MLIR  16.0.0git
ParallelLoopMapper.cpp
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1 //===- ParallelLoopMapper.cpp - Utilities for mapping parallel loops to GPU =//
2 //
3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4 // See https://llvm.org/LICENSE.txt for license information.
5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6 //
7 //===----------------------------------------------------------------------===//
8 //
9 // This file implements utilities to generate mappings for parallel loops to
10 // GPU devices.
11 //
12 //===----------------------------------------------------------------------===//
13 
15 
20 #include "mlir/IR/AffineMap.h"
21 
22 namespace mlir {
23 #define GEN_PASS_DEF_GPUMAPPARALLELLOOPSPASS
24 #include "mlir/Dialect/GPU/Transforms/Passes.h.inc"
25 } // namespace mlir
26 
27 namespace mlir {
28 
29 using scf::ParallelOp;
30 
31 StringRef gpu::getMappingAttrName() { return "mapping"; }
32 
34 gpu::setMappingAttr(ParallelOp ploopOp,
36  // Verify that each processor is mapped to only once.
37  llvm::DenseSet<gpu::Processor> specifiedMappings;
38  for (auto dimAttr : mapping) {
39  gpu::Processor processor = dimAttr.getProcessor();
40  if (processor != gpu::Processor::Sequential &&
41  specifiedMappings.count(processor))
42  return ploopOp.emitError(
43  "invalid mapping multiple loops to same processor");
44  }
45  ArrayRef<Attribute> mappingAsAttrs(mapping.data(), mapping.size());
46  ploopOp->setAttr(getMappingAttrName(),
47  ArrayAttr::get(ploopOp.getContext(), mappingAsAttrs));
48  return success();
49 }
50 
51 namespace gpu {
52 namespace {
53 enum MappingLevel { MapGrid = 0, MapBlock = 1, Sequential = 2 };
54 } // namespace
55 
56 static constexpr int kNumHardwareIds = 3;
57 
58 /// Bounded increment on MappingLevel. Increments to the next
59 /// level unless Sequential was already reached.
60 static MappingLevel &operator++(MappingLevel &mappingLevel) {
61  if (mappingLevel < Sequential) {
62  mappingLevel = static_cast<MappingLevel>(mappingLevel + 1);
63  }
64  return mappingLevel;
65 }
66 
67 /// Computed the hardware id to use for a given mapping level. Will
68 /// assign x,y and z hardware ids for the first 3 dimensions and use
69 /// sequential after.
70 /// TODO: Make this use x for the inner-most loop that is
71 /// distributed to map to x, the next innermost to y and the next innermost to
72 /// z.
73 static Processor getHardwareIdForMapping(MappingLevel level, int dimension) {
74 
75  if (dimension >= kNumHardwareIds || level == Sequential)
76  return Processor::Sequential;
77  switch (level) {
78  case MapGrid:
79  switch (dimension) {
80  case 0:
81  return Processor::BlockX;
82  case 1:
83  return Processor::BlockY;
84  case 2:
85  return Processor::BlockZ;
86  default:
87  return Processor::Sequential;
88  }
89  break;
90  case MapBlock:
91  switch (dimension) {
92  case 0:
93  return Processor::ThreadX;
94  case 1:
95  return Processor::ThreadY;
96  case 2:
97  return Processor::ThreadZ;
98  default:
99  return Processor::Sequential;
100  }
101  default:;
102  }
103  return Processor::Sequential;
104 }
105 
106 /// Add mapping information to the given parallel loop. Do not add
107 /// mapping information if the loop already has it. Also, don't
108 /// start a mapping at a nested loop.
109 static void mapParallelOp(ParallelOp parallelOp,
110  MappingLevel mappingLevel = MapGrid) {
111  // Do not try to add a mapping to already mapped loops or nested loops.
112  if (parallelOp->getAttr(getMappingAttrName()) ||
113  ((mappingLevel == MapGrid) && parallelOp->getParentOfType<ParallelOp>()))
114  return;
115 
116  MLIRContext *ctx = parallelOp.getContext();
117  Builder b(ctx);
119  attrs.reserve(parallelOp.getNumLoops());
120  for (int i = 0, e = parallelOp.getNumLoops(); i < e; ++i) {
121  attrs.push_back(b.getAttr<ParallelLoopDimMappingAttr>(
122  getHardwareIdForMapping(mappingLevel, i), b.getDimIdentityMap(),
123  b.getDimIdentityMap()));
124  }
125  (void)setMappingAttr(parallelOp, attrs);
126  ++mappingLevel;
127  // Parallel loop operations are immediately nested, so do not use
128  // walk but just iterate over the operations.
129  for (Operation &op : *parallelOp.getBody()) {
130  if (ParallelOp nested = dyn_cast<ParallelOp>(op))
131  mapParallelOp(nested, mappingLevel);
132  }
133 }
134 
135 namespace {
136 struct GpuMapParallelLoopsPass
137  : public impl::GpuMapParallelLoopsPassBase<GpuMapParallelLoopsPass> {
138  void runOnOperation() override {
139  for (Region &region : getOperation()->getRegions()) {
140  region.walk([](ParallelOp parallelOp) { mapParallelOp(parallelOp); });
141  }
142  }
143 };
144 
145 } // namespace
146 } // namespace gpu
147 } // namespace mlir
148 
149 std::unique_ptr<mlir::OperationPass<mlir::func::FuncOp>>
151  return std::make_unique<gpu::GpuMapParallelLoopsPass>();
152 }
This class is a general helper class for creating context-global objects like types,...
Definition: Builders.h:49
AffineMap getDimIdentityMap()
Definition: Builders.cpp:346
Attr getAttr(Args &&...args)
Get or construct an instance of the attribute Attr with provided arguments.
Definition: Builders.h:95
MLIRContext is the top-level object for a collection of MLIR operations.
Definition: MLIRContext.h:56
Operation is a basic unit of execution within MLIR.
Definition: Operation.h:31
This class contains a list of basic blocks and a link to the parent operation it is attached to.
Definition: Region.h:26
static Processor getHardwareIdForMapping(MappingLevel level, int dimension)
Computed the hardware id to use for a given mapping level.
static MappingLevel & operator++(MappingLevel &mappingLevel)
Bounded increment on MappingLevel.
static void mapParallelOp(ParallelOp parallelOp, MappingLevel mappingLevel=MapGrid)
Add mapping information to the given parallel loop.
LogicalResult setMappingAttr(scf::ParallelOp ploopOp, ArrayRef< ParallelLoopDimMappingAttr > mapping)
Sets the mapping attribute of a scf.parallel operation.
static constexpr int kNumHardwareIds
StringRef getMappingAttrName()
Name of the mapping attribute produced by loop mappers.
Include the generated interface declarations.
LogicalResult success(bool isSuccess=true)
Utility function to generate a LogicalResult.
Definition: LogicalResult.h:56
std::unique_ptr< OperationPass< func::FuncOp > > createGpuMapParallelLoopsPass()
Maps the parallel loops found in the given function to workgroups.
This class represents an efficient way to signal success or failure.
Definition: LogicalResult.h:26