloatToTF32Op::verify() {
398 using RndMode = NVVM::FPRoundingMode;
402 return emitError(
"Relu not supported with rna rounding mode.");
409 "Only {rn,rz,rna} rounding modes supported for ConvertFloatToTF32Op.");
414LogicalResult ConvertF32x2ToF6x2Op::verify() {
417 if (!llvm::isa<mlir::Float6E2M3FNType, mlir::Float6E3M2FNType>(getDstTy())) {
419 << mlir::Float6E2M3FNType::get(ctx) <<
" and "
420 << mlir::Float6E3M2FNType::get(ctx)
421 <<
" types are supported for conversions from f32x2 to f6x2.";
426LogicalResult ConvertF32x2ToF8x2Op::verify() {
427 using RndMode = NVVM::FPRoundingMode;
428 using SatMode = NVVM::SaturationMode;
430 bool isRoundingModeRN = getRnd() == RndMode::RN;
431 bool isRoundingModeRZ = getRnd() == RndMode::RZ;
432 bool isRoundingModeRP = getRnd() == RndMode::RP;
433 bool isSatFinite = getSat() == SatMode::SATFINITE;
435 bool hasRelu = getRelu();
440 .Case<mlir::Float8E4M3FNType, mlir::Float8E5M2Type>(
442 if (!isRoundingModeRN) {
443 return emitOpError(
"Only RN rounding mode is supported for "
444 "conversions from f32x2 to ")
445 << mlir::Float8E4M3FNType::get(ctx) <<
" and "
446 << mlir::Float8E5M2Type::get(ctx) <<
" types";
449 return emitOpError(
"Only SATFINITE saturation mode is supported "
452 << mlir::Float8E4M3FNType::get(ctx) <<
" and "
453 << mlir::Float8E5M2Type::get(ctx) <<
" types";
457 .Case<mlir::Float8E8M0FNUType>([&](
mlir::Type) -> LogicalResult {
458 if (!(isRoundingModeRZ || isRoundingModeRP)) {
459 return emitOpError(
"Only RZ and RP rounding modes are supported for "
460 "conversions from f32x2 to ")
461 << mlir::Float8E8M0FNUType::get(ctx) <<
" type";
464 return emitOpError(
"relu not supported for conversions to ")
465 << mlir::Float8E8M0FNUType::get(ctx) <<
" type";
471 << mlir::Float8E4M3FNType::get(ctx) <<
", "
472 << mlir::Float8E5M2Type::get(ctx) <<
", and "
473 << mlir::Float8E8M0FNUType::get(ctx)
475 "supported for conversions from f32x2 to f8x2";
479LogicalResult ConvertF16x2ToF8x2Op::verify() {
482 if (!llvm::isa<mlir::Float8E4M3FNType, mlir::Float8E5M2Type>(getDstTy())) {
484 << mlir::Float8E4M3FNType::get(ctx) <<
" and "
485 << mlir::Float8E5M2Type::get(ctx)
486 <<
" types are supported for conversions from f16x2 to f8x2.";
491LogicalResult ConvertBF16x2ToF8x2Op::verify() {
492 using RndMode = NVVM::FPRoundingMode;
493 using SatMode = NVVM::SaturationMode;
495 bool isRoundingModeRN = getRnd() == RndMode::RN;
496 bool isRoundingModeRZ = getRnd() == RndMode::RZ;
497 bool isRoundingModeRP = getRnd() == RndMode::RP;
498 bool isSatFinite = getSat() == SatMode::SATFINITE;
499 bool hasRelu = getRelu();
504 .Case<mlir::Float8E4M3FNType, mlir::Float8E5M2Type>(
506 if (!isRoundingModeRN)
507 return emitOpError(
"Only RN rounding mode is supported for "
508 "conversions from bf16x2 to ")
509 << mlir::Float8E4M3FNType::get(ctx) <<
" and "
510 << mlir::Float8E5M2Type::get(ctx) <<
" types";
512 return emitOpError(
"Only SATFINITE saturation mode is supported "
513 "for conversions from bf16x2 to ")
514 << mlir::Float8E4M3FNType::get(ctx) <<
" and "
515 << mlir::Float8E5M2Type::get(ctx) <<
" types";
518 .Case<mlir::Float8E8M0FNUType>([&](
mlir::Type) -> LogicalResult {
519 if (!(isRoundingModeRZ || isRoundingModeRP))
520 return emitOpError(
"Only RZ and RP rounding modes are supported for "
521 "conversions from bf16x2 to ")
522 << mlir::Float8E8M0FNUType::get(ctx) <<
" type";
524 return emitOpError(
"relu not supported for conversions to ")
525 << mlir::Float8E8M0FNUType::get(ctx) <<
" type";
529 llvm_unreachable(
"Invalid conversion in ConvertBF16x2ToF8x2Op");
534LogicalResult ConvertF32x2ToF4x2Op::verify() {
537 if (!llvm::isa<mlir::Float4E2M1FNType>(getDstTy()))
539 << mlir::Float4E2M1FNType::get(ctx)
540 <<
" type is supported for conversions from f32x2 to f4x2.";
545LogicalResult ConvertF8x2ToF16x2Op::verify() {
548 if (!llvm::isa<Float8E4M3FNType, Float8E5M2Type>(getSrcType()))
550 << mlir::Float8E4M3FNType::get(ctx) <<
" and "
551 << mlir::Float8E5M2Type::get(ctx)
552 <<
" types are supported for conversions from f8x2 to f16x2.";
557LogicalResult ConvertF8x2ToBF16x2Op::verify() {
559 if (!llvm::isa<Float8E8M0FNUType>(getSrcType()))
561 << mlir::Float8E8M0FNUType::get(ctx)
562 <<
" type is supported for conversions from f8x2 to bf16x2.";
567LogicalResult ConvertF6x2ToF16x2Op::verify() {
570 if (!llvm::isa<Float6E2M3FNType, Float6E3M2FNType>(getSrcType()))
572 << mlir::Float6E2M3FNType::get(ctx) <<
" and "
573 << mlir::Float6E3M2FNType::get(ctx)
574 <<
" types are supported for conversions from f6x2 to f16x2.";
579LogicalResult ConvertF4x2ToF16x2Op::verify() {
582 if (!llvm::isa<Float4E2M1FNType>(getSrcType()))
584 << mlir::Float4E2M1FNType::get(ctx)
585 <<
" type is supported for conversions from f4x2 to f16x2.";
590LogicalResult PermuteOp::verify() {
591 using Mode = NVVM::PermuteMode;
592 bool hasHi =
static_cast<bool>(getHi());
599 return emitError(
"mode '") << getMode() <<
"' requires 'hi' operand.";
607 << getMode() <<
"' does not accept 'hi' operand.";
622 static constexpr FPRoundingMode validRndModes[] = {
623 FPRoundingMode::RN, FPRoundingMode::RZ, FPRoundingMode::RS};
625 if (!llvm::is_contained(validRndModes, rnd)) {
627 "Only RN, RZ, and RS rounding modes are supported for "
628 "conversions from f32x2 to ")
632 if (rnd == FPRoundingMode::RS) {
633 if (!hasRandomBits) {
634 return op->
emitOpError(
"random_bits is required for RS rounding mode.");
639 "random_bits not supported for RN and RZ rounding modes.");
646LogicalResult ConvertF32x2ToF16x2Op::verify() {
648 getRandomBits() ?
true :
false, *
this);
651LogicalResult ConvertF32x2ToBF16x2Op::verify() {
653 getRandomBits() ?
true :
false, *
this);
656LogicalResult ConvertF32x4ToF8x4Op::verify() {
659 if (!llvm::isa<mlir::Float8E4M3FNType, mlir::Float8E5M2Type>(getDstTy()))
661 << mlir::Float8E4M3FNType::get(ctx) <<
" and "
662 << mlir::Float8E5M2Type::get(ctx)
663 <<
" types are supported for conversions from f32x4 to f8x4.";
668LogicalResult ConvertF32x4ToF6x4Op::verify() {
671 if (!llvm::isa<mlir::Float6E2M3FNType, mlir::Float6E3M2FNType>(getDstTy()))
673 << mlir::Float6E2M3FNType::get(ctx) <<
" and "
674 << mlir::Float6E3M2FNType::get(ctx)
675 <<
" types are supported for conversions from f32x4 to f6x4.";
680LogicalResult ConvertF32x4ToF4x4Op::verify() {
683 if (!llvm::isa<mlir::Float4E2M1FNType>(getDstTy()))
684 return emitOpError(
"Only ") << mlir::Float4E2M1FNType::get(ctx)
685 <<
" type is supported for conversions from "
691LogicalResult BulkStoreOp::verify() {
692 if (getInitVal() != 0)
693 return emitOpError(
"only 0 is supported for initVal, got ") << getInitVal();
697LogicalResult PMEventOp::verify() {
698 auto eventId = getEventId();
699 auto maskedEventId = getMaskedEventId();
700 if (!maskedEventId && !eventId) {
701 return emitOpError() <<
"either `id` or `mask` must be set";
704 if (maskedEventId && eventId) {
705 return emitOpError() <<
"`id` and `mask` cannot be set at the same time";
709 if (eventId < 0 || eventId > 15) {
710 return emitOpError() <<
"`id` must be between 0 and 15";
714 return llvm::success();
720std::optional<mlir::NVVM::MMATypes>
721MmaOp::inferOperandMMAType(
Type operandElType,
bool isAccumulator) {
723 VectorType::get(2, Float16Type::get(operandElType.
getContext()));
724 if (operandElType.
isF64())
725 return NVVM::MMATypes::f64;
726 if (operandElType.
isF16() || operandElType == half2Type)
727 return NVVM::MMATypes::f16;
728 if (operandElType.
isF32() && isAccumulator)
729 return NVVM::MMATypes::f32;
730 if (operandElType.
isF32() && !isAccumulator)
731 return NVVM::MMATypes::tf32;
732 if (llvm::isa<IntegerType>(operandElType)) {
734 return NVVM::MMATypes::s32;
738 if (
auto structType = llvm::dyn_cast<LLVM::LLVMStructType>(operandElType)) {
739 if (structType.getBody().empty())
741 return inferOperandMMAType(structType.getBody()[0], isAccumulator);
748 return (type == MMATypes::u4 || type == MMATypes::s4);
752 return (type == MMATypes::u8 || type == MMATypes::s8);
757 type == MMATypes::s32;
760MMATypes MmaOp::accumPtxType() {
761 std::optional<mlir::NVVM::MMATypes> val = inferOperandMMAType(
762 getODSOperands(2).getTypes().front(),
true);
763 assert(val.has_value() &&
"accumulator PTX type should always be inferrable");
767MMATypes MmaOp::resultPtxType() {
768 std::optional<mlir::NVVM::MMATypes> val =
769 inferOperandMMAType(getResult().
getType(),
true);
770 assert(val.has_value() &&
"result PTX type should always be inferrable");
776 struct MMAOperandFragment {
777 StringRef operandName;
778 StringRef ptxTypeAttr;
779 SmallVector<Value, 4> regs;
780 explicit MMAOperandFragment(StringRef name, StringRef ptxTypeName)
781 : operandName(name), ptxTypeAttr(ptxTypeName) {}
784 std::array<MMAOperandFragment, 3> frags{
785 MMAOperandFragment(
"A", getMultiplicandAPtxTypeAttrName()),
786 MMAOperandFragment(
"B", getMultiplicandBPtxTypeAttrName()),
787 MMAOperandFragment(
"C",
"")};
789 mlir::NVVM::MmaOp::getOperandSegmentSizeAttr()};
791 for (
unsigned fragIdx = 0; fragIdx < frags.size(); fragIdx++) {
792 auto &frag = frags[fragIdx];
793 auto varOperandSpec = getODSOperandIndexAndLength(fragIdx);
794 for (
auto operandIdx = varOperandSpec.first;
795 operandIdx < varOperandSpec.first + varOperandSpec.second;
797 frag.regs.push_back(this->getOperand(operandIdx));
798 if (operandIdx == 0) {
799 regTypes.push_back(this->getOperand(operandIdx).
getType());
802 std::optional<MMATypes> inferredType = MmaOp::inferOperandMMAType(
803 regTypes.back(), fragIdx >= 2);
805 ignoreAttrNames.push_back(frag.ptxTypeAttr);
808 auto printMmaOperand = [&](
const MMAOperandFragment &frag) ->
void {
809 p <<
" " << frag.operandName;
815 for (
const auto &frag : frags) {
816 printMmaOperand(frag);
825 frags[1].regs[0].getType(),
826 frags[2].regs[0].getType()},
835 std::optional<MMAIntOverflow> intOverflow,
836 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes,
837 std::optional<std::array<MMALayout, 2>> multiplicandLayouts) {
839 assert(
shape.size() == 3 &&
"expected shape to have size 3 (m, n, k)");
844 result.addOperands(operandA);
845 result.addOperands(operandB);
846 result.addOperands(operandC);
848 if (multiplicandPtxTypes) {
849 result.addAttribute(
"multiplicandAPtxType",
850 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[0]));
851 result.addAttribute(
"multiplicandBPtxType",
852 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[1]));
854 if (
auto res = inferOperandMMAType(operandA[0].
getType(),
false))
855 result.addAttribute(
"multiplicandAPtxType", MMATypesAttr::get(ctx, *res));
856 if (
auto res = inferOperandMMAType(operandB[0].
getType(),
false))
857 result.addAttribute(
"multiplicandBPtxType", MMATypesAttr::get(ctx, *res));
860 if (multiplicandLayouts) {
861 result.addAttribute(
"layoutA",
862 MMALayoutAttr::get(ctx, (*multiplicandLayouts)[0]));
863 result.addAttribute(
"layoutB",
864 MMALayoutAttr::get(ctx, (*multiplicandLayouts)[1]));
866 result.addAttribute(
"layoutA", MMALayoutAttr::get(ctx, MMALayout::row));
867 result.addAttribute(
"layoutB", MMALayoutAttr::get(ctx, MMALayout::col));
870 if (intOverflow.has_value())
871 result.addAttribute(
"intOverflowBehavior",
872 MMAIntOverflowAttr::get(ctx, *intOverflow));
873 if (b1Op.has_value())
874 result.addAttribute(
"b1Op", MMAB1OpAttr::get(ctx, *b1Op));
876 result.addTypes(resultType);
878 MmaOp::getOperandSegmentSizeAttr(),
880 static_cast<int32_t>(operandB.size()),
881 static_cast<int32_t>(operandC.size())}));
889 struct MMAOperandFragment {
890 std::optional<MMATypes> elemtype;
891 SmallVector<OpAsmParser::UnresolvedOperand, 4> regs;
892 SmallVector<Type> regTypes;
896 std::array<MMAOperandFragment, 4> frags;
902 MMAOperandFragment &frag) -> LogicalResult {
932 if (operandTypes.size() != 3)
935 "expected one type for each operand segment but got " +
936 Twine(operandTypes.size()) +
" types");
937 for (
const auto &iter : llvm::enumerate(operandTypes)) {
938 auto &frag = frags[iter.index()];
939 frag.regTypes.resize(frag.regs.size(), iter.value());
943 frag.elemtype = inferOperandMMAType(frag.regTypes[0],
950 frags[3].elemtype = inferOperandMMAType(resultType,
true);
952 std::array<StringRef, 2> names{
"multiplicandAPtxType",
953 "multiplicandBPtxType"};
954 for (
unsigned idx = 0; idx < names.size(); idx++) {
955 const auto &frag = frags[idx];
956 std::optional<NamedAttribute> attr = namedAttributes.
getNamed(names[idx]);
957 if (!frag.elemtype.has_value() && !attr.has_value()) {
960 "attribute " + names[idx] +
961 " is not provided explicitly and cannot be inferred");
963 if (!attr.has_value())
965 names[idx], MMATypesAttr::get(parser.
getContext(), *frag.elemtype));
968 result.addTypes(resultType);
969 if (!namedAttributes.
empty())
970 result.addAttributes(namedAttributes);
971 result.addAttribute(MmaOp::getOperandSegmentSizeAttr(),
973 static_cast<int32_t>(frags[0].regs.size()),
974 static_cast<int32_t>(frags[1].regs.size()),
975 static_cast<int32_t>(frags[2].regs.size()),
980LogicalResult MmaOp::verify() {
982 auto f16Ty = Float16Type::get(context);
983 auto i32Ty = IntegerType::get(context, 32);
984 auto f16x2Ty = VectorType::get(2, f16Ty);
985 auto f32Ty = Float32Type::get(context);
986 auto f16x2x4StructTy = LLVM::LLVMStructType::getLiteral(
987 context, {f16x2Ty, f16x2Ty, f16x2Ty, f16x2Ty});
990 LLVM::LLVMStructType::getLiteral(context, {i32Ty, i32Ty, i32Ty, i32Ty});
993 auto f16x2x2StructTy =
994 LLVM::LLVMStructType::getLiteral(context, {f16x2Ty, f16x2Ty});
996 LLVM::LLVMStructType::getLiteral(context, {f32Ty, f32Ty, f32Ty, f32Ty});
998 LLVM::LLVMStructType::getLiteral(context, {i32Ty, i32Ty});
1000 std::array<int64_t, 3> mmaShape{getShapeAttr().getM(), getShapeAttr().getN(),
1001 getShapeAttr().getK()};
1007 AllowedShapes allowedShapes;
1008 AllowedTypes expectedA;
1009 AllowedTypes expectedB;
1010 AllowedTypes expectedC;
1015 if (mmaShape[0] == 16) {
1017 Type multiplicandFragType;
1018 switch (*getMultiplicandAPtxType()) {
1019 case MMATypes::tf32:
1021 multiplicandFragType = i32Ty;
1022 expectedResult.push_back(LLVM::LLVMStructType::getLiteral(
1023 context, {f32Ty, f32Ty, f32Ty, f32Ty}));
1025 case MMATypes::bf16:
1027 multiplicandFragType = i32Ty;
1028 expectedResult.push_back(LLVM::LLVMStructType::getLiteral(
1029 context, {f32Ty, f32Ty, f32Ty, f32Ty}));
1033 multiplicandFragType = f16x2Ty;
1034 expectedResult.push_back(f16x2x2StructTy);
1035 expectedResult.push_back(f32x4StructTy);
1049 return emitError(
"invalid shape or multiplicand type: ")
1050 << getMultiplicandAPtxType().value();
1054 expectedResult.push_back(s32x4StructTy);
1055 expectedC.emplace_back(4, i32Ty);
1056 multiplicandFragType = i32Ty;
1058 expectedC.emplace_back(2, f16x2Ty);
1059 expectedC.emplace_back(4, f32Ty);
1062 int64_t unitA = (mmaShape[0] / 8) * (mmaShape[2] / kFactor);
1063 int64_t unitB = (mmaShape[1] / 8) * (mmaShape[2] / kFactor);
1064 expectedA.emplace_back(unitA, multiplicandFragType);
1065 expectedB.emplace_back(unitB, multiplicandFragType);
1066 allowedShapes.push_back({16, 8, kFactor});
1067 allowedShapes.push_back({16, 8, kFactor * 2});
1069 if (resultPtxType() != accumPtxType())
1074 if (mmaShape[0] == 8) {
1075 if (*getMultiplicandAPtxType() == MMATypes::f16) {
1076 expectedA.emplace_back(2, f16x2Ty);
1077 expectedB.emplace_back(2, f16x2Ty);
1078 expectedResult.push_back(f16x2x4StructTy);
1079 expectedResult.push_back(f32x8StructTy);
1080 expectedC.emplace_back(4, f16x2Ty);
1081 expectedC.emplace_back(8, f32Ty);
1082 allowedShapes.push_back({8, 8, 4});
1084 if (*getMultiplicandAPtxType() == MMATypes::f64) {
1085 Type f64Ty = Float64Type::get(context);
1086 expectedA.emplace_back(1, f64Ty);
1087 expectedB.emplace_back(1, f64Ty);
1088 expectedC.emplace_back(2, f64Ty);
1089 expectedResult.emplace_back(LLVM::LLVMStructType::getLiteral(
1091 allowedShapes.push_back({8, 8, 4});
1094 expectedA.push_back({i32Ty});
1095 expectedB.push_back({i32Ty});
1096 expectedC.push_back({i32Ty, i32Ty});
1097 expectedResult.push_back(s32x2StructTy);
1099 allowedShapes.push_back({8, 8, 32});
1101 allowedShapes.push_back({8, 8, 16});
1102 if (getMultiplicandAPtxType().value() == MMATypes::b1)
1103 allowedShapes.push_back({8, 8, 128});
1107 std::string errorMessage;
1108 llvm::raw_string_ostream errorStream(errorMessage);
1111 if (expectedA.empty() || expectedB.empty() || expectedC.empty() ||
1112 !llvm::is_contained(allowedShapes, mmaShape)) {
1113 errorStream <<
"unimplemented variant for MMA shape <";
1114 llvm::interleaveComma(mmaShape, errorStream);
1120 std::array<StringRef, 3> operandNames{
"A",
"B",
"C"};
1121 for (
const auto &iter : llvm::enumerate(
1123 auto spec = this->getODSOperandIndexAndLength(iter.index());
1125 operand_type_begin() + spec.first +
1127 bool match = llvm::is_contained(iter.value(), operandTySeg);
1130 errorStream <<
"Could not match types for the "
1131 << operandNames[iter.index()]
1132 <<
" operands; expected one of ";
1133 for (
const auto &x : iter.value()) {
1134 errorStream << x.size() <<
"x" << x[0] <<
" ";
1136 errorStream <<
"but got ";
1137 llvm::interleaveComma(operandTySeg, errorStream);
1143 if (!llvm::any_of(expectedResult, [&](
Type expectedResultType) {
1144 return expectedResultType == getResult().getType();
1147 <<
"Could not match allowed types for the result; expected one of ";
1148 llvm::interleaveComma(expectedResult, errorStream);
1149 errorStream <<
" but got " << getResult().getType();
1154 if (getMultiplicandAPtxType() == MMATypes::b1 && !getB1Op()) {
1155 return emitOpError(
"op requires " + getB1OpAttrName().strref() +
1163 if (!getIntOverflowBehavior())
1165 getIntOverflowBehaviorAttrName().strref() +
1173 (mmaShape[0] == 8 && mmaShape[1] == 8 && mmaShape[2] == 4 &&
1174 getMultiplicandAPtxType() == MMATypes::f16);
1176 if (!isM8N8K4_F16) {
1178 if (getLayoutA() != MMALayout::row || getLayoutB() != MMALayout::col) {
1179 return emitOpError(
"requires layoutA = #nvvm.mma_layout<row> and "
1180 "layoutB = #nvvm.mma_layout<col> for shape <")
1181 << mmaShape[0] <<
", " << mmaShape[1] <<
", " << mmaShape[2]
1182 <<
"> with element types " << *getMultiplicandAPtxType() <<
" and "
1183 << *getMultiplicandBPtxType()
1184 <<
". Only m8n8k4 with f16 supports other layouts.";
1191MMATypes MmaSpOp::accumPtxType() {
1192 std::optional<mlir::NVVM::MMATypes> val = MmaOp::inferOperandMMAType(
1193 getODSOperands(2).getTypes().front(),
true);
1194 assert(val.has_value() &&
"accumulator PTX type should always be inferrable");
1198MMATypes MmaSpOp::resultPtxType() {
1199 std::optional<mlir::NVVM::MMATypes> val =
1200 MmaOp::inferOperandMMAType(getResult().
getType(),
true);
1201 assert(val.has_value() &&
"result PTX type should always be inferrable");
1207 llvm::IRBuilderBase &builder) {
1208 auto thisOp = cast<NVVM::MmaSpOp>(op);
1216 auto intId = MmaSpOp::getIntrinsicID(
1217 thisOp.getShape().getM(), thisOp.getShape().getN(),
1218 thisOp.getShape().getK(), thisOp.getIntOverflowBehavior(),
1219 thisOp.getOrderedMetadata(), thisOp.getKind(),
1220 *thisOp.getMultiplicandAPtxType(), *thisOp.getMultiplicandBPtxType(),
1221 thisOp.accumPtxType(), thisOp.resultPtxType());
1223 return {intId, args};
1228 struct MMAOperandFragment {
1229 StringRef operandName;
1230 StringRef ptxTypeAttr;
1231 SmallVector<Value, 4> regs;
1232 explicit MMAOperandFragment(StringRef name, StringRef ptxTypeName)
1233 : operandName(name), ptxTypeAttr(ptxTypeName) {}
1236 std::array<MMAOperandFragment, 5> frags{
1237 MMAOperandFragment(
"A", getMultiplicandAPtxTypeAttrName()),
1238 MMAOperandFragment(
"B", getMultiplicandBPtxTypeAttrName()),
1239 MMAOperandFragment(
"C",
""), MMAOperandFragment(
"sparseMetadata",
""),
1240 MMAOperandFragment(
"selector",
"")};
1242 mlir::NVVM::MmaSpOp::getOperandSegmentSizeAttr()};
1245 for (
unsigned fragIdx = 0; fragIdx < 3; fragIdx++) {
1246 auto &frag = frags[fragIdx];
1247 auto varOperandSpec = getODSOperandIndexAndLength(fragIdx);
1248 for (
auto operandIdx = varOperandSpec.first;
1249 operandIdx < varOperandSpec.first + varOperandSpec.second;
1251 frag.regs.push_back(this->getOperand(operandIdx));
1252 if (operandIdx == varOperandSpec.first) {
1253 regTypes.push_back(this->getOperand(operandIdx).
getType());
1256 std::optional<MMATypes> inferredType = MmaOp::inferOperandMMAType(
1257 regTypes.back(), fragIdx >= 2);
1259 ignoreAttrNames.push_back(frag.ptxTypeAttr);
1263 frags[3].regs.push_back(getSparseMetadata());
1264 frags[4].regs.push_back(getSparsitySelector());
1266 auto printMmaSpOperand = [&](
const MMAOperandFragment &frag) ->
void {
1267 p <<
" " << frag.operandName;
1273 for (
const auto &frag : frags)
1274 printMmaSpOperand(frag);
1279 for (
int i = 0; i < 3; ++i) {
1284 p <<
") -> " << getResult().getType();
1291 std::optional<MMAIntOverflow> intOverflow,
1292 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes) {
1294 assert(
shape.size() == 3 &&
"expected shape to have size 3 (m, n, k)");
1299 result.addOperands(operandA);
1300 result.addOperands(operandB);
1301 result.addOperands(operandC);
1302 result.addOperands(sparseMetadata);
1303 result.addOperands(sparsitySelector);
1305 if (multiplicandPtxTypes) {
1306 result.addAttribute(
"multiplicandAPtxType",
1307 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[0]));
1308 result.addAttribute(
"multiplicandBPtxType",
1309 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[1]));
1311 if (
auto res = MmaOp::inferOperandMMAType(operandA[0].
getType(),
false))
1312 result.addAttribute(
"multiplicandAPtxType", MMATypesAttr::get(ctx, *res));
1313 if (
auto res = MmaOp::inferOperandMMAType(operandB[0].
getType(),
false))
1314 result.addAttribute(
"multiplicandBPtxType", MMATypesAttr::get(ctx, *res));
1317 if (intOverflow.has_value())
1318 result.addAttribute(
"intOverflowBehavior",
1319 MMAIntOverflowAttr::get(ctx, *intOverflow));
1321 result.addTypes(resultType);
1323 MmaSpOp::getOperandSegmentSizeAttr(),
1325 static_cast<int32_t>(operandB.size()),
1326 static_cast<int32_t>(operandC.size()), 1,
1331 struct MMAOperandFragment {
1332 std::optional<MMATypes> elemtype;
1333 SmallVector<OpAsmParser::UnresolvedOperand, 4> regs;
1334 SmallVector<Type> regTypes;
1338 std::array<MMAOperandFragment, 6> frags;
1343 auto parseMmaSpOperand = [&](StringRef operandName,
1344 MMAOperandFragment &frag) -> LogicalResult {
1355 if (parseMmaSpOperand(
"A", frags[0]).
failed())
1357 if (parseMmaSpOperand(
"B", frags[1]).
failed())
1359 if (parseMmaSpOperand(
"C", frags[2]).
failed())
1361 if (parseMmaSpOperand(
"sparseMetadata", frags[3]).
failed())
1363 if (parseMmaSpOperand(
"selector", frags[4]).
failed())
1379 if (operandTypes.size() != 3)
1382 "expected one type for each operand segment but got " +
1383 Twine(operandTypes.size()) +
" types");
1384 for (
const auto &iter : llvm::enumerate(operandTypes)) {
1385 auto &frag = frags[iter.index()];
1386 frag.regTypes.resize(frag.regs.size(), iter.value());
1391 MmaOp::inferOperandMMAType(frag.regTypes[0],
1399 MmaOp::inferOperandMMAType(resultType,
true);
1414 std::array<StringRef, 2> names{
"multiplicandAPtxType",
1415 "multiplicandBPtxType"};
1416 for (
unsigned idx = 0; idx < names.size(); idx++) {
1417 const auto &frag = frags[idx];
1418 std::optional<NamedAttribute> attr = namedAttributes.
getNamed(names[idx]);
1419 if (!frag.elemtype.has_value() && !attr.has_value()) {
1422 "attribute " + names[idx] +
1423 " is not provided explicitly and cannot be inferred");
1425 if (!attr.has_value())
1427 names[idx], MMATypesAttr::get(parser.
getContext(), *frag.elemtype));
1430 result.addTypes(resultType);
1431 if (!namedAttributes.
empty())
1432 result.addAttributes(namedAttributes);
1433 result.addAttribute(MmaSpOp::getOperandSegmentSizeAttr(),
1435 static_cast<int32_t>(frags[0].regs.size()),
1436 static_cast<int32_t>(frags[1].regs.size()),
1437 static_cast<int32_t>(frags[2].regs.size()),
1444LogicalResult MmaSpOp::verify() {
1446 auto f16Ty = Float16Type::get(context);
1447 auto i32Ty = IntegerType::get(context, 32);
1448 auto f16x2Ty = VectorType::get(2, f16Ty);
1449 auto f32Ty = Float32Type::get(context);
1450 auto f16x2x4StructTy = LLVM::LLVMStructType::getLiteral(
1451 context, {f16x2Ty, f16x2Ty, f16x2Ty, f16x2Ty});
1453 auto s32x4StructTy =
1454 LLVM::LLVMStructType::getLiteral(context, {i32Ty, i32Ty, i32Ty, i32Ty});
1455 auto f32x8StructTy =
1457 auto f16x2x2StructTy =
1458 LLVM::LLVMStructType::getLiteral(context, {f16x2Ty, f16x2Ty});
1459 auto f32x4StructTy =
1460 LLVM::LLVMStructType::getLiteral(context, {f32Ty, f32Ty, f32Ty, f32Ty});
1461 auto s32x2StructTy =
1462 LLVM::LLVMStructType::getLiteral(context, {i32Ty, i32Ty});
1464 std::array<int64_t, 3> mmaShape{getShapeAttr().getM(), getShapeAttr().getN(),
1465 getShapeAttr().getK()};
1471 AllowedShapes allowedShapes;
1472 AllowedTypes expectedA;
1473 AllowedTypes expectedB;
1474 AllowedTypes expectedC;
1479 if (mmaShape[0] == 16) {
1481 Type multiplicandFragType;
1482 switch (*getMultiplicandAPtxType()) {
1483 case MMATypes::tf32:
1485 multiplicandFragType = i32Ty;
1486 expectedResult.push_back(LLVM::LLVMStructType::getLiteral(
1487 context, {f32Ty, f32Ty, f32Ty, f32Ty}));
1489 allowedShapes.push_back({16, 8, 8});
1490 allowedShapes.push_back({16, 8, 16});
1492 case MMATypes::bf16:
1494 multiplicandFragType = i32Ty;
1495 expectedResult.push_back(LLVM::LLVMStructType::getLiteral(
1496 context, {f32Ty, f32Ty, f32Ty, f32Ty}));
1498 allowedShapes.push_back({16, 8, 16});
1499 allowedShapes.push_back({16, 8, 32});
1503 multiplicandFragType = f16x2Ty;
1504 expectedResult.push_back(f16x2x2StructTy);
1505 expectedResult.push_back(f32x4StructTy);
1507 allowedShapes.push_back({16, 8, 16});
1508 allowedShapes.push_back({16, 8, 32});
1514 allowedShapes.push_back({16, 8, 64});
1515 allowedShapes.push_back({16, 8, 128});
1521 allowedShapes.push_back({16, 8, 32});
1522 allowedShapes.push_back({16, 8, 64});
1524 case MMATypes::e4m3:
1525 case MMATypes::e5m2:
1526 case MMATypes::e3m2:
1527 case MMATypes::e2m3:
1528 case MMATypes::e2m1:
1530 multiplicandFragType = i32Ty;
1531 expectedResult.push_back(f16x2x2StructTy);
1532 expectedResult.push_back(f32x4StructTy);
1534 allowedShapes.push_back({16, 8, 64});
1537 return emitError(
"invalid shape or multiplicand type: ")
1538 << getMultiplicandAPtxType().value();
1542 expectedResult.push_back(s32x4StructTy);
1543 expectedC.emplace_back(4, i32Ty);
1544 multiplicandFragType = i32Ty;
1545 }
else if (*getMultiplicandAPtxType() >= MMATypes::e4m3 &&
1546 *getMultiplicandAPtxType() <= MMATypes::e2m1) {
1548 expectedC.emplace_back(2, f16x2Ty);
1549 expectedC.emplace_back(4, f32Ty);
1551 expectedC.emplace_back(2, f16x2Ty);
1552 expectedC.emplace_back(4, f32Ty);
1557 int64_t unitA = (mmaShape[0] / 8) * (mmaShape[2] / kFactor) / 2;
1558 int64_t unitB = (mmaShape[1] / 8) * (mmaShape[2] / kFactor);
1559 expectedA.emplace_back(unitA, multiplicandFragType);
1560 expectedB.emplace_back(unitB, multiplicandFragType);
1562 if (resultPtxType() != accumPtxType())
1567 if (mmaShape[0] == 8) {
1568 if (*getMultiplicandAPtxType() == MMATypes::f16) {
1569 expectedA.emplace_back(2, f16x2Ty);
1570 expectedB.emplace_back(2, f16x2Ty);
1571 expectedResult.push_back(f16x2x4StructTy);
1572 expectedResult.push_back(f32x8StructTy);
1573 expectedC.emplace_back(4, f16x2Ty);
1574 expectedC.emplace_back(8, f32Ty);
1575 allowedShapes.push_back({8, 8, 4});
1577 if (*getMultiplicandAPtxType() == MMATypes::f64) {
1578 Type f64Ty = Float64Type::get(context);
1579 expectedA.emplace_back(1, f64Ty);
1580 expectedB.emplace_back(1, f64Ty);
1581 expectedC.emplace_back(2, f64Ty);
1582 expectedResult.emplace_back(LLVM::LLVMStructType::getLiteral(
1584 allowedShapes.push_back({8, 8, 4});
1587 expectedA.push_back({i32Ty});
1588 expectedB.push_back({i32Ty});
1589 expectedC.push_back({i32Ty, i32Ty});
1590 expectedResult.push_back(s32x2StructTy);
1592 allowedShapes.push_back({8, 8, 32});
1594 allowedShapes.push_back({8, 8, 16});
1598 std::string errorMessage;
1599 llvm::raw_string_ostream errorStream(errorMessage);
1602 if (expectedA.empty() || expectedB.empty() || expectedC.empty() ||
1603 !llvm::is_contained(allowedShapes, mmaShape)) {
1604 errorStream <<
"unimplemented variant for MMA shape <";
1605 llvm::interleaveComma(mmaShape, errorStream);
1611 std::array<StringRef, 3> operandNames{
"A",
"B",
"C"};
1612 for (
const auto &iter : llvm::enumerate(
1614 auto spec = this->getODSOperandIndexAndLength(iter.index());
1616 operand_type_begin() + spec.first +
1618 bool match = llvm::is_contained(iter.value(), operandTySeg);
1621 errorStream <<
"Could not match types for the "
1622 << operandNames[iter.index()]
1623 <<
" operands; expected one of ";
1624 for (
const auto &x : iter.value()) {
1625 errorStream << x.size() <<
"x" << x[0] <<
" ";
1627 errorStream <<
"but got ";
1628 llvm::interleaveComma(operandTySeg, errorStream);
1634 if (!llvm::any_of(expectedResult, [&](
Type expectedResultType) {
1635 return expectedResultType == getResult().getType();
1638 <<
"Could not match allowed types for the result; expected one of ";
1639 llvm::interleaveComma(expectedResult, errorStream);
1640 errorStream <<
" but got " << getResult().getType();
1648 if (!getIntOverflowBehavior())
1650 getIntOverflowBehaviorAttrName().strref() +
1655 if (!getSparseMetadata().
getType().isInteger(32)) {
1656 return emitOpError() <<
"sparse metadata must be i32 type";
1660 if (!getSparsitySelector().
getType().isInteger(32)) {
1661 return emitOpError() <<
"sparsity selector must be i32 type";
1673struct MMAOperandFragment {
1674 StringRef operandName;
1675 StringRef ptxTypeAttr;
1676 SmallVector<Value, 4> regs;
1677 explicit MMAOperandFragment(StringRef name, StringRef ptxTypeName)
1678 : operandName(name), ptxTypeAttr(ptxTypeName) {}
1685 p <<
" " << name <<
"[";
1704template <
typename Op>
1709 for (
unsigned fragIdx = 0; fragIdx < frags.size(); fragIdx++) {
1710 auto &frag = frags[fragIdx];
1711 auto varOperandSpec = op.getODSOperandIndexAndLength(fragIdx);
1712 for (
auto operandIdx = varOperandSpec.first;
1713 operandIdx < varOperandSpec.first + varOperandSpec.second;
1715 frag.regs.push_back(op.getOperand(operandIdx));
1716 if (fragIdx == 0 && operandIdx == varOperandSpec.first) {
1717 regTypes.push_back(op.getOperand(operandIdx).getType());
1721 regTypes.push_back(frag.regs[0].getType());
1723 std::optional<MMATypes> inferredType =
1724 MmaOp::inferOperandMMAType(regTypes.back(),
1727 ignoreAttrNames.push_back(frag.ptxTypeAttr);
1738 auto typeParser = [&]() {
1742 operandTypes.push_back(ty);
1748 if (operandTypes.size() != 3)
1750 "expected exactly 3 types");
1759 if (!attrs.
get(
"multiplicandAPtxType")) {
1760 if (
auto inferredType =
1761 MmaOp::inferOperandMMAType(operandTypes[0],
false)) {
1762 attrs.
set(
"multiplicandAPtxType", MMATypesAttr::get(ctx, *inferredType));
1765 if (!attrs.
get(
"multiplicandBPtxType")) {
1766 if (
auto inferredType =
1767 MmaOp::inferOperandMMAType(operandTypes[1],
false)) {
1768 attrs.
set(
"multiplicandBPtxType", MMATypesAttr::get(ctx, *inferredType));
1774template <
typename OpType>
1777 ScaleVecSize scaleVecSize,
1778 BlockScaleFormat blockScaleFormat,
1779 MMABlockScaleKind kind) {
1781 auto &properties =
result.getOrAddProperties<
typename OpType::Properties>();
1782 properties.setShape(
1784 properties.setScaleVecSize(ScaleVecSizeAttr::get(ctx, scaleVecSize));
1785 properties.setBlockScaleFormat(
1786 BlockScaleFormatAttr::get(ctx, blockScaleFormat));
1787 properties.setKind(MMABlockScaleKindAttr::get(ctx, kind));
1794 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes) {
1795 if (multiplicandPtxTypes) {
1796 result.addAttribute(
"multiplicandAPtxType",
1797 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[0]));
1798 result.addAttribute(
"multiplicandBPtxType",
1799 MMATypesAttr::get(ctx, (*multiplicandPtxTypes)[1]));
1801 if (
auto res = MmaOp::inferOperandMMAType(operandA[0].
getType(),
false))
1802 result.addAttribute(
"multiplicandAPtxType", MMATypesAttr::get(ctx, *res));
1803 if (
auto res = MmaOp::inferOperandMMAType(operandB[0].
getType(),
false))
1804 result.addAttribute(
"multiplicandBPtxType", MMATypesAttr::get(ctx, *res));
1809template <
typename OpTy>
1811 return *MmaOp::inferOperandMMAType(
1812 cast<LLVM::LLVMStructType>(op.getRes().getType()).getBody()[0],
1822 std::array<MMAOperandFragment, 3> frags{
1823 MMAOperandFragment(
"A", getMultiplicandAPtxTypeAttrName()),
1824 MMAOperandFragment(
"B", getMultiplicandBPtxTypeAttrName()),
1825 MMAOperandFragment(
"C",
"")};
1827 mlir::NVVM::MmaBlockScaleOp::getOperandSegmentSizeAttr()};
1832 for (
const auto &frag : frags)
1837 {getScaleAData(), getByteIdA(), getThreadIdA()});
1839 {getScaleBData(), getByteIdB(), getThreadIdB()});
1846 frags[1].regs[0].getType(),
1847 frags[2].regs[0].getType()},
1853ParseResult MmaBlockScaleOp::parse(
OpAsmParser &parser,
1855 struct LocalOperandFragment {
1856 std::optional<MMATypes> elemtype;
1857 SmallVector<OpAsmParser::UnresolvedOperand, 4> regs;
1861 std::array<LocalOperandFragment, 3> frags;
1890 for (
const auto &[idx, frag] : llvm::enumerate(frags)) {
1891 frag.elemtype = MmaOp::inferOperandMMAType(operandTypes[idx],
1894 .resolveOperands(frag.regs, operandTypes[idx], parser.
getNameLoc(),
1904 .resolveOperands(scaleAOperands, scaleTypes, parser.
getNameLoc(),
1914 result.addAttributes(namedAttributes);
1918 result.addTypes(resultTypes);
1919 result.addAttribute(MmaBlockScaleOp::getOperandSegmentSizeAttr(),
1921 static_cast<int32_t>(frags[0].regs.size()),
1922 static_cast<int32_t>(frags[1].regs.size()),
1923 static_cast<int32_t>(frags[2].regs.size()),
1934void MmaBlockScaleOp::build(
1939 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes,
1940 ScaleVecSize scaleVecSize, BlockScaleFormat blockScaleFormat,
1941 MMABlockScaleKind kind) {
1942 assert(
shape.size() == 3 &&
"expected shape to have size 3 (m, n, k)");
1945 blockScaleFormat, kind);
1947 result.addOperands(operandA);
1948 result.addOperands(operandB);
1949 result.addOperands(operandC);
1951 {scaleAData, byteIdA, threadIdA, scaleBData, byteIdB, threadIdB});
1954 multiplicandPtxTypes);
1956 result.addTypes(resultType);
1957 result.addAttribute(MmaBlockScaleOp::getOperandSegmentSizeAttr(),
1959 static_cast<int32_t>(operandA.size()),
1960 static_cast<int32_t>(operandB.size()),
1961 static_cast<int32_t>(operandC.size()),
1973 auto curOp = cast<NVVM::MmaBlockScaleOp>(op);
1977 for (
Value operand : curOp.getOperandA())
1979 for (
Value operand : curOp.getOperandB())
1981 for (
Value operand : curOp.getOperandC())
1985 args.push_back(mt.
lookupValue(curOp.getScaleAData()));
1986 args.push_back(mt.
lookupValue(curOp.getByteIdA()));
1987 args.push_back(mt.
lookupValue(curOp.getThreadIdA()));
1988 args.push_back(mt.
lookupValue(curOp.getScaleBData()));
1989 args.push_back(mt.
lookupValue(curOp.getByteIdB()));
1990 args.push_back(mt.
lookupValue(curOp.getThreadIdB()));
1992 unsigned intId = MmaBlockScaleOp::getIntrinsicID(
1993 curOp.getShape().getM(), curOp.getShape().getN(), curOp.getShape().getK(),
1994 *curOp.getMultiplicandAPtxType(), *curOp.getMultiplicandBPtxType(),
1996 curOp.getBlockScaleFormat(), curOp.getKind());
1998 return {intId, args};
2001LogicalResult MmaBlockScaleOp::verify() {
2007 if (m == 16 && n == 8 && k == 64) {
2008 if (getMultiplicandAPtxType() != NVVM::MMATypes::e2m1 ||
2009 getMultiplicandBPtxType() != NVVM::MMATypes::e2m1)
2011 "unsupported MMATypes attribute for mma.m16n8k64.(mxf4nvf4|mxf4)");
2012 if (getKind() == NVVM::MMABlockScaleKind::MXF4) {
2013 if (getScaleVecSize() != NVVM::ScaleVecSize::X2)
2015 "unsupported ScaleVecSize attribute for mma.m16n8k64.mxf4");
2016 if (getBlockScaleFormat() != NVVM::BlockScaleFormat::UE8M0)
2018 "unsupported BlockScaleFormat attribute for mma.m16n8k64.mxf4");
2019 }
else if (getKind() == NVVM::MMABlockScaleKind::MXF4NVF4) {
2020 if (!((getScaleVecSize() == NVVM::ScaleVecSize::X2 &&
2021 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0) ||
2022 (getScaleVecSize() == NVVM::ScaleVecSize::X4 &&
2023 (getBlockScaleFormat() == NVVM::BlockScaleFormat::UE4M3 ||
2024 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0))))
2026 "attributes for mma.m16n8k64.mxf4nvf4");
2030 }
else if (m == 16 && n == 8 && k == 32) {
2031 if (!(getKind() == NVVM::MMABlockScaleKind::MXF8F6F4 &&
2032 getScaleVecSize() == NVVM::ScaleVecSize::X1 &&
2033 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0))
2035 emitOpError(
"unsupported Kind, ScaleVecSize and BlockScaleFormat "
2036 "attributes for mma.m16n8k32");
2049 std::array<MMAOperandFragment, 3> frags{
2050 MMAOperandFragment(
"A", getMultiplicandAPtxTypeAttrName()),
2051 MMAOperandFragment(
"B", getMultiplicandBPtxTypeAttrName()),
2052 MMAOperandFragment(
"C",
"")};
2054 mlir::NVVM::MmaSpBlockScaleOp::getOperandSegmentSizeAttr()};
2059 for (
const auto &frag : frags)
2068 {getScaleAData(), getByteIdA(), getThreadIdA()});
2070 {getScaleBData(), getByteIdB(), getThreadIdB()});
2077 frags[1].regs[0].getType(),
2078 frags[2].regs[0].getType()},
2084ParseResult MmaSpBlockScaleOp::parse(
OpAsmParser &parser,
2086 struct LocalOperandFragment {
2087 std::optional<MMATypes> elemtype;
2088 SmallVector<OpAsmParser::UnresolvedOperand, 4> regs;
2092 std::array<LocalOperandFragment, 3> frags;
2128 for (
const auto &[idx, frag] : llvm::enumerate(frags)) {
2129 frag.elemtype = MmaOp::inferOperandMMAType(operandTypes[idx],
2132 .resolveOperands(frag.regs, operandTypes[idx], parser.
getNameLoc(),
2141 .resolveOperands(metadataOperands, i32Type, parser.
getNameLoc(),
2154 .resolveOperands(scaleAOperands, scaleTypes, parser.
getNameLoc(),
2164 result.addAttributes(namedAttributes);
2169 if (!
result.attributes.get(
"orderedMetadata"))
2172 result.addTypes(resultTypes);
2173 result.addAttribute(MmaSpBlockScaleOp::getOperandSegmentSizeAttr(),
2175 static_cast<int32_t>(frags[0].regs.size()),
2176 static_cast<int32_t>(frags[1].regs.size()),
2177 static_cast<int32_t>(frags[2].regs.size()),
2190void MmaSpBlockScaleOp::build(
2196 std::optional<std::array<MMATypes, 2>> multiplicandPtxTypes,
2197 ScaleVecSize scaleVecSize, BlockScaleFormat blockScaleFormat,
2198 MMABlockScaleKind kind) {
2199 assert(
shape.size() == 3 &&
"expected shape to have size 3 (m, n, k)");
2202 builder,
result,
shape, scaleVecSize, blockScaleFormat, kind);
2205 result.addOperands(operandA);
2206 result.addOperands(operandB);
2207 result.addOperands(operandC);
2208 result.addOperands({sparseMetadata, sparsitySelector, scaleAData, byteIdA,
2209 threadIdA, scaleBData, byteIdB, threadIdB});
2212 multiplicandPtxTypes);
2214 result.addTypes(resultType);
2215 result.addAttribute(MmaSpBlockScaleOp::getOperandSegmentSizeAttr(),
2217 static_cast<int32_t>(operandA.size()),
2218 static_cast<int32_t>(operandB.size()),
2219 static_cast<int32_t>(operandC.size()),
2233 auto curOp = cast<NVVM::MmaSpBlockScaleOp>(op);
2237 for (
Value operand : curOp.getOperandA())
2239 for (
Value operand : curOp.getOperandB())
2241 for (
Value operand : curOp.getOperandC())
2245 args.push_back(mt.
lookupValue(curOp.getSparseMetadata()));
2246 args.push_back(mt.
lookupValue(curOp.getSparsitySelector()));
2249 args.push_back(mt.
lookupValue(curOp.getScaleAData()));
2250 args.push_back(mt.
lookupValue(curOp.getByteIdA()));
2251 args.push_back(mt.
lookupValue(curOp.getThreadIdA()));
2252 args.push_back(mt.
lookupValue(curOp.getScaleBData()));
2253 args.push_back(mt.
lookupValue(curOp.getByteIdB()));
2254 args.push_back(mt.
lookupValue(curOp.getThreadIdB()));
2256 unsigned intId = MmaSpBlockScaleOp::getIntrinsicID(
2257 curOp.getShape().getM(), curOp.getShape().getN(), curOp.getShape().getK(),
2258 *curOp.getMultiplicandAPtxType(), *curOp.getMultiplicandBPtxType(),
2260 curOp.getBlockScaleFormat(), curOp.getKind());
2262 return {intId, args};
2265LogicalResult MmaSpBlockScaleOp::verify() {
2267 if (!getOrderedMetadata()) {
2268 return emitOpError(
"'orderedMetadata' attribute is mandatory");
2276 if (m == 16 && n == 8 && k == 128) {
2277 if (getMultiplicandAPtxType() != NVVM::MMATypes::e2m1 ||
2278 getMultiplicandBPtxType() != NVVM::MMATypes::e2m1)
2280 "unsupported MMATypes attribute for mma.m16n8k128.(mxf4nvf4|mxf4)");
2281 if (getKind() == NVVM::MMABlockScaleKind::MXF4) {
2282 if (getScaleVecSize() != NVVM::ScaleVecSize::X2)
2284 "unsupported ScaleVecSize attribute for mma.m16n8k128.mxf4");
2285 if (getBlockScaleFormat() != NVVM::BlockScaleFormat::UE8M0)
2287 "unsupported BlockScaleFormat attribute for mma.m16n8k128.mxf4");
2288 }
else if (getKind() == NVVM::MMABlockScaleKind::MXF4NVF4) {
2289 if (!((getScaleVecSize() == NVVM::ScaleVecSize::X2 &&
2290 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0) ||
2291 (getScaleVecSize() == NVVM::ScaleVecSize::X4 &&
2292 (getBlockScaleFormat() == NVVM::BlockScaleFormat::UE4M3 ||
2293 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0))))
2295 "attributes for mma.m16n8k128.mxf4nvf4");
2299 }
else if (m == 16 && n == 8 && k == 64) {
2300 if (!(getKind() == NVVM::MMABlockScaleKind::MXF8F6F4 &&
2301 getScaleVecSize() == NVVM::ScaleVecSize::X1 &&
2302 getBlockScaleFormat() == NVVM::BlockScaleFormat::UE8M0))
2304 emitOpError(
"unsupported Kind, ScaleVecSize and BlockScaleFormat "
2305 "attributes for mma.m16n8k64");
2312LogicalResult ShflOp::verify() {
2313 auto returnStructType = llvm::dyn_cast<LLVM::LLVMStructType>(
getType());
2315 auto verifyTypeError = [&](Twine desc,
Type expectedType,
2316 Type actualType) -> LogicalResult {
2317 return emitOpError(
"expected " + desc +
" to be of type ")
2318 << expectedType <<
" but got " << actualType <<
" instead";
2321 if (returnStructType) {
2322 if (!getReturnValueAndIsValid())
2323 return emitOpError(
"\"return_value_and_is_valid\" attribute must be "
2324 "specified when the return type is a struct type");
2326 if (returnStructType.getBody().size() != 2)
2327 return emitOpError(
"expected return type to be a two-element struct");
2330 auto resultType = returnStruct[0];
2331 if (resultType != getVal().
getType())
2332 return verifyTypeError(
"first element in the returned struct",
2333 getVal().
getType(), resultType);
2335 auto predicateType = returnStruct[1];
2336 if (!predicateType.isInteger(1))
2337 return verifyTypeError(
"second element in the returned struct",
2341 if (getReturnValueAndIsValid())
2342 return emitOpError(
"expected return type to be a two-element struct");
2345 return verifyTypeError(
"return type", getVal().
getType(),
getType());
2351ShflOp::inferReturnTypes(
MLIRContext *context, std::optional<Location> location,
2352 ShflOp::Adaptor adaptor,
2354 Type valType = adaptor.getVal().getType();
2355 if (adaptor.getReturnValueAndIsValid())
2356 inferredReturnTypes.push_back(LLVM::LLVMStructType::getLiteral(
2357 context, {valType, IntegerType::get(context, 1)}));
2359 inferredReturnTypes.push_back(valType);
2364 NVVM::MMAFrag frag,
int nRow,
2367 unsigned numberElements = 0;
2370 Type f16x2 = VectorType::get(2, builder.getF16Type());
2371 if (type == NVVM::MMATypes::f16) {
2372 elementType = f16x2;
2373 if (frag == NVVM::MMAFrag::a || frag == NVVM::MMAFrag::b)
2377 }
else if (type == NVVM::MMATypes::f32) {
2378 elementType = builder.getF32Type();
2380 }
else if (type == NVVM::MMATypes::f64) {
2381 elementType = builder.getF64Type();
2382 if (frag == NVVM::MMAFrag::a || frag == NVVM::MMAFrag::b)
2386 }
else if (type == NVVM::MMATypes::tf32) {
2387 elementType = builder.getI32Type();
2389 }
else if (type == NVVM::MMATypes::s8 || type == NVVM::MMATypes::u8) {
2390 elementType = builder.getI32Type();
2391 int parallelSize = 0;
2392 if (frag == NVVM::MMAFrag::a)
2393 parallelSize = nRow;
2394 if (frag == NVVM::MMAFrag::b)
2395 parallelSize = nCol;
2398 if (parallelSize == 16)
2401 else if (parallelSize == 8)
2403 else if (parallelSize == 32)
2405 }
else if (type == NVVM::MMATypes::s32) {
2406 elementType = builder.getI32Type();
2409 assert(numberElements != 0 && elementType !=
nullptr);
2410 return std::make_pair(elementType, numberElements);
2413static std::pair<mlir::Type, unsigned>
2417 if (frag == NVVM::MMAFrag::a) {
2420 }
else if (frag == NVVM::MMAFrag::b) {
2427 assert(nRow && nCol);
2431LogicalResult NVVM::WMMALoadOp::verify() {
2432 unsigned addressSpace =
2433 llvm::cast<LLVM::LLVMPointerType>(getPtr().
getType()).getAddressSpace();
2434 if (addressSpace != 0 && addressSpace != NVVMMemorySpace::Global &&
2435 addressSpace != NVVMMemorySpace::Shared)
2436 return emitOpError(
"expected source pointer in memory "
2439 if (NVVM::WMMALoadOp::getIntrinsicID(
getM(),
getN(), getK(), getLayout(),
2440 getEltype(), getFrag()) == 0)
2441 return emitOpError() <<
"invalid attribute combination";
2446 if (typeInfo.first == f64Ty && typeInfo.second == 1) {
2448 return emitOpError(
"expected destination type to be f64");
2452 Type dstType = LLVM::LLVMStructType::getLiteral(
2455 return emitOpError(
"expected destination type is a structure of ")
2456 << typeInfo.second <<
" elements of type " << typeInfo.first;
2460LogicalResult NVVM::WMMAStoreOp::verify() {
2461 unsigned addressSpace =
2462 llvm::cast<LLVM::LLVMPointerType>(getPtr().
getType()).getAddressSpace();
2463 if (addressSpace != 0 && addressSpace != NVVMMemorySpace::Global &&
2464 addressSpace != NVVMMemorySpace::Shared)
2465 return emitOpError(
"expected operands to be a source pointer in memory "
2468 if (NVVM::WMMAStoreOp::getIntrinsicID(
getM(),
getN(), getK(), getLayout(),
2470 return emitOpError() <<
"invalid attribute combination";
2473 if (getArgs().size() != typeInfo.second)
2474 return emitOpError() <<
"expected " << typeInfo.second <<
" data operands";
2475 if (llvm::any_of(getArgs(), [&typeInfo](
Value operands) {
2476 return operands.
getType() != typeInfo.first;
2478 return emitOpError() <<
"expected data operands of type " << typeInfo.first;
2482LogicalResult NVVM::WMMAMmaOp::verify() {
2483 if (NVVM::WMMAMmaOp::getIntrinsicID(
getM(),
getN(), getK(), getLayoutA(),
2484 getLayoutB(), getEltypeA(),
2486 return emitOpError() <<
"invalid attribute combination";
2494 arguments.append(typeInfoA.second, typeInfoA.first);
2495 arguments.append(typeInfoB.second, typeInfoB.first);
2496 arguments.append(typeInfoC.second, typeInfoC.first);
2497 unsigned numArgs = arguments.size();
2498 if (getArgs().size() != numArgs)
2499 return emitOpError() <<
"expected " << numArgs <<
" arguments";
2500 for (
unsigned i = 0; i < numArgs; i++) {
2501 if (getArgs()[i].
getType() != arguments[i])
2502 return emitOpError() <<
"expected argument " << i <<
" to be of type "
2505 Type dstType = LLVM::LLVMStructType::getLiteral(
2508 return emitOpError(
"expected destination type is a structure of ")
2509 << typeInfoC.second <<
" elements of type " << typeInfoC.first;
2513LogicalResult NVVM::LdMatrixOp::verify() {
2515 if (m == 8 && n == 8) {
2516 if (num != 1 && num != 2 && num != 4) {
2517 return emitOpError(
"expected num attribute to be 1, 2 or 4 for 8x8 "
2520 if (getEltType() != LdStMatrixEltType::B16) {
2521 return emitOpError(
"expected element type to be b16 for 8x8 matrix");
2523 }
else if (m == 8 && n == 16) {
2524 if (num != 1 && num != 2 && num != 4) {
2525 return emitOpError(
"expected num attribute to be 1, 2 or 4 for 8x16 "
2528 if (getLayout() != MMALayout::row) {
2529 return emitOpError(
"expected layout to be row for 8x16 matrix");
2531 if (getEltType() != LdStMatrixEltType::B8X16_B4X16_P64 &&
2532 getEltType() != LdStMatrixEltType::B8X16_B6X16_P32) {
2533 return emitOpError(
"expected element type to be b8x16.b4x16_p64 or "
2534 "b8x16.b6x16_p32 for 8x16 matrix");
2536 }
else if (m == 16 && n == 16) {
2537 if (num != 1 && num != 2) {
2538 return emitOpError(
"expected num attribute to be 1 or 2 for 16x16 "
2541 if (getLayout() != MMALayout::col) {
2542 return emitOpError(
"expected layout to be col for 16x16 matrix");
2544 if (getEltType() != LdStMatrixEltType::B8 &&
2545 getEltType() != LdStMatrixEltType::B8X16_B4X16_P64 &&
2546 getEltType() != LdStMatrixEltType::B8X16_B6X16_P32) {
2547 return emitOpError(
"expected element type to be b8, b8x16.b4x16_p64 or "
2548 "b8x16.b6x16_p32 for 16x16 matrix");
2551 return emitOpError(
"expected shape to be 8x8, 8x16 or 16x16");
2555 uint32_t numElements = (m == 16 && n == 16 ? num * 2 : num);
2556 if (numElements == 1 &&
getType() != i32)
2557 return emitOpError(
"expected destination type is i32");
2558 if (numElements == 2 || numElements == 4) {
2559 Type dstType = LLVM::LLVMStructType::getLiteral(
2562 return emitOpError(
"expected destination type is a structure of ")
2563 << numElements <<
" elements of type i32";
2569LogicalResult LdMatrixOp::inferReturnTypes(
2570 MLIRContext *context, std::optional<Location> location,
2572 uint32_t num = adaptor.getNum();
2573 uint32_t m = adaptor.getShape().getM();
2574 uint32_t n = adaptor.getShape().getN();
2575 uint32_t numElements = (m == 16 && n == 16) ? num * 2 : num;
2577 Type i32 = IntegerType::get(context, 32);
2578 if (numElements == 1)
2579 inferredReturnTypes.push_back(i32);
2581 inferredReturnTypes.push_back(LLVM::LLVMStructType::getLiteral(
2586LogicalResult NVVM::StMatrixOp::verify() {
2587 int numMatrix = getSources().size();
2588 if (numMatrix != 1 && numMatrix != 2 && numMatrix != 4)
2589 return emitOpError(
"expected num attribute to be 1, 2 or 4");
2592 if (m == 8 && n == 8) {
2593 if (getEltType() != NVVM::LdStMatrixEltType::B16) {
2594 return emitOpError(
"expected element type to be B16 for 8x8 matrix");
2596 }
else if (m == 16 && n == 8) {
2597 if (getEltType() != NVVM::LdStMatrixEltType::B8) {
2598 return emitOpError(
"expected element type to be B8 for 16x8 matrix");
2600 if (getLayout() != NVVM::MMALayout::col) {
2601 return emitOpError(
"expected layout to be col for 16x8 matrix");
2604 return emitOpError(
"expected shape to be 8x8 or 16x8");
2610LogicalResult NVVM::MovMatrixOp::verify() {
2612 if (m != 8 || n != 8)
2614 if (getLayout() != NVVM::MMALayout::col)
2616 if (getEltType() != NVVM::LdStMatrixEltType::B16)
2617 return emitOpError(
"expected element type to be b16");
2622 if (typeA == NVVM::WGMMATypes::tf32)
2624 if (typeA == NVVM::WGMMATypes::f16 || typeA == NVVM::WGMMATypes::bf16)
2626 if (typeA == NVVM::WGMMATypes::s8 || typeA == NVVM::WGMMATypes::u8)
2628 if (typeA == NVVM::WGMMATypes::e4m3 || typeA == NVVM::WGMMATypes::e5m2)
2630 if (typeA == NVVM::WGMMATypes::b1)
2636 NVVM::WGMMATypes typeA,
2637 NVVM::WGMMATypes typeB) {
2639 case NVVM::WGMMATypes::f16:
2640 if ((typeD == NVVM::WGMMATypes::f32 || typeD == NVVM::WGMMATypes::f16) &&
2641 typeB == NVVM::WGMMATypes::f16)
2644 case NVVM::WGMMATypes::tf32:
2645 if (typeD == NVVM::WGMMATypes::f32 && typeB == NVVM::WGMMATypes::tf32)
2648 case NVVM::WGMMATypes::u8:
2649 case NVVM::WGMMATypes::s8:
2650 if (typeD == NVVM::WGMMATypes::s32 &&
2651 (typeB == NVVM::WGMMATypes::u8 || typeB == NVVM::WGMMATypes::s8))
2654 case NVVM::WGMMATypes::b1:
2655 if (typeD == NVVM::WGMMATypes::s32 && typeB == NVVM::WGMMATypes::b1)
2658 case NVVM::WGMMATypes::bf16:
2659 if ((typeD == NVVM::WGMMATypes::f32 || typeD == NVVM::WGMMATypes::f16) &&
2660 typeB == NVVM::WGMMATypes::bf16)
2663 case NVVM::WGMMATypes::e4m3:
2664 case NVVM::WGMMATypes::e5m2:
2665 if ((typeD == NVVM::WGMMATypes::f32 || typeD == NVVM::WGMMATypes::f16) &&
2666 (typeB == NVVM::WGMMATypes::e5m2 || typeB == NVVM::WGMMATypes::e4m3))
2669 case WGMMATypes::f32:
2670 case WGMMATypes::s32:
2671 llvm_unreachable(
"unsupported input types");
2679 72, 80, 88, 96, 104, 112, 120, 128,
2680 136, 144, 152, 160, 168, 176, 184, 192,
2681 200, 208, 216, 224, 232, 240, 248, 256};
2683 80, 96, 112, 128, 144, 160,
2684 176, 192, 208, 224, 240, 256};
2686 case WGMMATypes::f16:
2687 case WGMMATypes::tf32:
2688 case WGMMATypes::bf16:
2689 case WGMMATypes::e4m3:
2690 case WGMMATypes::e5m2:
2691 if (llvm::is_contained(allowedN, sizeN))
2694 case WGMMATypes::u8:
2695 case WGMMATypes::s8:
2696 case WGMMATypes::b1:
2697 if (llvm::is_contained(allowedNshort, sizeN))
2700 case WGMMATypes::f32:
2701 case WGMMATypes::s32:
2702 llvm_unreachable(
"unsupported input types");
2708LogicalResult NVVM::WgmmaMmaAsyncOp::verify() {
2709 Value outValue = getResults();
2710 auto stype = dyn_cast<LLVM::LLVMStructType>(outValue.
getType());
2712 return emitOpError() <<
"expected results to be struct";
2713 int outputSize = stype.getBody().size();
2714 WGMMATypes typeD = getTypeD();
2715 WGMMATypes typeA = getTypeA();
2716 WGMMATypes typeB = getTypeB();
2718 for (
Type t : stype.getBody()) {
2719 if (t != stype.getBody().front())
2721 <<
"all elements in struct must be same type but there is " << t;
2724 if (typeD != WGMMATypes::f32 && typeD != WGMMATypes::f16 &&
2725 typeD != WGMMATypes::s32) {
2726 return emitOpError() <<
"does not support the given output type " << typeD;
2728 if (typeD == WGMMATypes::s32 &&
2729 (getScaleA() == WGMMAScaleIn::neg || getScaleB() == WGMMAScaleIn::neg)) {
2730 return emitOpError() <<
"has s32 output, scaleA and scaleB cannot be neg";
2734 return emitOpError() << typeD <<
" += " << typeA <<
" * " << typeB
2735 <<
", it is not supported.";
2745 return emitOpError() <<
"shape 'k' must be " << allowedK.value()
2746 <<
" for input type " << typeA;
2750 return emitOpError() <<
"has input type " << typeA <<
" n is set to "
2751 <<
getShape().getN() <<
", it is not supported.";
2758 if ((typeA != WGMMATypes::f16 && typeA != WGMMATypes::bf16) &&
2759 (getLayoutA() == mlir::NVVM::MMALayout::col ||
2760 getLayoutB() == mlir::NVVM::MMALayout::row)) {
2762 <<
"given layouts layout_a = " << getLayoutA()
2763 <<
" and layout_b = " << getLayoutB() <<
" for input types " << typeA
2765 <<
" requires transpose. However, this is only supported for: "
2766 << MMATypes::f16 <<
" and " << MMATypes::bf16;
2770 int expectedOutput = 0;
2771 if (typeD == WGMMATypes::f32 || typeD == WGMMATypes::s32)
2772 expectedOutput =
getShape().getN() / 2;
2773 if (typeD == WGMMATypes::f16)
2774 expectedOutput =
getShape().getN() / 4;
2775 if (outputSize != expectedOutput) {
2776 return emitOpError() <<
"results " << expectedOutput
2777 <<
", however output struct has " << outputSize
2781 if (typeD != WGMMATypes::s32 &&
2782 getSatfinite().value_or(NVVM::MMAIntOverflow::wrapped) ==
2783 NVVM::MMAIntOverflow::satfinite) {
2785 <<
" `satfinite` can be only used with s32 accumulator, however "
2786 "the current accumulator is "
2793std::string NVVM::WgmmaMmaAsyncOp::getPtx() {
2796 bool isF16 = getTypeA() == WGMMATypes::f16 || getTypeA() == WGMMATypes::bf16;
2798 StringRef outputTypeName = stringifyWGMMATypes(getTypeD());
2800 int expectedOutputRegisters = 0;
2801 if (getTypeD() == WGMMATypes::f16)
2802 expectedOutputRegisters =
getShape().getN() / 4;
2804 expectedOutputRegisters =
getShape().getN() / 2;
2807 llvm::raw_string_ostream ss(ptx);
2812 << ((expectedOutputRegisters * 2) + 2)
2814 "wgmma.mma_async.sync.aligned.m"
2815 << m <<
"n" << n <<
"k" << k <<
"." << outputTypeName <<
"." << getTypeA()
2816 <<
"." << getTypeB();
2817 if (getSatfinite().value_or(NVVM::MMAIntOverflow::wrapped) ==
2818 NVVM::MMAIntOverflow::satfinite)
2822 for (; regCnt < expectedOutputRegisters; ++regCnt) {
2823 ss <<
"$" << regCnt;
2824 if (regCnt != expectedOutputRegisters - 1)
2830 regCnt = (regCnt * 2);
2831 ss <<
" $" << (regCnt) <<
","
2832 <<
" $" << (regCnt + 1) <<
","
2834 if (getTypeD() != WGMMATypes::s32) {
2835 ss <<
", $" << (regCnt + 3) <<
", $" << (regCnt + 4);
2839 ss <<
", $" << (regCnt + 5) <<
", $" << (regCnt + 6);
2846bool NVVM::WgmmaMmaAsyncOp::getAsmValues(
2850 bool isF16 = getTypeA() == WGMMATypes::f16 || getTypeA() == WGMMATypes::bf16;
2857 asmValues.push_back({makeConstantI32(rewriter,
static_cast<int>(getScaleD())),
2859 if (getTypeD() != WGMMATypes::s32) {
2860 asmValues.push_back(
2861 {makeConstantI32(rewriter,
2862 getScaleA() == NVVM::WGMMAScaleIn::neg ? -1 : 1),
2864 asmValues.push_back(
2865 {makeConstantI32(rewriter,
2866 getScaleB() == NVVM::WGMMAScaleIn::neg ? -1 : 1),
2870 asmValues.push_back(
2871 {makeConstantI32(rewriter,
static_cast<int>(getLayoutA())),
2873 asmValues.push_back(
2874 {makeConstantI32(rewriter, 1 -
static_cast<int>(getLayoutB())),
2880LogicalResult NVVM::FenceProxyOp::verify() {
2881 if (getKind() == NVVM::ProxyKind::async_shared && !getSpace().has_value()) {
2882 return emitOpError() <<
"async_shared fence requires space attribute";
2884 if (getKind() != NVVM::ProxyKind::async_shared && getSpace().has_value()) {
2885 return emitOpError() <<
"only async_shared fence can have space attribute";
2890LogicalResult NVVM::FenceProxyAcquireOp::verify() {
2891 if (getFromProxy() != NVVM::ProxyKind::GENERIC)
2892 return emitOpError(
"uni-directional proxies only support generic for "
2893 "from_proxy attribute");
2895 if (getToProxy() != NVVM::ProxyKind::TENSORMAP)
2896 return emitOpError(
"uni-directional proxies only support tensormap "
2897 "for to_proxy attribute");
2901LogicalResult NVVM::FenceProxyReleaseOp::verify() {
2902 if (getFromProxy() != NVVM::ProxyKind::GENERIC)
2903 return emitOpError(
"uni-directional proxies only support generic for "
2904 "from_proxy attribute");
2906 if (getToProxy() != NVVM::ProxyKind::TENSORMAP)
2907 return emitOpError(
"uni-directional proxies only support tensormap "
2908 "for to_proxy attribute");
2912LogicalResult NVVM::FenceProxySyncRestrictOp::verify() {
2913 if (getFromProxy() != NVVM::ProxyKind::GENERIC)
2914 return emitOpError(
"only generic is support for from_proxy attribute");
2916 if (getToProxy() != NVVM::ProxyKind::async)
2917 return emitOpError(
"only async is supported for to_proxy attribute");
2921LogicalResult NVVM::SetMaxRegisterOp::verify() {
2922 if (getRegCount() % 8)
2923 return emitOpError(
"new register size must be multiple of 8");
2924 if (getRegCount() < 24 || getRegCount() > 256)
2925 return emitOpError(
"new register size must be in between 24 to 256");
2929LogicalResult NVVM::Tcgen05CpOp::verify() {
2930 auto mc = getMulticast();
2932 using SH = Tcgen05CpShape;
2933 using MC = Tcgen05CpMulticast;
2935 case SH::SHAPE_128x256b:
2936 case SH::SHAPE_128x128b:
2937 case SH::SHAPE_4x256b:
2939 return emitError(
"Invalid multicast type for tcgen05.cp Op");
2941 case SH::SHAPE_64x128b:
2942 if (mc != MC::WARPX2_01_23 && mc != MC::WARPX2_02_13)
2943 return emitError(
"Shape 64x128b requires multicast warpx2_01_23 or "
2944 "warpx2_02_13 for tcgen05.cp Op");
2946 case SH::SHAPE_32x128b:
2947 if (mc != MC::WARPX4)
2949 "Shape 32x128b requires multicast warpx4 for tcgen05.cp Op");
2955LogicalResult NVVM::MatchSyncOp::verify() {
2956 if (getKind() == NVVM::MatchSyncKind::all) {
2957 auto type = llvm::dyn_cast<LLVM::LLVMStructType>(
getType());
2958 if (!type || type.getBody().size() != 2 ||
2959 !type.getBody()[0].isInteger(32) || !type.getBody()[1].isInteger(1)) {
2960 return emitOpError(
"match.sync 'all' returns a two element struct with "
2961 "first element as i32 and second element as i1");
2964 if (!
getType().isInteger(32)) {
2965 return emitOpError(
"match.sync 'any' returns an i32");
2971LogicalResult MatchSyncOp::inferReturnTypes(
2972 MLIRContext *context, std::optional<Location> location,
2974 if (adaptor.getKind() == NVVM::MatchSyncKind::all)
2975 inferredReturnTypes.push_back(LLVM::LLVMStructType::getLiteral(
2977 {IntegerType::get(context, 32), IntegerType::get(context, 1)}));
2979 inferredReturnTypes.push_back(IntegerType::get(context, 32));
2983LogicalResult NVVM::VoteSyncOp::verify() {
2984 if (getKind() == NVVM::VoteSyncKind::ballot) {
2985 if (!
getType().isInteger(32)) {
2986 return emitOpError(
"vote.sync 'ballot' returns an i32");
2989 if (!
getType().isInteger(1)) {
2990 return emitOpError(
"vote.sync 'any', 'all' and 'uni' returns an i1");
2996LogicalResult VoteSyncOp::inferReturnTypes(
2997 MLIRContext *context, std::optional<Location> location,
2999 unsigned width = adaptor.getKind() == NVVM::VoteSyncKind::ballot ? 32 : 1;
3000 inferredReturnTypes.push_back(IntegerType::get(context, width));
3004LogicalResult NVVM::PrefetchOp::verify() {
3005 using MemSpace = NVVM::NVVMMemorySpace;
3006 using CacheLevel = NVVM::PrefetchCacheLevel;
3008 unsigned addressSpace =
3009 llvm::cast<LLVM::LLVMPointerType>(getAddr().
getType()).getAddressSpace();
3010 std::optional<NVVM::CacheEvictionPriority> evictPriority = getEvictPriority();
3011 std::optional<NVVM::PrefetchCacheLevel> cacheLevel = getCacheLevel();
3013 if (getTensormap() && cacheLevel)
3014 return emitOpError(
"cannot specify both tensormap and cache level");
3016 if (getTensormap()) {
3017 if (addressSpace != MemSpace::Generic &&
3018 addressSpace != MemSpace::Constant) {
3020 "prefetch tensormap requires a generic or constant pointer");
3023 if (evictPriority) {
3025 "prefetch tensormap does not support eviction priority");
3028 if (getInParamSpace() && addressSpace != MemSpace::Generic) {
3030 "in_param_space can only be specified for a generic pointer");
3033 }
else if (cacheLevel) {
3034 if (addressSpace != MemSpace::Generic && addressSpace != MemSpace::Global &&
3035 addressSpace != MemSpace::Local) {
3036 return emitOpError(
"prefetch to cache level requires a generic, global, "
3037 "or local pointer");
3041 if (*cacheLevel != CacheLevel::L1) {
3043 "unsupported cache level, the only supported uniform "
3044 "cache level is L1");
3047 if (addressSpace != MemSpace::Generic) {
3049 "prefetch to uniform cache requires a generic pointer");
3053 if (evictPriority) {
3054 if (*cacheLevel != CacheLevel::L2)
3056 "cache eviction priority supported only for cache level L2");
3058 if (addressSpace != MemSpace::Global)
3059 return emitOpError(
"cache eviction priority requires a global pointer");
3061 if (*evictPriority != NVVM::CacheEvictionPriority::EvictNormal &&
3062 *evictPriority != NVVM::CacheEvictionPriority::EvictLast)
3064 "unsupported cache eviction priority, only evict_last and "
3065 "evict_normal are supported");
3069 return emitOpError(
"predicate supported only on prefetch tensormap");
3073 "requires specification of either cache level or tensormap");
3079LogicalResult NVVM::ClusterLaunchControlQueryCancelOp::verify() {
3080 switch (getQueryType()) {
3081 case NVVM::ClusterLaunchControlQueryType::IS_CANCELED:
3083 return emitOpError(
"is_canceled query type returns an i1");
3085 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_X:
3086 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_Y:
3087 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_Z:
3088 if (!
getType().isInteger(32)) {
3089 return emitOpError(
"get_first_cta_id_x, get_first_cta_id_y, "
3090 "get_first_cta_id_z query types return an i32");
3097LogicalResult ClusterLaunchControlQueryCancelOp::inferReturnTypes(
3098 MLIRContext *context, std::optional<Location> location,
3099 ClusterLaunchControlQueryCancelOp::Adaptor adaptor,
3102 adaptor.getQueryType() == NVVM::ClusterLaunchControlQueryType::IS_CANCELED
3105 inferredReturnTypes.push_back(IntegerType::get(context, width));
3109LogicalResult NVVM::ReduxOp::verify() {
3112 if (!reduxType.
isF32()) {
3114 return emitOpError(
"abs attribute is supported only for f32 type");
3116 return emitOpError(
"nan attribute is supported only for f32 type");
3119 NVVM::ReductionKind kind = getKind();
3121 case NVVM::ReductionKind::ADD:
3122 case NVVM::ReductionKind::AND:
3123 case NVVM::ReductionKind::OR:
3124 case NVVM::ReductionKind::XOR:
3125 case NVVM::ReductionKind::MAX:
3126 case NVVM::ReductionKind::MIN:
3127 case NVVM::ReductionKind::UMAX:
3128 case NVVM::ReductionKind::UMIN:
3131 << kind <<
"' reduction kind unsupported with " << reduxType
3132 <<
" type. Only supported type is 'i32'.";
3134 case NVVM::ReductionKind::FMIN:
3135 case NVVM::ReductionKind::FMAX:
3136 if (!reduxType.isF32())
3138 << kind <<
"' reduction kind unsupported with " << reduxType
3139 <<
" type. Only supported type is 'f32'.";
3146LogicalResult NVVM::TensormapReplaceOp::verify() {
3147 auto ord = getOrd();
3148 Value newVal = getNewValue();
3149 auto newValAttr = getNewValueAttr();
3150 auto fieldName = stringifyEnum(getField());
3152 if (ord && !llvm::is_contained({NVVM::TensormapField::BOX_DIM,
3153 NVVM::TensormapField::GLOBAL_DIM,
3154 NVVM::TensormapField::GLOBAL_STRIDE,
3155 NVVM::TensormapField::ELEMENT_STRIDE},
3157 return emitOpError(
"ordinal is not supported for ")
3158 << fieldName <<
" field";
3160 auto invalidNewVal = [&](llvm::Twine type) -> std::string {
3161 return llvm::Twine(
"new_value must be specified and must be an " + type +
3162 " for " + llvm::Twine(fieldName) +
" field")
3166 auto invalidNewValAttr = [&]() -> std::string {
3167 return (llvm::Twine(
3168 "new_value_attr must be specified and must be a valid ") +
3169 llvm::Twine(fieldName) +
" attribute for " + fieldName +
" field")
3173 switch (getField()) {
3174 case NVVM::TensormapField::GLOBAL_ADDRESS:
3178 case NVVM::TensormapField::RANK:
3182 case NVVM::TensormapField::GLOBAL_STRIDE:
3184 return emitOpError(
"ordinal is required for global_stride field");
3188 case NVVM::TensormapField::BOX_DIM:
3189 case NVVM::TensormapField::GLOBAL_DIM:
3190 case NVVM::TensormapField::ELEMENT_STRIDE:
3193 << stringifyEnum(getField()) <<
" field";
3197 case NVVM::TensormapField::ELEMTYPE:
3198 if (!(newValAttr && llvm::isa<TensormapElemtypeAttr>(*newValAttr)))
3201 case NVVM::TensormapField::INTERLEAVE_LAYOUT:
3202 if (!(newValAttr && llvm::isa<TensormapInterleaveLayoutAttr>(*newValAttr)))
3205 case NVVM::TensormapField::SWIZZLE_MODE:
3206 if (!(newValAttr && llvm::isa<TensormapSwizzleModeAttr>(*newValAttr)))
3209 case NVVM::TensormapField::SWIZZLE_ATOMICITY:
3210 if (!(newValAttr && llvm::isa<TensormapSwizzleAtomicityAttr>(*newValAttr)))
3213 case NVVM::TensormapField::FILL_MODE:
3214 if (!(newValAttr && llvm::isa<TensormapFillModeAttr>(*newValAttr)))
3222template <
typename OpType>
3224 mlir::NVVM::FPRoundingMode rndMode = op.getRnd();
3225 mlir::NVVM::SaturationMode satMode = op.getSat();
3226 bool isFTZ = op.getFtz();
3229 mlir::Type opBaseType = isa<VectorType>(opType)
3230 ? cast<VectorType>(opType).getElementType()
3233 if (opBaseType.
isF64() && (satMode != NVVM::SaturationMode::NONE || isFTZ))
3234 return op.emitOpError(
"FTZ and saturation are not supported for "
3235 "additions/subtractions involving f64 type");
3237 if (opBaseType.
isF16() && !(rndMode == NVVM::FPRoundingMode::RN ||
3238 rndMode == NVVM::FPRoundingMode::NONE))
3239 return op.emitOpError(
"only RN rounding mode is supported for f16 and "
3240 "vector<2xf16> additions/subtractions");
3242 if (opBaseType.
isBF16()) {
3243 if (rndMode != NVVM::FPRoundingMode::RN &&
3244 rndMode != NVVM::FPRoundingMode::NONE)
3245 return op.emitOpError(
"only RN rounding mode is supported for bf16 and "
3246 "vector<2xbf16> additions/subtractions");
3247 if (satMode != NVVM::SaturationMode::NONE || isFTZ)
3248 return op.emitOpError(
"FTZ and saturation are not supported for bf16 and "
3249 "vector<2xbf16> additions/subtractions");
3256 if (opBaseType.
isF16() && isFTZ && satMode == NVVM::SaturationMode::NONE)
3257 return op.emitOpError(
"FTZ with no saturation is not supported for f16 and "
3258 "vector<2xf16> additions/subtractions");
3267LogicalResult NVVM::FmaOp::verify() {
3268 auto opType = getRes().getType();
3269 mlir::NVVM::FPRoundingMode rndMode = getRnd();
3270 mlir::NVVM::SaturationMode satMode = getSat();
3271 bool isFTZ = getFtz();
3272 bool isRelu = getRelu();
3273 bool hasOOB = getOob();
3275 auto getBaseFType = [](
Type type) ->
Type {
3276 if (isa<VectorType>(type))
3277 return cast<VectorType>(type).getElementType();
3281 auto opBaseType = getBaseFType(opType);
3283 if (rndMode == NVVM::FPRoundingMode::NONE)
3284 return emitOpError(
"rounding mode must be specified");
3286 if (isRelu && satMode == NVVM::SaturationMode::SAT)
3287 return emitOpError(
"relu and saturation are not supported together");
3289 if (hasOOB && (satMode == NVVM::SaturationMode::SAT || isFTZ))
3290 return emitOpError(
"oob is not supported with saturation or FTZ");
3292 if (!(opBaseType.isF16() || opBaseType.isBF16()) && (isRelu || hasOOB))
3293 return emitOpError(
"relu and oob are only supported for f16 and bf16");
3295 if (opBaseType.isF64() && (satMode != NVVM::SaturationMode::NONE || isFTZ))
3296 return emitOpError(
"FTZ and saturation are not supported for f64 type");
3298 if (opBaseType.isF16() && rndMode != NVVM::FPRoundingMode::RN)
3300 "only RN rounding mode is supported for f16 and vector<2xf16>");
3302 if (opBaseType.isBF16()) {
3303 if (rndMode != NVVM::FPRoundingMode::RN)
3305 "only RN rounding mode is supported for bf16 and vector<2xbf16>");
3306 if (satMode != NVVM::SaturationMode::NONE || isFTZ)
3308 "FTZ and saturation are not supported for bf16 and vector<2xbf16>");
3314LogicalResult NVVM::SqrtOp::verify() {
3315 if (getRnd() == NVVM::FPRoundingMode::NONE)
3316 return emitOpError(
"rounding mode cannot be None");
3318 if (getRes().
getType().isF64() && getFtz())
3319 return emitOpError(
"FTZ is not supported for f64");
3324LogicalResult NVVM::DivFOp::verify() {
3325 bool isApprox = getApprox();
3326 bool isFull = getFull();
3327 bool isF64 = getRes().getType().isF64();
3328 bool isFtz = getFtz();
3329 NVVM::FPRoundingMode rndMode = getRnd();
3331 if (isApprox && isFull)
3332 return emitOpError(
"'approx' and 'full' are mutually exclusive");
3334 if (isApprox || isFull) {
3336 return emitOpError(
"'approx' and 'full' forms are f32-only");
3337 if (rndMode != NVVM::FPRoundingMode::NONE)
3339 "'approx' and 'full' forms do not accept a rounding mode");
3344 if (rndMode == NVVM::FPRoundingMode::NONE)
3345 return emitOpError(
"rounding mode cannot be None for the rounded divide");
3347 return emitOpError(
"FTZ is not supported for f64");
3358 unsigned sizeInBits,
3360 field = builder.CreateZExtOrBitCast(field, builder.getInt32Ty());
3362 unsigned mask = (sizeInBits < 32 ? ((1u << sizeInBits) - 1) : 0xffffffffu);
3363 if (mask != 0xffffffffu)
3364 field = builder.CreateAnd(field, builder.getInt32(mask));
3366 field = builder.CreateZExtOrBitCast(field, builder.getInt64Ty());
3367 field = builder.CreateShl(field, start);
3369 return builder.CreateOr(
result, field);
3372void Tcgen05MmaSmemDescOp::createSmemDescriptor(
Operation &op,
3374 llvm::IRBuilderBase &builder) {
3375 auto thisOp = cast<NVVM::Tcgen05MmaSmemDescOp>(op);
3376 llvm::Value *smemDesc = builder.getInt64(0);
3381 builder, smemDesc, mt.
lookupValue(thisOp.getLeadingDimOffset()), 14, 16);
3383 builder, smemDesc, mt.
lookupValue(thisOp.getStrideDimOffset()), 14, 32);
3389 builder, smemDesc, mt.
lookupValue(thisOp.getLeadingDimMode()), 1, 52);
3393 mt.
mapValue(thisOp.getRes()) = smemDesc;
3400std::string NVVM::MBarrierInitOp::getPtx() {
3402 return isShared ? std::string(
"mbarrier.init.shared.b64 [%0], %1;")
3403 : std::string(
"mbarrier.init.b64 [%0], %1;");
3406std::string NVVM::MBarrierArriveExpectTxOp::getPtx() {
3409 ? std::string(
"mbarrier.arrive.expect_tx.shared.b64 _, [%0], %1;")
3410 : std::string(
"mbarrier.arrive.expect_tx.b64 _, [%0], %1;");
3413std::string NVVM::MBarrierTryWaitParityOp::getPtx() {
3415 llvm::StringRef space = isShared ?
".shared" :
"";
3417 return llvm::formatv(
"{\n\t"
3418 ".reg .pred P1; \n\t"
3420 "mbarrier.try_wait.parity{0}.b64 P1, [%0], %1, %2; \n\t"
3421 "@P1 bra.uni DONE; \n\t"
3422 "bra.uni LAB_WAIT; \n\t"
3439 LLVM::FNegOp::create(rewriter, loc, op.getRhs().getType(), op.getRhs());
3442 op.getRnd(), op.getSat(), op.getFtz());
3458 auto thisOp = cast<NVVM::BarrierOp>(op);
3459 llvm::Value *barrierId = thisOp.getBarrierId()
3461 : builder.getInt32(0);
3462 llvm::Intrinsic::ID id;
3464 if (thisOp.getNumberOfThreads()) {
3465 id = llvm::Intrinsic::nvvm_barrier_cta_sync_aligned_count;
3466 args.push_back(mt.
lookupValue(thisOp.getNumberOfThreads()));
3468 id = llvm::Intrinsic::nvvm_barrier_cta_sync_aligned_all;
3470 return {id, std::move(args)};
3475 auto thisOp = cast<NVVM::BarrierReductionOp>(op);
3476 llvm::Intrinsic::ID id;
3477 switch (thisOp.getReductionOp()) {
3478 case NVVM::BarrierReduction::AND:
3479 id = llvm::Intrinsic::nvvm_barrier_cta_red_and_aligned_all;
3481 case NVVM::BarrierReduction::OR:
3482 id = llvm::Intrinsic::nvvm_barrier_cta_red_or_aligned_all;
3484 case NVVM::BarrierReduction::POPC:
3485 id = llvm::Intrinsic::nvvm_barrier_cta_red_popc_aligned_all;
3488 llvm::Value *barrierId = thisOp.getBarrierId()
3490 : builder.getInt32(0);
3493 builder.CreateICmpNE(mt.
lookupValue(thisOp.getReductionPredicate()),
3494 builder.getInt32(0))};
3495 return {id, std::move(args)};
3500 llvm::IRBuilderBase &builder) {
3501 auto thisOp = cast<NVVM::CosOp>(op);
3502 llvm::Intrinsic::ID
id = thisOp.getFtz()
3503 ? llvm::Intrinsic::nvvm_cos_approx_ftz_f
3504 : llvm::Intrinsic::nvvm_cos_approx_f;
3510 llvm::IRBuilderBase &builder) {
3511 auto thisOp = cast<NVVM::SinOp>(op);
3512 llvm::Intrinsic::ID
id = thisOp.getFtz()
3513 ? llvm::Intrinsic::nvvm_sin_approx_ftz_f
3514 : llvm::Intrinsic::nvvm_sin_approx_f;
3520 llvm::IRBuilderBase &builder) {
3521 auto thisOp = cast<NVVM::Log2Op>(op);
3522 llvm::Intrinsic::ID
id = thisOp.getFtz()
3523 ? llvm::Intrinsic::nvvm_lg2_approx_ftz_f
3524 : llvm::Intrinsic::nvvm_lg2_approx_f;
3530 llvm::IRBuilderBase &builder) {
3531 auto thisOp = cast<NVVM::Ex2Op>(op);
3532 llvm::Intrinsic::ID
id = thisOp.getFtz()
3533 ? llvm::Intrinsic::nvvm_ex2_approx_ftz
3534 : llvm::Intrinsic::nvvm_ex2_approx;
3540 llvm::IRBuilderBase &builder) {
3541 auto thisOp = cast<NVVM::RsqrtOp>(op);
3542 Type t = thisOp.getRes().getType();
3543 bool isFtz = thisOp.getFtz();
3545 llvm::Intrinsic::ID
id = [&] {
3547 return isFtz ? llvm::Intrinsic::nvvm_rsqrt_approx_ftz_f
3548 : llvm::Intrinsic::nvvm_rsqrt_approx_f;
3551 return isFtz ? llvm::Intrinsic::nvvm_rsqrt_approx_ftz_d
3552 : llvm::Intrinsic::nvvm_rsqrt_approx_d;
3560 llvm::IRBuilderBase &builder) {
3561 auto thisOp = cast<NVVM::SqrtOp>(op);
3562 Type t = thisOp.getRes().getType();
3563 NVVM::FPRoundingMode rndMode = thisOp.getRnd();
3564 bool isFtz = thisOp.getFtz();
3568 unsigned rndIndex =
static_cast<unsigned>(rndMode) - 1;
3570 static constexpr llvm::Intrinsic::ID f32IDs[] = {
3571 llvm::Intrinsic::nvvm_sqrt_rn_f,
3572 llvm::Intrinsic::nvvm_sqrt_rm_f,
3573 llvm::Intrinsic::nvvm_sqrt_rp_f,
3574 llvm::Intrinsic::nvvm_sqrt_rz_f,
3576 static constexpr llvm::Intrinsic::ID f32FTZIDs[] = {
3577 llvm::Intrinsic::nvvm_sqrt_rn_ftz_f,
3578 llvm::Intrinsic::nvvm_sqrt_rm_ftz_f,
3579 llvm::Intrinsic::nvvm_sqrt_rp_ftz_f,
3580 llvm::Intrinsic::nvvm_sqrt_rz_ftz_f,
3582 static constexpr llvm::Intrinsic::ID f64IDs[] = {
3583 llvm::Intrinsic::nvvm_sqrt_rn_d,
3584 llvm::Intrinsic::nvvm_sqrt_rm_d,
3585 llvm::Intrinsic::nvvm_sqrt_rp_d,
3586 llvm::Intrinsic::nvvm_sqrt_rz_d,
3589 llvm::Intrinsic::ID
id =
3590 t.
isF32() ? (isFtz ? f32FTZIDs[rndIndex] : f32IDs[rndIndex])
3598 llvm::IRBuilderBase &builder) {
3599 auto thisOp = cast<NVVM::SqrtApproxOp>(op);
3600 llvm::Intrinsic::ID
id = thisOp.getFtz()
3601 ? llvm::Intrinsic::nvvm_sqrt_approx_ftz_f
3602 : llvm::Intrinsic::nvvm_sqrt_approx_f;
3608 llvm::IRBuilderBase &builder) {
3609 auto thisOp = cast<NVVM::DivFOp>(op);
3610 bool isFtz = thisOp.getFtz();
3612 llvm::Intrinsic::ID id;
3614 if (thisOp.getApprox()) {
3615 id = isFtz ? llvm::Intrinsic::nvvm_div_approx_ftz_f
3616 : llvm::Intrinsic::nvvm_div_approx_f;
3617 }
else if (thisOp.getFull()) {
3620 id = isFtz ? llvm::Intrinsic::nvvm_div_full_ftz
3621 : llvm::Intrinsic::nvvm_div_full;
3624 unsigned rndIndex =
static_cast<unsigned>(thisOp.getRnd()) - 1;
3626 static constexpr llvm::Intrinsic::ID f32IDs[] = {
3627 llvm::Intrinsic::nvvm_div_rn_f,
3628 llvm::Intrinsic::nvvm_div_rm_f,
3629 llvm::Intrinsic::nvvm_div_rp_f,
3630 llvm::Intrinsic::nvvm_div_rz_f,
3632 static constexpr llvm::Intrinsic::ID f32FTZIDs[] = {
3633 llvm::Intrinsic::nvvm_div_rn_ftz_f,
3634 llvm::Intrinsic::nvvm_div_rm_ftz_f,
3635 llvm::Intrinsic::nvvm_div_rp_ftz_f,
3636 llvm::Intrinsic::nvvm_div_rz_ftz_f,
3638 static constexpr llvm::Intrinsic::ID f64IDs[] = {
3639 llvm::Intrinsic::nvvm_div_rn_d,
3640 llvm::Intrinsic::nvvm_div_rm_d,
3641 llvm::Intrinsic::nvvm_div_rp_d,
3642 llvm::Intrinsic::nvvm_div_rz_d,
3644 Type t = thisOp.getRes().getType();
3645 id = t.
isF32() ? (isFtz ? f32FTZIDs[rndIndex] : f32IDs[rndIndex])
3655 llvm::IRBuilderBase &builder) {
3656 auto thisOp = cast<NVVM::PMEventOp>(op);
3660 llvm::Value *maskVal;
3661 if (
auto eventAttr = thisOp.getEventIdAttr()) {
3662 uint16_t mask =
static_cast<uint16_t
>(1u << eventAttr.getInt());
3663 maskVal = llvm::ConstantInt::get(i16Ty, mask);
3666 llvm::ConstantInt::get(i16Ty, thisOp.getMaskedEventIdAttr().getValue());
3669 return {llvm::Intrinsic::nvvm_pm_event_mask, {maskVal}};
3674 auto thisOp = cast<NVVM::MBarrierInitOp>(op);
3676 llvm::Intrinsic::ID
id = isShared ? llvm::Intrinsic::nvvm_mbarrier_init_shared
3677 : llvm::Intrinsic::nvvm_mbarrier_init;
3682 args.push_back(mt.
lookupValue(thisOp.getCount()));
3684 return {id, std::move(args)};
3689 auto thisOp = cast<NVVM::MBarrierInvalOp>(op);
3691 llvm::Intrinsic::ID
id = isShared
3692 ? llvm::Intrinsic::nvvm_mbarrier_inval_shared
3693 : llvm::Intrinsic::nvvm_mbarrier_inval;
3700 auto thisOp = cast<NVVM::MBarrierExpectTxOp>(op);
3703 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3706 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3708 static constexpr llvm::Intrinsic::ID IDs[] = {
3709 llvm::Intrinsic::nvvm_mbarrier_expect_tx_scope_cta_space_cta,
3710 llvm::Intrinsic::nvvm_mbarrier_expect_tx_scope_cta_space_cluster,
3711 llvm::Intrinsic::nvvm_mbarrier_expect_tx_scope_cluster_space_cta,
3712 llvm::Intrinsic::nvvm_mbarrier_expect_tx_scope_cluster_space_cluster};
3717 args.push_back(mt.
lookupValue(thisOp.getTxcount()));
3719 return {IDs[
index], std::move(args)};
3724 auto thisOp = cast<NVVM::MBarrierCompleteTxOp>(op);
3727 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3730 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3732 static constexpr llvm::Intrinsic::ID IDs[] = {
3733 llvm::Intrinsic::nvvm_mbarrier_complete_tx_scope_cta_space_cta,
3734 llvm::Intrinsic::nvvm_mbarrier_complete_tx_scope_cta_space_cluster,
3735 llvm::Intrinsic::nvvm_mbarrier_complete_tx_scope_cluster_space_cta,
3736 llvm::Intrinsic::nvvm_mbarrier_complete_tx_scope_cluster_space_cluster};
3741 args.push_back(mt.
lookupValue(thisOp.getTxcount()));
3743 return {IDs[
index], std::move(args)};
3748 auto thisOp = cast<NVVM::MBarrierArriveOp>(op);
3751 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3754 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3756 static constexpr llvm::Intrinsic::ID IDs[] = {
3757 llvm::Intrinsic::nvvm_mbarrier_arrive_scope_cta_space_cta,
3758 llvm::Intrinsic::nvvm_mbarrier_arrive_scope_cta_space_cluster,
3759 llvm::Intrinsic::nvvm_mbarrier_arrive_scope_cluster_space_cta,
3760 llvm::Intrinsic::nvvm_mbarrier_arrive_scope_cluster_space_cluster};
3761 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3762 llvm::Intrinsic::nvvm_mbarrier_arrive_relaxed_scope_cta_space_cta,
3763 llvm::Intrinsic::nvvm_mbarrier_arrive_relaxed_scope_cta_space_cluster,
3764 llvm::Intrinsic::nvvm_mbarrier_arrive_relaxed_scope_cluster_space_cta,
3766 nvvm_mbarrier_arrive_relaxed_scope_cluster_space_cluster};
3767 auto id = thisOp.getRelaxed() ? relaxedIDs[
index] : IDs[
index];
3771 llvm::Value *mbar = mt.
lookupValue(thisOp.getAddr());
3778 bool hasCount =
static_cast<bool>(thisOp.getCount());
3780 (
id == llvm::Intrinsic::nvvm_mbarrier_arrive_scope_cta_space_cta))
3781 return {llvm::Intrinsic::nvvm_mbarrier_arrive_shared, {mbar}};
3785 llvm::Value *count =
3787 : llvm::ConstantInt::get(llvm::Type::getInt32Ty(ctx), 1);
3788 return {id, {mbar, count}};
3793 auto thisOp = cast<NVVM::MBarrierArriveDropOp>(op);
3796 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3799 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3801 static constexpr llvm::Intrinsic::ID IDs[] = {
3802 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_scope_cta_space_cta,
3803 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_scope_cta_space_cluster,
3804 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_scope_cluster_space_cta,
3805 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_scope_cluster_space_cluster};
3806 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3807 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_relaxed_scope_cta_space_cta,
3809 nvvm_mbarrier_arrive_drop_relaxed_scope_cta_space_cluster,
3811 nvvm_mbarrier_arrive_drop_relaxed_scope_cluster_space_cta,
3813 nvvm_mbarrier_arrive_drop_relaxed_scope_cluster_space_cluster};
3814 auto id = thisOp.getRelaxed() ? relaxedIDs[
index] : IDs[
index];
3818 llvm::Value *mbar = mt.
lookupValue(thisOp.getAddr());
3824 bool hasCount =
static_cast<bool>(thisOp.getCount());
3825 llvm::Value *count =
3827 : llvm::ConstantInt::get(llvm::Type::getInt32Ty(ctx), 1);
3829 return {id, {mbar, count}};
3832bool MBarrierArriveExpectTxOp::getAsmValues(
3839 for (
auto val : getOperands())
3847 auto thisOp = cast<NVVM::MBarrierArriveExpectTxOp>(op);
3850 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3853 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3856 static constexpr llvm::Intrinsic::ID IDs[] = {
3857 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_scope_cta_space_cta,
3858 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_scope_cta_space_cluster,
3859 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_scope_cluster_space_cta,
3860 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_scope_cluster_space_cluster};
3861 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3862 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_relaxed_scope_cta_space_cta,
3863 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_relaxed_scope_cta_space_cluster,
3864 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_relaxed_scope_cluster_space_cta,
3865 llvm::Intrinsic::nvvm_mbarrier_arrive_expect_tx_relaxed_scope_cluster_space_cluster};
3867 auto id = thisOp.getRelaxed() ? relaxedIDs[
index] : IDs[
index];
3870 llvm::Value *txcount = mt.
lookupValue(thisOp.getTxcount());
3871 llvm::Value *mbar = mt.
lookupValue(thisOp.getAddr());
3876 return {id, {mbar, txcount}};
3881 auto thisOp = cast<NVVM::MBarrierArriveDropExpectTxOp>(op);
3884 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3887 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isClusterSpace ? 1 : 0);
3890 static constexpr llvm::Intrinsic::ID IDs[] = {
3891 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_scope_cta_space_cta,
3892 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_scope_cta_space_cluster,
3893 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_scope_cluster_space_cta,
3894 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_scope_cluster_space_cluster};
3895 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3896 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_relaxed_scope_cta_space_cta,
3897 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_relaxed_scope_cta_space_cluster,
3898 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_relaxed_scope_cluster_space_cta,
3899 llvm::Intrinsic::nvvm_mbarrier_arrive_drop_expect_tx_relaxed_scope_cluster_space_cluster};
3901 auto id = thisOp.getRelaxed() ? relaxedIDs[
index] : IDs[
index];
3904 llvm::Value *txcount = mt.
lookupValue(thisOp.getTxcount());
3905 llvm::Value *mbar = mt.
lookupValue(thisOp.getAddr());
3910 return {id, {mbar, txcount}};
3915 auto thisOp = cast<NVVM::MBarrierArriveNocompleteOp>(op);
3917 llvm::Intrinsic::ID
id =
3918 isShared ? llvm::Intrinsic::nvvm_mbarrier_arrive_noComplete_shared
3919 : llvm::Intrinsic::nvvm_mbarrier_arrive_noComplete;
3923 args.push_back(mt.
lookupValue(thisOp.getCount()));
3925 return {id, std::move(args)};
3930 auto thisOp = cast<NVVM::MBarrierArriveDropNocompleteOp>(op);
3932 llvm::Intrinsic::ID
id =
3933 isShared ? llvm::Intrinsic::nvvm_mbarrier_arrive_drop_noComplete_shared
3934 : llvm::Intrinsic::nvvm_mbarrier_arrive_drop_noComplete;
3938 args.push_back(mt.
lookupValue(thisOp.getCount()));
3940 return {id, std::move(args)};
3945 auto thisOp = cast<NVVM::MBarrierTestWaitOp>(op);
3946 bool isPhaseParity = thisOp.getStateOrPhase().getType().isInteger(32);
3947 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3950 size_t index = ((isClusterScope ? 1 : 0) << 1) | (isPhaseParity ? 1 : 0);
3953 static constexpr llvm::Intrinsic::ID IDs[] = {
3954 llvm::Intrinsic::nvvm_mbarrier_test_wait_scope_cta_space_cta,
3955 llvm::Intrinsic::nvvm_mbarrier_test_wait_parity_scope_cta_space_cta,
3956 llvm::Intrinsic::nvvm_mbarrier_test_wait_scope_cluster_space_cta,
3957 llvm::Intrinsic::nvvm_mbarrier_test_wait_parity_scope_cluster_space_cta};
3958 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3959 llvm::Intrinsic::nvvm_mbarrier_test_wait_relaxed_scope_cta_space_cta,
3960 llvm::Intrinsic::nvvm_mbarrier_test_wait_parity_relaxed_scope_cta_space_cta,
3961 llvm::Intrinsic::nvvm_mbarrier_test_wait_relaxed_scope_cluster_space_cta,
3962 llvm::Intrinsic::nvvm_mbarrier_test_wait_parity_relaxed_scope_cluster_space_cta};
3964 auto id = thisOp.getRelaxed() ? relaxedIDs[
index] : IDs[
index];
3967 llvm::Value *mbar = mt.
lookupValue(thisOp.getAddr());
3968 llvm::Value *input = mt.
lookupValue(thisOp.getStateOrPhase());
3973 return {id, {mbar, input}};
3978 auto thisOp = cast<NVVM::MBarrierTryWaitOp>(op);
3979 bool isPhaseParity = thisOp.getStateOrPhase().getType().isInteger(32);
3980 bool isClusterScope = thisOp.getScope() == NVVM::MemScopeKind::CLUSTER;
3981 bool hasTicks =
static_cast<bool>(thisOp.getTicks());
3985 size_t index = ((hasTicks ? 1 : 0) << 2) | ((isClusterScope ? 1 : 0) << 1) |
3986 (isPhaseParity ? 1 : 0);
3989 static constexpr llvm::Intrinsic::ID IDs[] = {
3990 llvm::Intrinsic::nvvm_mbarrier_try_wait_scope_cta_space_cta,
3991 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_scope_cta_space_cta,
3992 llvm::Intrinsic::nvvm_mbarrier_try_wait_scope_cluster_space_cta,
3993 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_scope_cluster_space_cta,
3994 llvm::Intrinsic::nvvm_mbarrier_try_wait_tl_scope_cta_space_cta,
3995 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_tl_scope_cta_space_cta,
3996 llvm::Intrinsic::nvvm_mbarrier_try_wait_tl_scope_cluster_space_cta,
3997 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_tl_scope_cluster_space_cta};
3998 static constexpr llvm::Intrinsic::ID relaxedIDs[] = {
3999 llvm::Intrinsic::nvvm_mbarrier_try_wait_relaxed_scope_cta_space_cta,
4000 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_relaxed_scope_cta_space_cta,
4001 llvm::Intrinsic::nvvm_mbarrier_try_wait_relaxed_scope_cluster_space_cta,
4002 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_relaxed_scope_cluster_space_cta,
4003 llvm::Intrinsic::nvvm_mbarrier_try_wait_tl_relaxed_scope_cta_space_cta,
4004 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_tl_relaxed_scope_cta_space_cta,
4005 llvm::Intrinsic::nvvm_mbarrier_try_wait_tl_relaxed_scope_cluster_space_cta,
4006 llvm::Intrinsic::nvvm_mbarrier_try_wait_parity_tl_relaxed_scope_cluster_space_cta};
4008 auto id = thisOp.getRelaxed() ? relaxedIDs[
index] : IDs[
index];
4011 llvm::Value *mbar = mt.
lookupValue(thisOp.getAddr());
4018 args.push_back(mbar);
4019 args.push_back(mt.
lookupValue(thisOp.getStateOrPhase()));
4021 args.push_back(mt.
lookupValue(thisOp.getTicks()));
4023 return {id, std::move(args)};
4028 auto thisOp = cast<NVVM::CpAsyncMBarrierArriveOp>(op);
4031 llvm::Intrinsic::ID id;
4032 if (thisOp.getNoinc()) {
4033 id = isShared ? llvm::Intrinsic::nvvm_cp_async_mbarrier_arrive_noinc_shared
4034 : llvm::Intrinsic::nvvm_cp_async_mbarrier_arrive_noinc;
4036 id = isShared ? llvm::Intrinsic::nvvm_cp_async_mbarrier_arrive_shared
4037 : llvm::Intrinsic::nvvm_cp_async_mbarrier_arrive;
4045 llvm::IRBuilderBase &builder) {
4046 auto thisOp = cast<NVVM::MovMatrixOp>(op);
4047 return {llvm::Intrinsic::nvvm_movmatrix_sync_aligned_m8n8_trans_b16,
4051#define CP_ASYNC_ID_IMPL(mod, size, suffix) \
4052 llvm::Intrinsic::nvvm_cp_async_##mod##_shared_global_##size##suffix
4054#define GET_CP_ASYNC_ID(mod, size, has_cpsize) \
4055 has_cpsize ? CP_ASYNC_ID_IMPL(mod, size, _s) : CP_ASYNC_ID_IMPL(mod, size, )
4060 llvm::Intrinsic::ID id;
4062 auto cpAsyncOp = cast<NVVM::CpAsyncOp>(op);
4063 bool hasCpSize =
static_cast<bool>(cpAsyncOp.getCpSize());
4064 switch (cpAsyncOp.getSize()) {
4072 id = (cpAsyncOp.getModifier() == NVVM::LoadCacheModifierKind::CG)
4077 llvm_unreachable(
"Invalid copy size in CpAsyncOp.");
4081 args.push_back(mt.
lookupValue(cpAsyncOp.getDst()));
4082 args.push_back(mt.
lookupValue(cpAsyncOp.getSrc()));
4084 args.push_back(mt.
lookupValue(cpAsyncOp.getCpSize()));
4091 auto thisOp = cast<NVVM::CpAsyncBulkPrefetchOp>(op);
4093 llvm::Intrinsic::ID
id = llvm::Intrinsic::nvvm_cp_async_bulk_prefetch_L2;
4096 args.push_back(mt.
lookupValue(thisOp.getSrcMem()));
4100 const bool hasCacheHint =
static_cast<bool>(cacheHint);
4101 llvm::Value *i64Unused =
4102 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.
getLLVMContext()), 0);
4103 args.push_back(hasCacheHint ? mt.
lookupValue(cacheHint) : i64Unused);
4104 args.push_back(builder.getInt1(hasCacheHint));
4106 return {id, std::move(args)};
4111 auto thisOp = cast<NVVM::CpAsyncBulkGlobalToSharedClusterOp>(op);
4115 args.push_back(mt.
lookupValue(thisOp.getDstMem()));
4117 args.push_back(mt.
lookupValue(thisOp.getSrcMem()));
4121 mlir::Value multicastMask = thisOp.getMulticastMask();
4122 const bool hasMulticastMask =
static_cast<bool>(multicastMask);
4125 llvm::Value *i16Unused = llvm::ConstantInt::get(builder.getInt16Ty(), 0);
4126 args.push_back(hasMulticastMask ? mt.
lookupValue(multicastMask)
4132 const bool hasCacheHint =
static_cast<bool>(cacheHint);
4133 llvm::Value *i64Unused = llvm::ConstantInt::get(builder.getInt64Ty(), 0);
4134 args.push_back(hasCacheHint ? mt.
lookupValue(cacheHint) : i64Unused);
4138 args.push_back(builder.getInt1(hasMulticastMask));
4139 args.push_back(builder.getInt1(hasCacheHint));
4141 llvm::Intrinsic::ID
id =
4143 ? llvm::Intrinsic::nvvm_cp_async_bulk_global_to_shared_cta
4144 : llvm::Intrinsic::nvvm_cp_async_bulk_global_to_shared_cluster;
4146 return {id, std::move(args)};
4151 auto thisOp = cast<NVVM::CpAsyncBulkSharedCTAToGlobalOp>(op);
4153 llvm::Intrinsic::ID
id =
4154 llvm::Intrinsic::nvvm_cp_async_bulk_shared_cta_to_global;
4157 args.push_back(mt.
lookupValue(thisOp.getDstMem()));
4158 args.push_back(mt.
lookupValue(thisOp.getSrcMem()));
4162 const bool hasCacheHint =
static_cast<bool>(cacheHint);
4163 llvm::Value *i64Unused =
4164 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.
getLLVMContext()), 0);
4165 args.push_back(hasCacheHint ? mt.
lookupValue(cacheHint) : i64Unused);
4166 args.push_back(builder.getInt1(hasCacheHint));
4169 if (
mlir::Value byteMask = thisOp.getByteMask()) {
4171 id = llvm::Intrinsic::nvvm_cp_async_bulk_shared_cta_to_global_bytemask;
4174 return {id, std::move(args)};
4177bool CpAsyncBulkTensorGlobalToSharedClusterOp::getAsmValues(
4184 for (
auto val : getOperands())
4191CpAsyncBulkTensorGlobalToSharedClusterOp::getIntrinsicIDAndArgs(
4193 auto thisOp = cast<NVVM::CpAsyncBulkTensorGlobalToSharedClusterOp>(op);
4194 const bool isCTAOnly = thisOp.getIsCTAOnly();
4198 args.push_back(mt.
lookupValue(thisOp.getDstMem()));
4200 args.push_back(mt.
lookupValue(thisOp.getTmaDescriptor()));
4210 const bool hasMC =
static_cast<bool>(mcMask);
4211 llvm::Value *i16Zero =
4212 llvm::ConstantInt::get(llvm::Type::getInt16Ty(mt.
getLLVMContext()), 0);
4216 const bool hasCacheHint =
static_cast<bool>(cacheHint);
4217 llvm::Value *i64Zero =
4218 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.
getLLVMContext()), 0);
4224 thisOp.getGroup() ? (
static_cast<int32_t
>(*thisOp.getGroup()) + 1) : 0;
4226 llvm::ConstantInt::get(llvm::Type::getInt32Ty(mt.
getLLVMContext()), val);
4230 args.push_back(hasMC ? mt.
lookupValue(mcMask) : i16Zero);
4231 args.push_back(hasCacheHint ? mt.
lookupValue(cacheHint) : i64Zero);
4232 args.push_back(builder.getInt1(hasMC));
4233 args.push_back(builder.getInt1(hasCacheHint));
4237 args.push_back(hasCacheHint ? mt.
lookupValue(cacheHint) : i64Zero);
4238 args.push_back(builder.getInt1(hasCacheHint));
4241 constexpr size_t numDims = 5;
4242 constexpr size_t numModes = 5;
4243 using rowTy = std::array<llvm::Intrinsic::ID, numDims + 1>;
4244 using TableTy = std::array<rowTy, numModes>;
4245 static constexpr TableTy IDTable{
4246 {{
notIntrinsic, llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_1d,
4247 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_2d,
4248 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_3d,
4249 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_4d,
4250 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_5d},
4252 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_3d,
4253 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_4d,
4254 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_5d},
4256 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_3d,
4257 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_4d,
4258 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_5d},
4260 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_128_3d,
4261 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_128_4d,
4262 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_im2col_w_128_5d},
4264 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_tile_gather4_2d}}};
4266 static constexpr TableTy IDTableCTA{
4268 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_1d,
4269 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_2d,
4270 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_3d,
4271 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_4d,
4272 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_5d},
4274 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_3d,
4275 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_4d,
4276 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_5d},
4278 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_3d,
4279 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_4d,
4280 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_5d},
4282 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_128_3d,
4283 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_128_4d,
4284 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_im2col_w_128_5d},
4286 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_g2s_cta_tile_gather4_2d}}};
4289 (getMaxEnumValForTMALoadMode() == std::size(IDTable) - 1) &&
4290 (getMaxEnumValForTMALoadMode() == std::size(IDTableCTA) - 1),
4291 "TMALoadModes must match number of rows in IDTable and IDTableCTA");
4292 size_t mode =
static_cast<size_t>(thisOp.getMode());
4293 size_t dim = thisOp.getCoordinates().size();
4294 auto id = isCTAOnly ? IDTableCTA[mode][dim] : IDTable[mode][dim];
4296 "Invalid intrinsic for CpAsyncBulkTensorGlobalToSharedClusterOp.");
4298 return {id, std::move(args)};
4303 auto thisOp = cast<NVVM::CpAsyncBulkTensorPrefetchOp>(op);
4307 args.push_back(mt.
lookupValue(thisOp.getTmaDescriptor()));
4309 for (
auto v : thisOp.getCoordinates())
4311 for (
auto v : thisOp.getIm2colOffsets())
4315 const bool hasCacheHint =
static_cast<bool>(cacheHint);
4316 llvm::Value *i64Unused =
4317 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.
getLLVMContext()), 0);
4318 args.push_back(hasCacheHint ? mt.
lookupValue(cacheHint) : i64Unused);
4319 args.push_back(builder.getInt1(hasCacheHint));
4321 const unsigned NI = llvm::Intrinsic::not_intrinsic;
4322 static constexpr llvm::Intrinsic::ID IDTable[][6] = {
4323 {NI, llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_1d,
4324 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_2d,
4325 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_3d,
4326 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_4d,
4327 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_5d},
4329 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_3d,
4330 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_4d,
4331 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_5d},
4333 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_3d,
4334 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_4d,
4335 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_5d},
4337 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_128_3d,
4338 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_128_4d,
4339 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_im2col_w_128_5d},
4340 {NI, NI, NI, NI, NI,
4341 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_prefetch_tile_gather4_2d}};
4343 static_assert(getMaxEnumValForTMALoadMode() == std::size(IDTable) - 1,
4344 "TMALoadModes must match number of rows in IDTable");
4345 size_t mode =
static_cast<size_t>(thisOp.getMode());
4346 size_t dim = thisOp.getCoordinates().size();
4347 llvm::Intrinsic::ID
id = IDTable[mode][dim];
4348 if (
id == llvm::Intrinsic::not_intrinsic)
4349 llvm_unreachable(
"Invalid intrinsic for CpAsyncBulkTensorPrefetchOp.");
4351 return {id, std::move(args)};
4355CpAsyncBulkTensorSharedCTAToGlobalOp::getIntrinsicIDAndArgs(
4357 auto thisOp = cast<NVVM::CpAsyncBulkTensorSharedCTAToGlobalOp>(op);
4361 args.push_back(mt.
lookupValue(thisOp.getSrcMem()));
4362 args.push_back(mt.
lookupValue(thisOp.getTmaDescriptor()));
4364 for (
auto v : thisOp.getCoordinates())
4368 const bool hasCacheHint =
static_cast<bool>(cacheHint);
4369 llvm::Value *i64Unused =
4370 llvm::ConstantInt::get(llvm::Type::getInt64Ty(mt.
getLLVMContext()), 0);
4371 args.push_back(hasCacheHint ? mt.
lookupValue(cacheHint) : i64Unused);
4372 args.push_back(builder.getInt1(hasCacheHint));
4374 const unsigned NI = llvm::Intrinsic::not_intrinsic;
4375 static constexpr llvm::Intrinsic::ID IDTable[][6] = {
4376 {NI, llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_1d,
4377 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_2d,
4378 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_3d,
4379 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_4d,
4380 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_5d},
4381 {NI, NI, NI, llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_im2col_3d,
4382 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_im2col_4d,
4383 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_im2col_5d},
4384 {NI, NI, NI, NI, NI,
4385 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_s2g_tile_scatter4_2d}};
4387 static_assert(getMaxEnumValForTMAStoreMode() == std::size(IDTable) - 1,
4388 "TMAStoreModes must match number of rows in IDTable");
4389 size_t mode =
static_cast<size_t>(thisOp.getMode());
4390 size_t dim = thisOp.getCoordinates().size();
4391 llvm::Intrinsic::ID
id = IDTable[mode][dim];
4392 if (
id == llvm::Intrinsic::not_intrinsic)
4394 "Invalid intrinsic for CpAsyncBulkTensorSharedCTAToGlobalOp.");
4396 return {id, std::move(args)};
4401 auto thisOp = cast<NVVM::CpAsyncBulkTensorReduceOp>(op);
4409 args.push_back(mt.
lookupValue(thisOp.getSrcMem()));
4410 args.push_back(mt.
lookupValue(thisOp.getTmaDescriptor()));
4412 for (
Value v : thisOp.getCoordinates())
4416 const bool hasCacheHint =
static_cast<bool>(cacheHint);
4417 llvm::Value *i64ZeroValue =
4418 llvm::ConstantInt::get(llvm::Type::getInt64Ty(ctx), 0);
4419 args.push_back(hasCacheHint ? mt.
lookupValue(cacheHint) : i64ZeroValue);
4420 args.push_back(builder.getInt1(hasCacheHint));
4422 const llvm::Intrinsic::ID
notIntrinsic = llvm::Intrinsic::not_intrinsic;
4424 constexpr unsigned numRedKinds = 8;
4425 constexpr unsigned numLayouts = 2;
4426 constexpr unsigned maxDim = 5;
4427 using row = std::array<llvm::Intrinsic::ID, maxDim + 1>;
4428 using layoutTable = std::array<row, numLayouts>;
4429 using fullTable = std::array<layoutTable, numRedKinds>;
4430 static constexpr fullTable IDTable{
4433 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_1d,
4434 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_2d,
4435 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_3d,
4436 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_4d,
4437 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_tile_5d}},
4439 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_im2col_3d,
4440 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_im2col_4d,
4441 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_add_im2col_5d}}}},
4444 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_1d,
4445 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_2d,
4446 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_3d,
4447 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_4d,
4448 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_tile_5d}},
4450 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_im2col_3d,
4451 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_im2col_4d,
4452 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_min_im2col_5d}}}},
4455 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_1d,
4456 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_2d,
4457 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_3d,
4458 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_4d,
4459 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_tile_5d}},
4461 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_im2col_3d,
4462 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_im2col_4d,
4463 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_max_im2col_5d}}}},
4466 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_1d,
4467 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_2d,
4468 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_3d,
4469 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_4d,
4470 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_tile_5d}},
4472 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_im2col_3d,
4473 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_im2col_4d,
4474 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_inc_im2col_5d}}}},
4477 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_1d,
4478 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_2d,
4479 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_3d,
4480 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_4d,
4481 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_tile_5d}},
4483 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_im2col_3d,
4484 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_im2col_4d,
4485 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_dec_im2col_5d}}}},
4488 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_1d,
4489 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_2d,
4490 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_3d,
4491 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_4d,
4492 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_tile_5d}},
4494 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_im2col_3d,
4495 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_im2col_4d,
4496 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_and_im2col_5d}}}},
4499 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_1d,
4500 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_2d,
4501 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_3d,
4502 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_4d,
4503 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_tile_5d}},
4505 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_im2col_3d,
4506 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_im2col_4d,
4507 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_or_im2col_5d}}}},
4510 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_1d,
4511 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_2d,
4512 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_3d,
4513 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_4d,
4514 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_tile_5d}},
4516 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_im2col_3d,
4517 llvm::Intrinsic::nvvm_cp_async_bulk_tensor_reduce_xor_im2col_4d,
4519 nvvm_cp_async_bulk_tensor_reduce_xor_im2col_5d}}}}}};
4521 static_assert(getMaxEnumValForTMAReduxKind() == std::size(IDTable) - 1,
4522 "TMAReduxKinds must match number of rows in IDTable");
4524 size_t redKind =
static_cast<size_t>(thisOp.getRedKind());
4525 size_t mode =
static_cast<size_t>(thisOp.getMode());
4526 size_t dim = thisOp.getCoordinates().size();
4528 assert(redKind < IDTable.size() &&
4529 "Invalid redKind for CpAsyncBulkTensorReduceOp");
4530 assert(mode < IDTable[redKind].size() &&
4531 "Invalid mode for CpAsyncBulkTensorReduceOp");
4532 assert(dim < IDTable[redKind][mode].size() &&
4533 "Invalid dim for CpAsyncBulkTensorReduceOp");
4535 llvm::Intrinsic::ID intrinsicID = IDTable[redKind][mode][dim];
4538 "Invalid intrinsic for CpAsyncBulkTensorReduceOp.");
4540 return {intrinsicID, std::move(args)};
4545#define CVT_F2TF32_ID_IMPL(rnd, relu, sf) \
4546 hasRelu ? llvm::Intrinsic::nvvm_f2tf32_##rnd##relu##sf \
4547 : llvm::Intrinsic::nvvm_f2tf32_##rnd##sf
4549#define GET_CVT_F2TF32_ID(rnd, relu, sf) \
4550 hasSatFinite ? CVT_F2TF32_ID_IMPL(rnd, relu, sf) \
4551 : CVT_F2TF32_ID_IMPL(rnd, relu, )
4554ConvertFloatToTF32Op::getIntrinsicID(NVVM::FPRoundingMode rnd,
4555 NVVM::SaturationMode sat,
bool hasRelu) {
4556 using RndMode = NVVM::FPRoundingMode;
4557 bool hasSatFinite = (sat == NVVM::SaturationMode::SATFINITE);
4566 llvm_unreachable(
"Invalid RoundingMode for CvtFloatToTF32Op");
4571ConvertF32x2ToF4x2Op::getIntrinsicIDAndArgs(NVVM::ConvertF32x2ToF4x2Op op,
4573 llvm::IRBuilderBase &builder) {
4578 bool hasRelu = op.getRelu();
4580 llvm::Intrinsic::ID intId =
4581 hasRelu ? llvm::Intrinsic::nvvm_ff_to_e2m1x2_rn_relu_satfinite
4582 : llvm::Intrinsic::nvvm_ff_to_e2m1x2_rn_satfinite;
4584 return {intId, std::move(args)};
4587#define GET_F32x2_TO_F6x2_ID(type, has_relu) \
4588 has_relu ? llvm::Intrinsic::nvvm_ff_to_##type##_rn_relu_satfinite \
4589 : llvm::Intrinsic::nvvm_ff_to_##type##_rn_satfinite
4591llvm::Intrinsic::ID ConvertF32x2ToF6x2Op::getIntrinsicID(
mlir::Type dstTy,
4594 .Case([&](mlir::Float6E2M3FNType) {
4597 .Case([&](mlir::Float6E3M2FNType) {
4601 llvm_unreachable(
"Invalid conversion in ConvertF32x2ToF6x2Op");
4602 return llvm::Intrinsic::not_intrinsic;
4607ConvertF16x2ToF4x2Op::getIntrinsicIDAndArgs(NVVM::ConvertF16x2ToF4x2Op &op,
4609 llvm::IRBuilderBase &builder) {
4611 bool hasRelu = op.getRelu();
4613 llvm::Intrinsic::ID intId = llvm::Intrinsic::not_intrinsic;
4615 if (llvm::isa<mlir::Float4E2M1FNType>(dstTy))
4616 intId = hasRelu ? llvm::Intrinsic::nvvm_f16x2_to_e2m1x2_rn_relu_satfinite
4617 : llvm::Intrinsic::nvvm_f16x2_to_e2m1x2_rn_satfinite;
4622 return {intId, std::move(args)};
4626ConvertBF16x2ToF4x2Op::getIntrinsicIDAndArgs(NVVM::ConvertBF16x2ToF4x2Op &op,
4628 llvm::IRBuilderBase &builder) {
4630 bool hasRelu = op.getRelu();
4632 llvm::Intrinsic::ID intId = llvm::Intrinsic::not_intrinsic;
4634 if (llvm::isa<mlir::Float4E2M1FNType>(dstTy))
4635 intId = hasRelu ? llvm::Intrinsic::nvvm_bf16x2_to_e2m1x2_rn_relu_satfinite
4636 : llvm::Intrinsic::nvvm_bf16x2_to_e2m1x2_rn_satfinite;
4641 return {intId, std::move(args)};
4644llvm::Intrinsic::ID ConvertF16x2ToF6x2Op::getIntrinsicID(
mlir::Type dstTy,
4647 .Case<mlir::Float6E2M3FNType>([&](mlir::Float6E2M3FNType) {
4648 return hasRelu ? llvm::Intrinsic::nvvm_f16x2_to_e2m3x2_rn_relu_satfinite
4649 : llvm::Intrinsic::nvvm_f16x2_to_e2m3x2_rn_satfinite;
4651 .Case<mlir::Float6E3M2FNType>([&](mlir::Float6E3M2FNType) {
4652 return hasRelu ? llvm::Intrinsic::nvvm_f16x2_to_e3m2x2_rn_relu_satfinite
4653 : llvm::Intrinsic::nvvm_f16x2_to_e3m2x2_rn_satfinite;
4656 llvm_unreachable(
"Invalid conversion in ConvertF16x2ToF6x2Op");
4657 return llvm::Intrinsic::not_intrinsic;
4661llvm::Intrinsic::ID ConvertBF16x2ToF6x2Op::getIntrinsicID(
mlir::Type dstTy,
4664 .Case<mlir::Float6E2M3FNType>([&](mlir::Float6E2M3FNType) {
4666 ? llvm::Intrinsic::nvvm_bf16x2_to_e2m3x2_rn_relu_satfinite
4667 : llvm::Intrinsic::nvvm_bf16x2_to_e2m3x2_rn_satfinite;
4669 .Case<mlir::Float6E3M2FNType>([&](mlir::Float6E3M2FNType) {
4671 ? llvm::Intrinsic::nvvm_bf16x2_to_e3m2x2_rn_relu_satfinite
4672 : llvm::Intrinsic::nvvm_bf16x2_to_e3m2x2_rn_satfinite;
4675 llvm_unreachable(
"Invalid conversion in ConvertBF16x2ToF6x2Op");
4676 return llvm::Intrinsic::not_intrinsic;
4680#define GET_F32x2_TO_F8X2_US_ID(rnd, has_satf) \
4681 has_satf ? llvm::Intrinsic::nvvm_ff_to_ue8m0x2_##rnd##_satfinite \
4682 : llvm::Intrinsic::nvvm_ff_to_ue8m0x2_##rnd
4684#define GET_F32x2_TO_F8X2_S_ID(type, has_relu) \
4685 has_relu ? llvm::Intrinsic::nvvm_ff_to_##type##_rn_relu \
4686 : llvm::Intrinsic::nvvm_ff_to_##type##_rn
4689ConvertF32x2ToF8x2Op::getIntrinsicID(
mlir::Type dstTy, NVVM::FPRoundingMode rnd,
4690 NVVM::SaturationMode sat,
bool hasRelu) {
4691 bool hasSatFinite = (sat == NVVM::SaturationMode::SATFINITE);
4692 bool hasRoundingModeRZ = (rnd == NVVM::FPRoundingMode::RZ);
4693 bool hasRoundingModeRP = (rnd == NVVM::FPRoundingMode::RP);
4696 .Case([&](mlir::Float8E4M3FNType) {
4699 .Case([&](mlir::Float8E5M2Type) {
4702 .Case([&](mlir::Float8E8M0FNUType) {
4703 if (hasRoundingModeRZ)
4705 else if (hasRoundingModeRP)
4708 llvm_unreachable(
"Invalid conversion in ConvertF32x2ToF8x2Op");
4711 llvm_unreachable(
"Invalid conversion in ConvertF32x2ToF8x2Op");
4712 return llvm::Intrinsic::not_intrinsic;
4716#define GET_F16x2_TO_F8X2_ID(type, has_relu) \
4717 has_relu ? llvm::Intrinsic::nvvm_f16x2_to_##type##_rn_relu \
4718 : llvm::Intrinsic::nvvm_f16x2_to_##type##_rn
4720llvm::Intrinsic::ID ConvertF16x2ToF8x2Op::getIntrinsicID(
mlir::Type dstTy,
4723 .Case([&](mlir::Float8E4M3FNType) {
4726 .Case([&](mlir::Float8E5M2Type) {
4730 llvm_unreachable(
"Invalid conversion in ConvertF16x2ToF8x2Op");
4731 return llvm::Intrinsic::not_intrinsic;
4736ConvertBF16x2ToF8x2Op::getIntrinsicID(
mlir::Type dstTy,
4737 NVVM::FPRoundingMode rnd,
4738 NVVM::SaturationMode sat,
bool hasRelu) {
4739 bool hasSatFinite = (sat == NVVM::SaturationMode::SATFINITE);
4741 static constexpr llvm::Intrinsic::ID ue8m0x2IDs[] = {
4742 llvm::Intrinsic::nvvm_bf16x2_to_ue8m0x2_rz,
4743 llvm::Intrinsic::nvvm_bf16x2_to_ue8m0x2_rp,
4744 llvm::Intrinsic::nvvm_bf16x2_to_ue8m0x2_rz_satfinite,
4745 llvm::Intrinsic::nvvm_bf16x2_to_ue8m0x2_rp_satfinite,
4749 .Case<mlir::Float8E4M3FNType>([&](mlir::Float8E4M3FNType) {
4751 ? llvm::Intrinsic::nvvm_bf16x2_to_e4m3x2_rn_relu_satfinite
4752 : llvm::Intrinsic::nvvm_bf16x2_to_e4m3x2_rn_satfinite;
4754 .Case<mlir::Float8E5M2Type>([&](mlir::Float8E5M2Type) {
4756 ? llvm::Intrinsic::nvvm_bf16x2_to_e5m2x2_rn_relu_satfinite
4757 : llvm::Intrinsic::nvvm_bf16x2_to_e5m2x2_rn_satfinite;
4759 .Case<mlir::Float8E8M0FNUType>([&](mlir::Float8E8M0FNUType) {
4760 bool hasRoundingModeRP = (rnd == NVVM::FPRoundingMode::RP);
4761 unsigned index = (hasSatFinite << 1) | hasRoundingModeRP;
4762 return ue8m0x2IDs[
index];
4765 llvm_unreachable(
"Invalid conversion in ConvertBF16x2ToF8x2Op");
4766 return llvm::Intrinsic::not_intrinsic;
4772 auto curOp = cast<NVVM::ConvertF8x2ToF16x2Op>(op);
4774 bool hasRelu = curOp.getRelu();
4776 llvm::Intrinsic::ID intId =
4778 .Case([&](Float8E4M3FNType type) {
4779 return hasRelu ? llvm::Intrinsic::nvvm_e4m3x2_to_f16x2_rn_relu
4780 : llvm::Intrinsic::nvvm_e4m3x2_to_f16x2_rn;
4782 .Case([&](Float8E5M2Type type) {
4783 return hasRelu ? llvm::Intrinsic::nvvm_e5m2x2_to_f16x2_rn_relu
4784 : llvm::Intrinsic::nvvm_e5m2x2_to_f16x2_rn;
4787 llvm_unreachable(
"Invalid type for ConvertF8x2ToF16x2Op");
4788 return llvm::Intrinsic::not_intrinsic;
4791 llvm::Value *packedI16 =
4792 builder.CreateBitCast(mt.
lookupValue(curOp.getSrc()),
4793 llvm::Type::getInt16Ty(builder.getContext()));
4795 return {intId, {packedI16}};
4800 auto curOp = cast<NVVM::ConvertF8x2ToBF16x2Op>(op);
4802 llvm::Intrinsic::ID intId = llvm::Intrinsic::nvvm_ue8m0x2_to_bf16x2;
4803 llvm::Value *packedI16 =
4804 builder.CreateBitCast(mt.
lookupValue(curOp.getSrc()),
4805 llvm::Type::getInt16Ty(builder.getContext()));
4807 return {intId, {packedI16}};
4812 auto curOp = cast<NVVM::ConvertF6x2ToF16x2Op>(op);
4814 bool hasRelu = curOp.getRelu();
4816 llvm::Intrinsic::ID intId =
4818 .Case([&](Float6E2M3FNType type) {
4819 return hasRelu ? llvm::Intrinsic::nvvm_e2m3x2_to_f16x2_rn_relu
4820 : llvm::Intrinsic::nvvm_e2m3x2_to_f16x2_rn;
4822 .Case([&](Float6E3M2FNType type) {
4823 return hasRelu ? llvm::Intrinsic::nvvm_e3m2x2_to_f16x2_rn_relu
4824 : llvm::Intrinsic::nvvm_e3m2x2_to_f16x2_rn;
4827 llvm_unreachable(
"Invalid type for ConvertF6x2ToF16x2Op");
4828 return llvm::Intrinsic::not_intrinsic;
4831 llvm::Value *packedI16 =
4832 builder.CreateBitCast(mt.
lookupValue(curOp.getSrc()),
4833 llvm::Type::getInt16Ty(builder.getContext()));
4835 return {intId, {packedI16}};
4840 auto curOp = cast<NVVM::ConvertF4x2ToF16x2Op>(op);
4842 bool hasRelu = curOp.getRelu();
4844 llvm::Intrinsic::ID intId =
4846 .Case([&](Float4E2M1FNType type) {
4847 return hasRelu ? llvm::Intrinsic::nvvm_e2m1x2_to_f16x2_rn_relu
4848 : llvm::Intrinsic::nvvm_e2m1x2_to_f16x2_rn;
4851 llvm_unreachable(
"Invalid type for ConvertF4x2ToF16x2Op");
4852 return llvm::Intrinsic::not_intrinsic;
4855 llvm::Value *extendedI16 =
4856 builder.CreateZExt(mt.
lookupValue(curOp.getSrc()),
4857 llvm::Type::getInt16Ty(builder.getContext()));
4859 return {intId, {extendedI16}};
4864 auto thisOp = cast<NVVM::ConvertF32x2ToS2F6x2Op>(op);
4865 bool hasRelu = thisOp.getRelu();
4866 bool hasScale =
static_cast<bool>(thisOp.getScaleFactor());
4868 llvm::Intrinsic::ID
id =
4870 ? llvm::Intrinsic::nvvm_ff_to_s2f6x2_rn_relu_satfinite_scale_n2_ue8m0
4871 : llvm::Intrinsic::nvvm_ff_to_s2f6x2_rn_satfinite_scale_n2_ue8m0;
4877 args.push_back(hasScale ? mt.
lookupValue(thisOp.getScaleFactor())
4878 : builder.getInt16(0x7f7f));
4879 return {id, std::move(args)};
4884 auto thisOp = cast<NVVM::ConvertBF16x2ToS2F6x2Op>(op);
4885 bool hasRelu = thisOp.getRelu();
4886 bool hasScale =
static_cast<bool>(thisOp.getScaleFactor());
4888 llvm::Intrinsic::ID
id =
4891 nvvm_bf16x2_to_s2f6x2_rn_relu_satfinite_scale_n2_ue8m0
4892 : llvm::Intrinsic::nvvm_bf16x2_to_s2f6x2_rn_satfinite_scale_n2_ue8m0;
4897 args.push_back(hasScale ? mt.
lookupValue(thisOp.getScaleFactor())
4898 : builder.getInt16(0x7f7f));
4899 return {id, std::move(args)};
4904 auto thisOp = cast<NVVM::ConvertS2F6x2ToBF16x2Op>(op);
4905 bool hasRelu = thisOp.getRelu();
4906 bool hasScale =
static_cast<bool>(thisOp.getScaleFactor());
4907 bool hasSat = thisOp.getSat() == NVVM::SaturationMode::SATFINITE;
4909 static constexpr llvm::Intrinsic::ID ids[] = {
4910 llvm::Intrinsic::nvvm_s2f6x2_to_bf16x2_rn_scale_n2_ue8m0,
4911 llvm::Intrinsic::nvvm_s2f6x2_to_bf16x2_rn_relu_scale_n2_ue8m0,
4912 llvm::Intrinsic::nvvm_s2f6x2_to_bf16x2_rn_satfinite_scale_n2_ue8m0,
4913 llvm::Intrinsic::nvvm_s2f6x2_to_bf16x2_rn_relu_satfinite_scale_n2_ue8m0,
4916 unsigned idx = (hasSat << 1) | hasRelu;
4920 llvm::Value *packedI16 =
4921 builder.CreateBitCast(mt.
lookupValue(thisOp.getSrc()),
4922 llvm::Type::getInt16Ty(builder.getContext()));
4923 args.push_back(packedI16);
4924 args.push_back(hasScale ? mt.
lookupValue(thisOp.getScaleFactor())
4925 : builder.getInt16(0x7f7f));
4927 return {ids[idx], std::move(args)};
4931Tcgen05AllocOp::getIntrinsicIDAndArgs(
Operation &op,
4934 auto curOp = cast<NVVM::Tcgen05AllocOp>(op);
4935 unsigned as = llvm::cast<LLVM::LLVMPointerType>(curOp.getAddr().getType())
4937 bool isShared = as == NVVMMemorySpace::Shared;
4938 bool is2CTAMode = curOp.getGroup() == CTAGroupKind::CTA_2;
4940 llvm::Intrinsic::ID id;
4942 id = is2CTAMode ? llvm::Intrinsic::nvvm_tcgen05_alloc_shared_cg2
4943 : llvm::Intrinsic::nvvm_tcgen05_alloc_shared_cg1;
4945 id = is2CTAMode ? llvm::Intrinsic::nvvm_tcgen05_alloc_cg2
4946 : llvm::Intrinsic::nvvm_tcgen05_alloc_cg1;
4956llvm::Intrinsic::ID Tcgen05DeallocOp::getIntrinsicIDAndArgs(
4959 auto curOp = cast<NVVM::Tcgen05DeallocOp>(op);
4960 auto id = (curOp.getGroup() == CTAGroupKind::CTA_1)
4961 ? llvm::Intrinsic::nvvm_tcgen05_dealloc_cg1
4962 : llvm::Intrinsic::nvvm_tcgen05_dealloc_cg2;
4971#define TCGEN05_COMMIT_IMPL(cg, is_shared, mc) \
4972 is_shared ? llvm::Intrinsic::nvvm_tcgen05_commit##mc##_shared##_##cg \
4973 : llvm::Intrinsic::nvvm_tcgen05_commit##mc##_##cg
4975#define GET_TCGEN05_COMMIT_ID(cta_group, is_shared, has_mc) \
4976 has_mc ? TCGEN05_COMMIT_IMPL(cta_group, is_shared, _mc) \
4977 : TCGEN05_COMMIT_IMPL(cta_group, is_shared, )
4980Tcgen05CommitOp::getIntrinsicIDAndArgs(
Operation &op,
4983 auto curOp = cast<NVVM::Tcgen05CommitOp>(op);
4984 unsigned as = llvm::cast<LLVM::LLVMPointerType>(curOp.getAddr().getType())
4986 bool isShared = as == NVVMMemorySpace::Shared;
4987 bool hasMulticast =
static_cast<bool>(curOp.getMulticastMask());
4988 bool is2CTAMode = curOp.getGroup() == CTAGroupKind::CTA_2;
4990 llvm::Intrinsic::ID
id =
4997 args.push_back(mt.
lookupValue(curOp.getMulticastMask()));
5002#define TCGEN05_CP_IMPL(shape_mc, src_fmt, cg) \
5003 llvm::Intrinsic::nvvm_tcgen05_cp##shape_mc##src_fmt##cg
5005#define TCGEN05_CP_2CTA(shape_mc, src_fmt, is_2cta) \
5006 is_2cta ? TCGEN05_CP_IMPL(shape_mc, src_fmt, _cg2) \
5007 : TCGEN05_CP_IMPL(shape_mc, src_fmt, _cg1)
5009#define GET_TCGEN05_CP_ID(shape_mc, src_fmt, is_2cta) \
5011 if ((src_fmt) == Tcgen05CpSrcFormat::B6x16_P32) \
5012 return TCGEN05_CP_2CTA(shape_mc, _b6x16_p32, is_2cta); \
5013 if ((src_fmt) == Tcgen05CpSrcFormat::B4x16_P64) \
5014 return TCGEN05_CP_2CTA(shape_mc, _b4x16_p64, is_2cta); \
5015 return TCGEN05_CP_2CTA(shape_mc, , is_2cta); \
5019ConvertF32x2ToF16x2Op::getIntrinsicIDAndArgs(NVVM::ConvertF32x2ToF16x2Op &op,
5021 llvm::IRBuilderBase &builder) {
5022 static constexpr llvm::Intrinsic::ID rndRNIds[] = {
5023 llvm::Intrinsic::nvvm_ff2f16x2_rn,
5024 llvm::Intrinsic::nvvm_ff2f16x2_rn_relu,
5025 llvm::Intrinsic::nvvm_ff2f16x2_rn_satfinite,
5026 llvm::Intrinsic::nvvm_ff2f16x2_rn_relu_satfinite,
5028 static constexpr llvm::Intrinsic::ID rndRZIds[] = {
5029 llvm::Intrinsic::nvvm_ff2f16x2_rz,
5030 llvm::Intrinsic::nvvm_ff2f16x2_rz_relu,
5031 llvm::Intrinsic::nvvm_ff2f16x2_rz_satfinite,
5032 llvm::Intrinsic::nvvm_ff2f16x2_rz_relu_satfinite,
5034 static constexpr llvm::Intrinsic::ID rndRSIds[] = {
5035 llvm::Intrinsic::nvvm_ff2f16x2_rs,
5036 llvm::Intrinsic::nvvm_ff2f16x2_rs_relu,
5037 llvm::Intrinsic::nvvm_ff2f16x2_rs_satfinite,
5038 llvm::Intrinsic::nvvm_ff2f16x2_rs_relu_satfinite,
5041 unsigned hasRelu = op.getRelu() ? 1 : 0;
5042 unsigned hasSatFinite =
5043 (op.getSat() == NVVM::SaturationMode::SATFINITE) ? 1 : 0;
5046 unsigned idx = (hasSatFinite << 1) | hasRelu;
5051 if (op.getRandomBits())
5052 args.push_back(mt.
lookupValue(op.getRandomBits()));
5054 switch (op.getRnd()) {
5055 case FPRoundingMode::RN:
5056 return {rndRNIds[idx], std::move(args)};
5057 case FPRoundingMode::RZ:
5058 return {rndRZIds[idx], std::move(args)};
5059 case FPRoundingMode::RS:
5060 return {rndRSIds[idx], std::move(args)};
5062 llvm_unreachable(
"Invalid rounding mode for ConvertF32x2ToF16x2Op");
5067ConvertF32x2ToBF16x2Op::getIntrinsicIDAndArgs(NVVM::ConvertF32x2ToBF16x2Op &op,
5069 llvm::IRBuilderBase &builder) {
5070 static constexpr llvm::Intrinsic::ID rndRNIds[] = {
5071 llvm::Intrinsic::nvvm_ff2bf16x2_rn,
5072 llvm::Intrinsic::nvvm_ff2bf16x2_rn_relu,
5073 llvm::Intrinsic::nvvm_ff2bf16x2_rn_satfinite,
5074 llvm::Intrinsic::nvvm_ff2bf16x2_rn_relu_satfinite,
5076 static constexpr llvm::Intrinsic::ID rndRZIds[] = {
5077 llvm::Intrinsic::nvvm_ff2bf16x2_rz,
5078 llvm::Intrinsic::nvvm_ff2bf16x2_rz_relu,
5079 llvm::Intrinsic::nvvm_ff2bf16x2_rz_satfinite,
5080 llvm::Intrinsic::nvvm_ff2bf16x2_rz_relu_satfinite,
5082 static constexpr llvm::Intrinsic::ID rndRSIds[] = {
5083 llvm::Intrinsic::nvvm_ff2bf16x2_rs,
5084 llvm::Intrinsic::nvvm_ff2bf16x2_rs_relu,
5085 llvm::Intrinsic::nvvm_ff2bf16x2_rs_satfinite,
5086 llvm::Intrinsic::nvvm_ff2bf16x2_rs_relu_satfinite,
5089 unsigned hasRelu = op.getRelu() ? 1 : 0;
5090 unsigned hasSatFinite =
5091 (op.getSat() == NVVM::SaturationMode::SATFINITE) ? 1 : 0;
5094 unsigned idx = (hasSatFinite << 1) | hasRelu;
5099 if (op.getRandomBits())
5100 args.push_back(mt.
lookupValue(op.getRandomBits()));
5102 switch (op.getRnd()) {
5103 case FPRoundingMode::RN:
5104 return {rndRNIds[idx], std::move(args)};
5105 case FPRoundingMode::RZ:
5106 return {rndRZIds[idx], std::move(args)};
5107 case FPRoundingMode::RS:
5108 return {rndRSIds[idx], std::move(args)};
5110 llvm_unreachable(
"Invalid rounding mode for ConvertF32x2ToBF16x2Op");
5114llvm::Intrinsic::ID ConvertF32x4ToF8x4Op::getIntrinsicID() {
5116 bool hasRelu = getRelu();
5119 .Case([&](mlir::Float8E4M3FNType) {
5120 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e4m3x4_rs_relu_satfinite
5121 : llvm::Intrinsic::nvvm_f32x4_to_e4m3x4_rs_satfinite;
5123 .Case([&](mlir::Float8E5M2Type) {
5124 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e5m2x4_rs_relu_satfinite
5125 : llvm::Intrinsic::nvvm_f32x4_to_e5m2x4_rs_satfinite;
5128 llvm_unreachable(
"Invalid F8 type in ConvertF32x4ToF8x4Op");
5129 return llvm::Intrinsic::not_intrinsic;
5133llvm::Intrinsic::ID ConvertF32x4ToF6x4Op::getIntrinsicID() {
5135 bool hasRelu = getRelu();
5138 .Case([&](mlir::Float6E2M3FNType) {
5139 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e2m3x4_rs_relu_satfinite
5140 : llvm::Intrinsic::nvvm_f32x4_to_e2m3x4_rs_satfinite;
5142 .Case([&](mlir::Float6E3M2FNType) {
5143 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e3m2x4_rs_relu_satfinite
5144 : llvm::Intrinsic::nvvm_f32x4_to_e3m2x4_rs_satfinite;
5147 llvm_unreachable(
"Invalid F6 type in ConvertF32x4ToF6x4Op");
5148 return llvm::Intrinsic::not_intrinsic;
5152llvm::Intrinsic::ID ConvertF32x4ToF4x4Op::getIntrinsicID() {
5154 bool hasRelu = getRelu();
5157 .Case([&](mlir::Float4E2M1FNType) {
5158 return hasRelu ? llvm::Intrinsic::nvvm_f32x4_to_e2m1x4_rs_relu_satfinite
5159 : llvm::Intrinsic::nvvm_f32x4_to_e2m1x4_rs_satfinite;
5162 llvm_unreachable(
"Invalid F4 type in ConvertF32x4ToF4x4Op");
5163 return llvm::Intrinsic::not_intrinsic;
5167llvm::Intrinsic::ID Tcgen05CpOp::getIntrinsicID(
Operation &op) {
5168 auto curOp = cast<NVVM::Tcgen05CpOp>(op);
5169 bool is2CTA = curOp.getGroup() == CTAGroupKind::CTA_2;
5170 auto srcFmt = curOp.getSrcFormat();
5171 auto mc = curOp.getMulticast();
5173 switch (curOp.getShape()) {
5174 case Tcgen05CpShape::SHAPE_128x256b:
5176 case Tcgen05CpShape::SHAPE_128x128b:
5178 case Tcgen05CpShape::SHAPE_4x256b:
5180 case Tcgen05CpShape::SHAPE_32x128b:
5182 case Tcgen05CpShape::SHAPE_64x128b:
5183 return (mc == Tcgen05CpMulticast::WARPX2_01_23)
5187 llvm_unreachable(
"Invalid shape in tcgen05 cp Op");
5194 if (
shape == NVVM::Tcgen05LdStShape::SHAPE_16X128B)
5196 if (
shape == NVVM::Tcgen05LdStShape::SHAPE_16X256B)
5201LogicalResult Tcgen05LdOp::verify() {
5203 if (
getShape() == NVVM::Tcgen05LdStShape::SHAPE_16X32BX2 && !getOffset())
5206 if (
getShape() != NVVM::Tcgen05LdStShape::SHAPE_16X32BX2 && getOffset())
5207 result =
emitError(
"offset argument is only supported for shape 16x32bx2");
5209 auto resTy = getRes().getType();
5210 unsigned resLen = isa<VectorType>(resTy)
5211 ? llvm::cast<VectorType>(resTy).getNumElements()
5214 result =
emitError(llvm::formatv(
"invalid result type length {0} for shape "
5215 "{1} in tcgen05.ld Op",
5216 resLen, stringifyEnum(
getShape())));
5221LogicalResult Tcgen05StOp::verify() {
5223 if (
getShape() == NVVM::Tcgen05LdStShape::SHAPE_16X32BX2 && !getOffset())
5226 auto valTy = getVal().getType();
5227 unsigned valLen = isa<VectorType>(valTy)
5228 ? llvm::cast<VectorType>(valTy).getNumElements()
5231 result =
emitError(llvm::formatv(
"invalid input length {0} for shape "
5232 "{1} in tcgen05.st Op",
5233 valLen, stringifyEnum(
getShape())));
5243 if (
auto rangeAttr = op->
getAttrOfType<LLVM::ConstantRangeAttr>(
"range")) {
5244 setResultRanges(
result, {rangeAttr.getLower(), rangeAttr.getUpper(),
5245 rangeAttr.getLower(), rangeAttr.getUpper()});
5255 std::optional<LLVM::ConstantRangeAttr> rangeAttr) {
5259 const llvm::APInt &lower = rangeAttr->getLower();
5260 const llvm::APInt &upper = rangeAttr->getUpper();
5263 if (lower == upper && !lower.isMaxValue() && !lower.isMinValue()) {
5264 unsigned bitWidth = lower.getBitWidth();
5265 llvm::APInt minVal = llvm::APInt::getMinValue(bitWidth);
5266 llvm::APInt maxVal = llvm::APInt::getMaxValue(bitWidth);
5268 "invalid range attribute: Lower == Upper, but they aren't min (")
5269 << llvm::toString(minVal, 10,
false) <<
") or max ("
5270 << llvm::toString(maxVal, 10,
false)
5271 <<
") value! This is an invalid constant range.";
5278 llvm::IRBuilderBase &builder) {
5279 return builder.CreateBitCast(arg,
5280 llvm::Type::getInt32Ty(builder.getContext()));
5285 auto curOp = cast<NVVM::DotAccumulate4WayOp>(op);
5292 bool isASigned = curOp.getAType() == NVVM::DotAccumulateType::SIGNED;
5293 bool isBSigned = curOp.getBType() == NVVM::DotAccumulateType::SIGNED;
5294 unsigned type = (isASigned << 1) | isBSigned;
5295 const llvm::Intrinsic::ID ids[] = {
5296 llvm::Intrinsic::nvvm_idp4a_u_u,
5297 llvm::Intrinsic::nvvm_idp4a_u_s,
5298 llvm::Intrinsic::nvvm_idp4a_s_u,
5299 llvm::Intrinsic::nvvm_idp4a_s_s,
5301 return {ids[type], args};
5306 auto curOp = cast<NVVM::DotAccumulate2WayOp>(op);
5311 args.push_back(builder.getInt1(curOp.getBHi()));
5314 bool isASigned = curOp.getAType() == NVVM::DotAccumulateType::SIGNED;
5315 bool isBSigned = curOp.getBType() == NVVM::DotAccumulateType::SIGNED;
5316 unsigned type = (isASigned << 1) | isBSigned;
5317 const llvm::Intrinsic::ID ids[] = {
5318 llvm::Intrinsic::nvvm_idp2a_u_u,
5319 llvm::Intrinsic::nvvm_idp2a_u_s,
5320 llvm::Intrinsic::nvvm_idp2a_s_u,
5321 llvm::Intrinsic::nvvm_idp2a_s_s,
5323 return {ids[type], args};
5327 llvm::IRBuilderBase &builder) {
5328 return builder.CreateAddrSpaceCast(
5329 addr, builder.getPtrTy(llvm::NVPTXAS::ADDRESS_SPACE_ENTRY_PARAM));
5333PrefetchOp::getIntrinsicIDAndArgs(NVVM::PrefetchOp &op,
5335 llvm::IRBuilderBase &builder) {
5336 using MemSpace = NVVM::NVVMMemorySpace;
5337 using CacheLevel = NVVM::PrefetchCacheLevel;
5339 std::optional<NVVM::PrefetchCacheLevel> cacheLevel = op.getCacheLevel();
5340 std::optional<NVVM::CacheEvictionPriority> evictPriority =
5341 op.getEvictPriority();
5342 unsigned addressSpace =
5343 llvm::cast<LLVM::LLVMPointerType>(op.getAddr().getType())
5351 if (op.getTensormap())
5352 return {llvm::Intrinsic::nvvm_prefetch_tensormap, args};
5354 assert(cacheLevel &&
"expected cache level for non-tensormap prefetch");
5356 if (op.getUniform() && *cacheLevel == CacheLevel::L1)
5357 return {llvm::Intrinsic::nvvm_prefetchu_L1, args};
5359 if (evictPriority && *cacheLevel == CacheLevel::L2) {
5360 switch (*evictPriority) {
5361 case NVVM::CacheEvictionPriority::EvictLast:
5362 return {llvm::Intrinsic::nvvm_prefetch_global_L2_evict_last, args};
5363 case NVVM::CacheEvictionPriority::EvictNormal:
5364 return {llvm::Intrinsic::nvvm_prefetch_global_L2_evict_normal, args};
5366 llvm_unreachable(
"Invalid cache eviction priority");
5370 switch (
static_cast<MemSpace
>(addressSpace)) {
5371 case MemSpace::Generic:
5372 return *cacheLevel == CacheLevel::L1
5374 :
NVVM::
IDArgPair({llvm::Intrinsic::nvvm_prefetch_L2, args});
5375 case MemSpace::Global:
5376 return *cacheLevel == CacheLevel::L1
5378 {llvm::Intrinsic::nvvm_prefetch_global_L1, args})
5380 {llvm::Intrinsic::nvvm_prefetch_global_L2, args});
5381 case MemSpace::Local:
5382 return *cacheLevel == CacheLevel::L1
5384 {llvm::Intrinsic::nvvm_prefetch_local_L1, args})
5386 {llvm::Intrinsic::nvvm_prefetch_local_L2, args});
5388 llvm_unreachable(
"Invalid pointer address space");
5392bool NVVM::InlinePtxOp::getAsmValues(
5396 for (
auto arg : getReadWriteArgs())
5398 for (
auto arg : getResults())
5400 for (
auto arg : getReadOnlyArgs())
5407NVVM::IDArgPair ClusterLaunchControlTryCancelOp::getIntrinsicIDAndArgs(
5409 auto curOp = cast<NVVM::ClusterLaunchControlTryCancelOp>(op);
5411 args.push_back(mt.
lookupValue(curOp.getSmemAddress()));
5412 args.push_back(mt.
lookupValue(curOp.getMbarrier()));
5414 llvm::Intrinsic::ID intrinsicID =
5415 curOp.getMulticast()
5417 nvvm_clusterlaunchcontrol_try_cancel_async_multicast_shared
5418 : llvm::Intrinsic::nvvm_clusterlaunchcontrol_try_cancel_async_shared;
5420 return {intrinsicID, args};
5423NVVM::IDArgPair ClusterLaunchControlQueryCancelOp::getIntrinsicIDAndArgs(
5425 auto curOp = cast<NVVM::ClusterLaunchControlQueryCancelOp>(op);
5427 args.push_back(mt.
lookupValue(curOp.getTryCancelResponse()));
5429 llvm::Intrinsic::ID intrinsicID;
5431 switch (curOp.getQueryType()) {
5432 case NVVM::ClusterLaunchControlQueryType::IS_CANCELED:
5434 llvm::Intrinsic::nvvm_clusterlaunchcontrol_query_cancel_is_canceled;
5436 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_X:
5437 intrinsicID = llvm::Intrinsic::
5438 nvvm_clusterlaunchcontrol_query_cancel_get_first_ctaid_x;
5440 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_Y:
5441 intrinsicID = llvm::Intrinsic::
5442 nvvm_clusterlaunchcontrol_query_cancel_get_first_ctaid_y;
5444 case NVVM::ClusterLaunchControlQueryType::GET_FIRST_CTA_ID_Z:
5445 intrinsicID = llvm::Intrinsic::
5446 nvvm_clusterlaunchcontrol_query_cancel_get_first_ctaid_z;
5449 return {intrinsicID, args};
5454 llvm::IRBuilderBase &builder) {
5455 auto thisOp = cast<NVVM::PermuteOp>(op);
5456 NVVM::PermuteMode mode = thisOp.getMode();
5458 static constexpr llvm::Intrinsic::ID IDs[] = {
5459 llvm::Intrinsic::nvvm_prmt, llvm::Intrinsic::nvvm_prmt_f4e,
5460 llvm::Intrinsic::nvvm_prmt_b4e, llvm::Intrinsic::nvvm_prmt_rc8,
5461 llvm::Intrinsic::nvvm_prmt_ecl, llvm::Intrinsic::nvvm_prmt_ecr,
5462 llvm::Intrinsic::nvvm_prmt_rc16};
5464 unsigned modeIndex =
static_cast<unsigned>(mode);
5472 args.push_back(mt.
lookupValue(thisOp.getSelector()));
5474 return {IDs[modeIndex], args};
5479 auto thisOp = cast<NVVM::TensormapReplaceOp>(op);
5483 if (thisOp.getOrd())
5484 args.push_back(builder.getInt32(thisOp.getOrd().value()));
5485 if (thisOp.getNewValue())
5486 args.push_back(mt.
lookupValue(thisOp.getNewValue()));
5487 if (
auto attr = thisOp.getNewValueAttr()) {
5490 .Case<TensormapElemtypeAttr, TensormapInterleaveLayoutAttr,
5491 TensormapSwizzleModeAttr, TensormapSwizzleAtomicityAttr,
5492 TensormapFillModeAttr>([](
auto attr) {
5493 return static_cast<unsigned>(attr.getValue());
5495 .Default([](
auto attr) {
5496 llvm_unreachable(
"Invalid attribute type");
5499 args.push_back(builder.getInt32(val));
5502 static constexpr llvm::Intrinsic::ID IDs[] = {
5503 llvm::Intrinsic::nvvm_tensormap_replace_global_address,
5504 llvm::Intrinsic::nvvm_tensormap_replace_rank,
5505 llvm::Intrinsic::nvvm_tensormap_replace_box_dim,
5506 llvm::Intrinsic::nvvm_tensormap_replace_global_dim,
5507 llvm::Intrinsic::nvvm_tensormap_replace_global_stride,
5508 llvm::Intrinsic::nvvm_tensormap_replace_element_stride,
5509 llvm::Intrinsic::nvvm_tensormap_replace_elemtype,
5510 llvm::Intrinsic::nvvm_tensormap_replace_interleave_layout,
5511 llvm::Intrinsic::nvvm_tensormap_replace_swizzle_mode,
5512 llvm::Intrinsic::nvvm_tensormap_replace_swizzle_atomicity,
5513 llvm::Intrinsic::nvvm_tensormap_replace_fill_mode,
5516 unsigned fieldIndex =
static_cast<unsigned>(thisOp.getField());
5518 return {IDs[fieldIndex], args};
5527 llvm::IRBuilderBase &builder) {
5529 auto thisOp = cast<NVVM::Tcgen05MMAOp>(op);
5532 args.push_back(mt.
lookupValue(thisOp.getMatrixD()));
5535 const bool isATensor = isa<llvm::PointerType>(
A->getType());
5538 args.push_back(mt.
lookupValue(thisOp.getMatrixB()));
5539 args.push_back(mt.
lookupValue(thisOp.getIdesc()));
5540 args.push_back(mt.
lookupValue(thisOp.getEnableInputD()));
5542 using EnableAShiftArray = std::array<llvm::Intrinsic::ID, 2>;
5543 using CtaGroupArray = std::array<EnableAShiftArray, 2>;
5544 using IsATensorArray = std::array<CtaGroupArray, 2>;
5545 using HasScaleInputDArray = std::array<IsATensorArray, 2>;
5546 using HasDisableOutputLaneArray = std::array<HasScaleInputDArray, 2>;
5549 static constexpr HasDisableOutputLaneArray tcgen05MMAIDs = {
5555 {llvm::Intrinsic::nvvm_tcgen05_mma_shared,
notIntrinsic},
5557 {llvm::Intrinsic::nvvm_tcgen05_mma_shared,
notIntrinsic}}},
5561 llvm::Intrinsic::nvvm_tcgen05_mma_tensor,
5562 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_ashift,
5566 llvm::Intrinsic::nvvm_tcgen05_mma_tensor,
5567 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_ashift,
5573 {llvm::Intrinsic::nvvm_tcgen05_mma_shared_scale_d,
notIntrinsic},
5575 {llvm::Intrinsic::nvvm_tcgen05_mma_shared_scale_d,
notIntrinsic}}},
5579 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_scale_d,
5580 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_scale_d_ashift,
5584 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_scale_d,
5585 llvm::Intrinsic::nvvm_tcgen05_mma_tensor_scale_d_ashift,
5591 {llvm::Intrinsic::nvvm_tcgen05_mma_shared_disable_output_lane_cg1,
5594 {llvm::Intrinsic::nvvm_tcgen05_mma_shared_disable_output_lane_cg2,
5599 nvvm_tcgen05_mma_tensor_disable_output_lane_cg1,
5601 nvvm_tcgen05_mma_tensor_disable_output_lane_cg1_ashift,
5606 nvvm_tcgen05_mma_tensor_disable_output_lane_cg2,
5608 nvvm_tcgen05_mma_tensor_disable_output_lane_cg2_ashift,
5614 nvvm_tcgen05_mma_shared_scale_d_disable_output_lane_cg1,
5618 nvvm_tcgen05_mma_shared_scale_d_disable_output_lane_cg2,
5623 nvvm_tcgen05_mma_tensor_scale_d_disable_output_lane_cg1,
5625 nvvm_tcgen05_mma_tensor_scale_d_disable_output_lane_cg1_ashift},
5629 nvvm_tcgen05_mma_tensor_scale_d_disable_output_lane_cg2,
5631 nvvm_tcgen05_mma_tensor_scale_d_disable_output_lane_cg2_ashift,
5634 llvm::Value *ScaleInputD = mt.
lookupValue(thisOp.getScaleInputD());
5635 bool hasScaleInputD = ScaleInputD !=
nullptr;
5637 llvm::Value *DisableOutputLane =
5639 bool hasDisableOutputLane = DisableOutputLane !=
nullptr;
5641 const unsigned ctaGroup =
5644 llvm::Intrinsic::ID ID =
5645 tcgen05MMAIDs[hasDisableOutputLane][hasScaleInputD][isATensor]
5646 [ctaGroup - 1][thisOp.getAShift()];
5648 assert(ID !=
notIntrinsic &&
"Invalid intrinsic for Tcgen05MMAOp.");
5651 args.push_back(ScaleInputD);
5653 if (hasDisableOutputLane)
5654 args.push_back(DisableOutputLane);
5656 args.push_back(builder.getInt32(
static_cast<unsigned>(thisOp.getKind())));
5658 if (!hasDisableOutputLane)
5659 args.push_back(builder.getInt32(ctaGroup));
5662 builder.getInt32(
static_cast<unsigned>(thisOp.getCollectorOp())));
5669 NVVM::CTAGroupKind ctaGroup,
bool hasAShift,
5670 NVVM::Tcgen05MMACollectorOp collectorOp,
Location loc) {
5672 if (disableOutputLane) {
5673 mlir::VectorType disableOutputLaneType =
5674 cast<mlir::VectorType>(disableOutputLane.
getType());
5675 if ((ctaGroup == NVVM::CTAGroupKind::CTA_1 &&
5676 disableOutputLaneType.getNumElements() != 4) ||
5677 (ctaGroup == NVVM::CTAGroupKind::CTA_2 &&
5678 disableOutputLaneType.getNumElements() != 8))
5679 return emitError(loc) <<
"Disable Output Lane of length "
5680 << disableOutputLaneType.getNumElements()
5681 <<
" is incompatible with CtaGroupAttr";
5684 if (hasAShift && !isATensor)
5686 loc,
"A-shift can be applied only when matrix A is in tensor memory");
5688 if (hasAShift ==
true && (collectorOp == Tcgen05MMACollectorOp::FILL ||
5689 collectorOp == Tcgen05MMACollectorOp::USE))
5691 loc,
"Cannot use collector buffer operation fill or use with ashift");
5696LogicalResult Tcgen05MMAOp::verify() {
5698 getDisableOutputLane(), getCtaGroup(), getAShift(),
5699 getCollectorOp(), getLoc());
5709 auto thisOp = cast<NVVM::Tcgen05MMASparseOp>(op);
5712 args.push_back(mt.
lookupValue(thisOp.getMatrixD()));
5715 bool isATensor = isa<llvm::PointerType>(
A->getType());
5718 args.push_back(mt.
lookupValue(thisOp.getMatrixB()));
5719 args.push_back(mt.
lookupValue(thisOp.getIdesc()));
5720 args.push_back(mt.
lookupValue(thisOp.getEnableInputD()));
5721 args.push_back(mt.
lookupValue(thisOp.getSparseMetadata()));
5723 using EnableAShiftArray = std::array<llvm::Intrinsic::ID, 2>;
5724 using CtaGroupArray = std::array<EnableAShiftArray, 2>;
5725 using IsATensorArray = std::array<CtaGroupArray, 2>;
5726 using HasScaleInputDArray = std::array<IsATensorArray, 2>;
5727 using HasDisableOutputLaneArray = std::array<HasScaleInputDArray, 2>;
5730 static constexpr HasDisableOutputLaneArray tcgen05MMASparseIDs = {
5736 {llvm::Intrinsic::nvvm_tcgen05_mma_sp_shared,
notIntrinsic},
5738 {llvm::Intrinsic::nvvm_tcgen05_mma_sp_shared,
notIntrinsic}}},
5742 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor,
5743 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_ashift,
5747 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor,
5748 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_ashift,
5754 {llvm::Intrinsic::nvvm_tcgen05_mma_sp_shared_scale_d,
5757 {llvm::Intrinsic::nvvm_tcgen05_mma_sp_shared_scale_d,
5762 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_scale_d,
5763 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_scale_d_ashift,
5767 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_scale_d,
5768 llvm::Intrinsic::nvvm_tcgen05_mma_sp_tensor_scale_d_ashift,
5775 nvvm_tcgen05_mma_sp_shared_disable_output_lane_cg1,
5779 nvvm_tcgen05_mma_sp_shared_disable_output_lane_cg2,
5784 nvvm_tcgen05_mma_sp_tensor_disable_output_lane_cg1,
5786 nvvm_tcgen05_mma_sp_tensor_disable_output_lane_cg1_ashift,
5791 nvvm_tcgen05_mma_sp_tensor_disable_output_lane_cg2,
5793 nvvm_tcgen05_mma_sp_tensor_disable_output_lane_cg2_ashift,
5799 nvvm_tcgen05_mma_sp_shared_scale_d_disable_output_lane_cg1,
5803 nvvm_tcgen05_mma_sp_shared_scale_d_disable_output_lane_cg2,
5808 nvvm_tcgen05_mma_sp_tensor_scale_d_disable_output_lane_cg1,
5810 nvvm_tcgen05_mma_sp_tensor_scale_d_disable_output_lane_cg1_ashift},
5814 nvvm_tcgen05_mma_sp_tensor_scale_d_disable_output_lane_cg2,
5816 nvvm_tcgen05_mma_sp_tensor_scale_d_disable_output_lane_cg2_ashift,
5819 llvm::Value *ScaleInputD = mt.
lookupValue(thisOp.getScaleInputD());
5820 bool hasScaleInputD = ScaleInputD !=
nullptr;
5822 llvm::Value *DisableOutputLane =
5824 bool hasDisableOutputLane = DisableOutputLane !=
nullptr;
5829 llvm::Intrinsic::ID ID =
5830 tcgen05MMASparseIDs[hasDisableOutputLane][hasScaleInputD][isATensor]
5831 [ctaGroup - 1][thisOp.getAShift()];
5833 assert(ID !=
notIntrinsic &&
"Invalid intrinsic for Tcgen05MMASparseOp.");
5836 args.push_back(ScaleInputD);
5838 if (hasDisableOutputLane)
5839 args.push_back(DisableOutputLane);
5841 args.push_back(builder.getInt32(
static_cast<unsigned>(thisOp.getKind())));
5843 if (!hasDisableOutputLane)
5844 args.push_back(builder.getInt32(ctaGroup));
5847 builder.getInt32(
static_cast<unsigned>(thisOp.getCollectorOp())));
5852LogicalResult Tcgen05MMASparseOp::verify() {
5854 getDisableOutputLane(), getCtaGroup(), getAShift(),
5855 getCollectorOp(), getLoc());
5865 auto thisOp = cast<NVVM::Tcgen05MMABlockScaleOp>(op);
5868 args.push_back(mt.
lookupValue(thisOp.getMatrixD()));
5871 bool isATensor = isa<llvm::PointerType>(
A->getType());
5874 args.push_back(mt.
lookupValue(thisOp.getMatrixB()));
5875 args.push_back(mt.
lookupValue(thisOp.getIdesc()));
5876 args.push_back(mt.
lookupValue(thisOp.getEnableInputD()));
5877 args.push_back(mt.
lookupValue(thisOp.getScaleA()));
5878 args.push_back(mt.
lookupValue(thisOp.getScaleB()));
5879 args.push_back(builder.getInt32(
5882 builder.getInt32(
static_cast<unsigned>(thisOp.getCollectorOp())));
5884 auto kind = thisOp.getKind();
5885 auto blockScale = thisOp.getBlockScale();
5886 llvm::Intrinsic::ID ID = [&]() {
5887 if (kind == NVVM::Tcgen05MMAKind::MXF8F6F4) {
5888 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT) {
5889 return isATensor ? llvm::Intrinsic::
5890 nvvm_tcgen05_mma_tensor_mxf8f6f4_block_scale
5892 nvvm_tcgen05_mma_shared_mxf8f6f4_block_scale;
5893 }
else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5896 nvvm_tcgen05_mma_tensor_mxf8f6f4_block_scale_block32
5898 nvvm_tcgen05_mma_shared_mxf8f6f4_block_scale_block32;
5900 }
else if (kind == NVVM::Tcgen05MMAKind::MXF4) {
5901 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT) {
5903 ? llvm::Intrinsic::nvvm_tcgen05_mma_tensor_mxf4_block_scale
5904 : llvm::Intrinsic::nvvm_tcgen05_mma_shared_mxf4_block_scale;
5905 }
else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5906 return isATensor ? llvm::Intrinsic::
5907 nvvm_tcgen05_mma_tensor_mxf4_block_scale_block32
5909 nvvm_tcgen05_mma_shared_mxf4_block_scale_block32;
5911 }
else if (kind == NVVM::Tcgen05MMAKind::MXF4NVF4) {
5912 if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5915 nvvm_tcgen05_mma_tensor_mxf4nvf4_block_scale_block32
5917 nvvm_tcgen05_mma_shared_mxf4nvf4_block_scale_block32;
5919 }
else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK16) {
5922 nvvm_tcgen05_mma_tensor_mxf4nvf4_block_scale_block16
5924 nvvm_tcgen05_mma_shared_mxf4nvf4_block_scale_block16;
5927 llvm_unreachable(
"Invalid tcgen05.mma.block_scale attributes");
5934 NVVM::Tcgen05MMACollectorOp collectorOp, NVVM::Tcgen05MMAKind kind,
5935 NVVM::Tcgen05MMABlockScale blockScale,
Location loc) {
5936 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT &&
5937 kind == NVVM::Tcgen05MMAKind::MXF4NVF4)
5938 return emitError(loc,
"mxf4nvf4 requires block scale attribute");
5940 if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK16 &&
5941 kind != NVVM::Tcgen05MMAKind::MXF4NVF4)
5943 llvm::formatv(
"{} kind does not support block16 attribute",
5944 stringifyEnum(kind)));
5949LogicalResult Tcgen05MMABlockScaleOp::verify() {
5951 getBlockScale(), getLoc());
5961 auto thisOp = cast<NVVM::Tcgen05MMASparseBlockScaleOp>(op);
5964 args.push_back(mt.
lookupValue(thisOp.getMatrixD()));
5967 bool isATensor = isa<llvm::PointerType>(
A->getType());
5970 args.push_back(mt.
lookupValue(thisOp.getMatrixB()));
5971 args.push_back(mt.
lookupValue(thisOp.getIdesc()));
5972 args.push_back(mt.
lookupValue(thisOp.getEnableInputD()));
5973 args.push_back(mt.
lookupValue(thisOp.getSparseMetadata()));
5974 args.push_back(mt.
lookupValue(thisOp.getScaleA()));
5975 args.push_back(mt.
lookupValue(thisOp.getScaleB()));
5976 args.push_back(builder.getInt32(
5979 builder.getInt32(
static_cast<unsigned>(thisOp.getCollectorOp())));
5981 auto kind = thisOp.getKind();
5982 auto blockScale = thisOp.getBlockScale();
5983 llvm::Intrinsic::ID ID = [&]() {
5984 if (kind == NVVM::Tcgen05MMAKind::MXF8F6F4) {
5985 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT) {
5986 return isATensor ? llvm::Intrinsic::
5987 nvvm_tcgen05_mma_sp_tensor_mxf8f6f4_block_scale
5989 nvvm_tcgen05_mma_sp_shared_mxf8f6f4_block_scale;
5990 }
else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
5993 nvvm_tcgen05_mma_sp_tensor_mxf8f6f4_block_scale_block32
5995 nvvm_tcgen05_mma_sp_shared_mxf8f6f4_block_scale_block32;
5997 }
else if (kind == NVVM::Tcgen05MMAKind::MXF4) {
5998 if (blockScale == NVVM::Tcgen05MMABlockScale::DEFAULT) {
5999 return isATensor ? llvm::Intrinsic::
6000 nvvm_tcgen05_mma_sp_tensor_mxf4_block_scale
6002 nvvm_tcgen05_mma_sp_shared_mxf4_block_scale;
6003 }
else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
6006 nvvm_tcgen05_mma_sp_tensor_mxf4_block_scale_block32
6008 nvvm_tcgen05_mma_sp_shared_mxf4_block_scale_block32;
6010 }
else if (kind == NVVM::Tcgen05MMAKind::MXF4NVF4) {
6011 if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK32) {
6014 nvvm_tcgen05_mma_sp_tensor_mxf4nvf4_block_scale_block32
6016 nvvm_tcgen05_mma_sp_shared_mxf4nvf4_block_scale_block32;
6018 }
else if (blockScale == NVVM::Tcgen05MMABlockScale::BLOCK16) {
6021 nvvm_tcgen05_mma_sp_tensor_mxf4nvf4_block_scale_block16
6023 nvvm_tcgen05_mma_sp_shared_mxf4nvf4_block_scale_block16;
6026 llvm_unreachable(
"Invalid tcgen05.mma.sp.block_scale attributes");
6032LogicalResult Tcgen05MMASparseBlockScaleOp::verify() {
6034 getBlockScale(), getLoc());
6044 auto thisOp = cast<NVVM::Tcgen05MMAWsOp>(op);
6047 args.push_back(mt.
lookupValue(thisOp.getMatrixD()));
6050 bool isATensor = isa<llvm::PointerType>(
A->getType());
6053 args.push_back(mt.
lookupValue(thisOp.getMatrixB()));
6054 args.push_back(mt.
lookupValue(thisOp.getIdesc()));
6055 args.push_back(mt.
lookupValue(thisOp.getEnableInputD()));
6057 mlir::Value ZeroColMask = thisOp.getZeroColMask();
6061 ID = isATensor ? llvm::Intrinsic::nvvm_tcgen05_mma_ws_tensor_zero_col_mask
6062 : llvm::Intrinsic::nvvm_tcgen05_mma_ws_shared_zero_col_mask;
6064 ID = isATensor ? llvm::Intrinsic::nvvm_tcgen05_mma_ws_tensor
6065 : llvm::Intrinsic::nvvm_tcgen05_mma_ws_shared;
6067 args.push_back(builder.getInt32(
static_cast<unsigned>(thisOp.getKind())));
6069 builder.getInt32(
static_cast<unsigned>(thisOp.getCollectorBBuffer())));
6071 builder.getInt32(
static_cast<unsigned>(thisOp.getCollectorOp())));
6083 auto thisOp = cast<NVVM::Tcgen05MMAWsSparseOp>(op);
6086 args.push_back(mt.
lookupValue(thisOp.getMatrixD()));
6089 bool isATensor = isa<llvm::PointerType>(
A->getType());
6092 args.push_back(mt.
lookupValue(thisOp.getMatrixB()));
6093 args.push_back(mt.
lookupValue(thisOp.getIdesc()));
6094 args.push_back(mt.
lookupValue(thisOp.getEnableInputD()));
6095 args.push_back(mt.
lookupValue(thisOp.getSparseMetadata()));
6097 mlir::Value ZeroColMask = thisOp.getZeroColMask();
6102 ? llvm::Intrinsic::nvvm_tcgen05_mma_ws_sp_tensor_zero_col_mask
6103 : llvm::Intrinsic::nvvm_tcgen05_mma_ws_sp_shared_zero_col_mask;
6105 ID = isATensor ? llvm::Intrinsic::nvvm_tcgen05_mma_ws_sp_tensor
6106 : llvm::Intrinsic::nvvm_tcgen05_mma_ws_sp_shared;
6108 args.push_back(builder.getInt32(
static_cast<unsigned>(thisOp.getKind())));
6110 builder.getInt32(
static_cast<unsigned>(thisOp.getCollectorBBuffer())));
6112 builder.getInt32(
static_cast<unsigned>(thisOp.getCollectorOp())));
6121#define TCGEN05LDRED(SHAPE, NUM, TYPE) \
6122 llvm::Intrinsic::nvvm_tcgen05_ld_red_##SHAPE##_##NUM##_##TYPE
6126 auto thisOp = cast<NVVM::Tcgen05LdRedOp>(op);
6129 mlir::VectorType VecResTy =
6130 cast<mlir::VectorType>(thisOp.getData().getType());
6131 unsigned Num = VecResTy.getNumElements();
6132 bool IsFloat = thisOp.getRedVal().getType().isF32();
6134 llvm::Intrinsic::ID Shape32x32b[][2] = {
6145 llvm::Intrinsic::ID Shape16x32bx2[][2] = {
6156 NVVM::Tcgen05LdStShape
shape = thisOp.getShape();
6157 unsigned ID = [&]() {
6160 unsigned idx = std::log2(Num);
6162 case NVVM::Tcgen05LdStShape::SHAPE_32X32B:
6163 return Shape32x32b[idx][IsFloat];
6164 case NVVM::Tcgen05LdStShape::SHAPE_16X32BX2:
6165 return Shape16x32bx2[idx][IsFloat];
6167 llvm_unreachable(
"unhandled tcgen05.ld lowering");
6173 if (
shape == NVVM::Tcgen05LdStShape::SHAPE_16X32BX2)
6174 args.push_back(mt.
lookupValue(thisOp.getOffset()));
6177 builder.getInt32(thisOp.getOp() == NVVM::ReductionKind::MIN ? 0 : 1));
6180 args.push_back(builder.getInt1(
static_cast<unsigned>(thisOp.getAbs())));
6181 args.push_back(builder.getInt1(
static_cast<unsigned>(thisOp.getNan())));
6186LogicalResult Tcgen05LdRedOp::verify() {
6187 VectorType data = cast<VectorType>(getData().
getType());
6188 Type redVal = getRedVal().getType();
6190 if (data.getElementType() != redVal)
6192 "type of reduction value and element type of vector data should match");
6194 if (getOp() != NVVM::ReductionKind::MIN &&
6195 getOp() != NVVM::ReductionKind::MAX)
6196 return emitError(
"only min and max reduction kinds are supported");
6198 if (redVal.
isInteger() && (getAbs() || getNan())) {
6199 return emitError(
"abs or nan is only applicable for f32 type");
6209void NVVMDialect::initialize() {
6212#include "mlir/Dialect/LLVMIR/NVVMOps.cpp.inc"
6215#define GET_ATTRDEF_LIST
6216#include "mlir/Dialect/LLVMIR/NVVMOpsAttributes.cpp.inc"
6221 allowUnknownOperations();
6222 declarePromisedInterface<ConvertToLLVMPatternInterface, NVVMDialect>();
6223 declarePromisedInterface<gpu::TargetAttrInterface, NVVMTargetAttr>();
6226LogicalResult NVVMDialect::verifyOperationAttribute(
Operation *op,
6228 StringAttr attrName = attr.
getName();
6230 if (attrName == NVVMDialect::getKernelFuncAttrName()) {
6231 if (!isa<LLVM::LLVMFuncOp>(op)) {
6232 return op->
emitError() <<
"'" << NVVMDialect::getKernelFuncAttrName()
6233 <<
"' attribute attached to unexpected op";
6238 if (attrName == NVVMDialect::getMaxntidAttrName() ||
6239 attrName == NVVMDialect::getReqntidAttrName() ||
6240 attrName == NVVMDialect::getClusterDimAttrName()) {
6241 auto values = llvm::dyn_cast<DenseI32ArrayAttr>(attr.
getValue());
6242 if (!values || values.empty() || values.size() > 3) {
6245 <<
"' attribute must be integer array with maximum 3 index";
6250 if (attrName == NVVMDialect::getMinctasmAttrName() ||
6251 attrName == NVVMDialect::getMaxnregAttrName() ||
6252 attrName == NVVMDialect::getClusterMaxBlocksAttrName()) {
6253 if (!llvm::dyn_cast<IntegerAttr>(attr.
getValue())) {
6255 <<
"'" << attrName <<
"' attribute must be integer constant";
6259 if (attrName == NVVMDialect::getBlocksAreClustersAttrName()) {
6260 if (!op->
hasAttr(NVVMDialect::getReqntidAttrName()) ||
6261 !op->
hasAttr(NVVMDialect::getClusterDimAttrName())) {
6263 <<
"'" << attrName <<
"' attribute must be used along with "
6264 <<
"'" << NVVMDialect::getReqntidAttrName() <<
"' and "
6265 <<
"'" << NVVMDialect::getClusterDimAttrName() <<
"'";
6272LogicalResult NVVMDialect::verifyRegionArgAttribute(
Operation *op,
6273 unsigned regionIndex,
6276 auto funcOp = dyn_cast<FunctionOpInterface>(op);
6280 bool isKernel = op->
hasAttr(NVVMDialect::getKernelFuncAttrName());
6281 StringAttr attrName = argAttr.
getName();
6282 if (attrName == NVVM::NVVMDialect::getGridConstantAttrName()) {
6286 <<
"' attribute must be present only on kernel arguments";
6288 if (!isa<UnitAttr>(argAttr.
getValue()))
6289 return op->
emitError() <<
"'" << attrName <<
"' must be a unit attribute";
6290 if (!funcOp.getArgAttr(argIndex, LLVM::LLVMDialect::getByValAttrName())) {
6293 <<
"' attribute requires the argument to also have attribute '"
6294 << LLVM::LLVMDialect::getByValAttrName() <<
"'";
6305unsigned NVVMMemorySpaceAttr::getAddressSpace()
const {
6306 return static_cast<unsigned>(getValue());
6309bool NVVMMemorySpaceAttr::isValidLoad(
6310 Type type, ptr::AtomicOrdering ordering, std::optional<int64_t> alignment,
6311 const ::mlir::DataLayout *dataLayout,
6317bool NVVMMemorySpaceAttr::isValidStore(
6318 Type type, ptr::AtomicOrdering ordering, std::optional<int64_t> alignment,
6319 const ::mlir::DataLayout *dataLayout,
6325bool NVVMMemorySpaceAttr::isValidAtomicOp(
6326 ptr::AtomicBinOp op,
Type type, ptr::AtomicOrdering ordering,
6327 std::optional<int64_t> alignment, const ::mlir::DataLayout *dataLayout,
6330 assert(
false &&
"unimplemented, see TODO in the source.");
6334bool NVVMMemorySpaceAttr::isValidAtomicXchg(
6335 Type type, ptr::AtomicOrdering successOrdering,
6336 ptr::AtomicOrdering failureOrdering, std::optional<int64_t> alignment,
6337 const ::mlir::DataLayout *dataLayout,
6340 assert(
false &&
"unimplemented, see TODO in the source.");
6344bool NVVMMemorySpaceAttr::isValidAddrSpaceCast(
6348 assert(
false &&
"unimplemented, see TODO in the source.");
6352bool NVVMMemorySpaceAttr::isValidPtrIntCast(
6357 assert(
false &&
"unimplemented, see TODO in the source.");
6366 int optLevel, StringRef triple, StringRef chip,
6367 StringRef features, DictionaryAttr flags,
6369 if (optLevel < 0 || optLevel > 3) {
6370 emitError() <<
"The optimization level must be a number between 0 and 3.";
6373 if (triple.empty()) {
6374 emitError() <<
"The target triple cannot be empty.";
6378 emitError() <<
"The target chip cannot be empty.";
6381 if (files && !llvm::all_of(files, [](::mlir::Attribute attr) {
6382 return mlir::isa_and_nonnull<StringAttr>(attr);
6384 emitError() <<
"All the elements in the `link` array must be strings.";
6390LogicalResult NVVMTargetAttr::verifyTarget(
Operation *gpuModule) {
6391 if (!getVerifyTarget())
6394 auto gpuModuleOp = llvm::dyn_cast<gpu::GPUModuleOp>(gpuModule);
6397 "NVVM target attribute must be attached to a GPU module");
6400 const unsigned targetFullSmVersion =
6404 "Minimum NVVM target SM version is sm_20");
6408 ->
walk([&](Operation *op) {
6409 if (
auto reqOp = llvm::dyn_cast<NVVM::RequiresSMInterface>(op)) {
6410 const NVVMCheckSMVersion requirement =
6411 reqOp.getRequiredMinSMVersion();
6413 op->
emitOpError() <<
"is not supported on " << getChip();
6425#define GET_OP_CLASSES
6426#include "mlir/Dialect/LLVMIR/NVVMOps.cpp.inc"
6428#define GET_ATTRDEF_CLASSES
6429#include "mlir/Dialect/LLVMIR/NVVMOpsAttributes.cpp.inc"
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.
#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)
static bool isPtrInAddrSpace(mlir::Value ptr, NVVMMemorySpace targetAS)
static bool isCompatibleReturnTypesOptionalResult(TypeRange inferred, TypeRange actual)
For ops with optional results, allow the user to omit the result even when inference would produce on...
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 verifyAddSubFOp(OpType op)
static LogicalResult verifyTcgen05MMABlockScaleOp(NVVM::Tcgen05MMACollectorOp collectorOp, NVVM::Tcgen05MMAKind 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)
static void inferAndSetMultiplicandTypes(MLIRContext *ctx, NamedAttrList &attrs, const SmallVectorImpl< Type > &operandTypes)
static LogicalResult parseMmaOperand(OpAsmParser &parser, StringRef operandName, SmallVectorImpl< OpAsmParser::UnresolvedOperand > ®s)
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)
#define TCGEN05LDRED(SHAPE, NUM, 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 > ®Types, SmallVectorImpl< StringRef > &ignoreAttrNames)
static constexpr unsigned notIntrinsic
static LogicalResult inferMBarrierArriveResultTypes(MLIRContext *context, Value addr, SmallVectorImpl< Type > &inferredReturnTypes)
Only shared_cluster (ptr<7>) produces zero results; all other address spaces (including generic) retu...
static ArrayRef< int64_t > getShape(Type type)
Returns the shape of the given type.
@ 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,...
DenseI32ArrayAttr getDenseI32ArrayAttr(ArrayRef< int32_t > values)
IntegerType getIntegerType(unsigned width)
MLIRContext * getContext() const
Attr getAttr(Args &&...args)
Get or construct an instance of the attribute Attr with provided arguments.
This class represents a diagnostic that is inflight and set to be reported.
static IntegerValueRange getMaxRange(Value value)
Create a maximal range ([0, uint_max(t)] / [int_min(t), int_max(t)]) range that is used to mark the v...
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...
MLIRContext is the top-level object for a collection of MLIR operations.
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.
StringAttr getName() const
Return the name of the attribute.
Attribute getValue() const
Return the value of the attribute.
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.
This provides public APIs that all operations should have.
Operation is the basic unit of execution within MLIR.
AttrClass getAttrOfType(StringAttr name)
bool hasAttr(StringAttr name)
Return true if the operation has an attribute with the provided name, false otherwise.
Location getLoc()
The source location the operation was defined or derived from.
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.
A special type of RewriterBase that coordinates the application of a rewrite pattern on the current I...
RewritePatternSet & add(ConstructorArg &&arg, ConstructorArgs &&...args)
Add an instance of each of the pattern types 'Ts' to the pattern list with the given arguments.
This class coordinates the application of a rewrite on a set of IR, providing a way for clients to tr...
OpTy replaceOpWithNewOp(Operation *op, Args &&...args)
Replace the results of the given (original) op with a new op that is created without verification (re...
This class provides an abstraction over the various different ranges of value types.
Instances of the Type class are uniqued, have an immutable identifier and an optional mutable compone...
MLIRContext * getContext() const
Return the MLIRContext in which this type was uniqued.
bool isInteger() const
Return true if this is an integer type (with the specified width).
This class provides an abstraction over the different types of ranges over Values.
This class represents an instance of an SSA value in the MLIR system, representing a computable value...
Type getType() const
Return the type of this value.
static WalkResult advance()
static WalkResult interrupt()
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.
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).
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.
uint64_t getN(LevelType lt)
uint64_t getM(LevelType lt)
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.
InFlightDiagnostic emitError(Location loc)
Utility method to emit an error message using this location.
llvm::function_ref< Fn > function_ref
LogicalResult matchAndRewrite(SubFOp op, PatternRewriter &rewriter) const override
static bool isMinimumSMVersion(unsigned fullSmVersion)
static unsigned getTargetFullSmVersionFromStr(StringRef smVersionString)
bool isCompatibleWith(const unsigned &targetFullSmVersion) const
OpRewritePattern(MLIRContext *context, PatternBenefit benefit=1, ArrayRef< StringRef > generatedNames={})
This represents an operation in an abstracted form, suitable for use with the builder APIs.