xref: /llvm-project/mlir/lib/Dialect/GPU/Transforms/KernelOutlining.cpp (revision f1b100c77ba005899c60f3dea74607d5daad3f52)
1 //===- KernelOutlining.cpp - Implementation of GPU kernel outling ---------===//
2 //
3 // Copyright 2019 The MLIR Authors.
4 //
5 // Licensed under the Apache License, Version 2.0 (the "License");
6 // you may not use this file except in compliance with the License.
7 // You may obtain a copy of the License at
8 //
9 //   http://www.apache.org/licenses/LICENSE-2.0
10 //
11 // Unless required by applicable law or agreed to in writing, software
12 // distributed under the License is distributed on an "AS IS" BASIS,
13 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 // See the License for the specific language governing permissions and
15 // limitations under the License.
16 // =============================================================================
17 //
18 // This file implements the GPU dialect kernel outlining pass.
19 //
20 //===----------------------------------------------------------------------===//
21 
22 #include "mlir/Dialect/GPU/GPUDialect.h"
23 #include "mlir/Dialect/GPU/Passes.h"
24 #include "mlir/Dialect/StandardOps/Ops.h"
25 #include "mlir/IR/BlockAndValueMapping.h"
26 #include "mlir/IR/Builders.h"
27 #include "mlir/Pass/Pass.h"
28 
29 using namespace mlir;
30 
31 template <typename OpTy>
32 static void createForAllDimensions(OpBuilder &builder, Location loc,
33                                    SmallVectorImpl<Value *> &values) {
34   for (StringRef dim : {"x", "y", "z"}) {
35     Value *v = builder.create<OpTy>(loc, builder.getIndexType(),
36                                     builder.getStringAttr(dim));
37     values.push_back(v);
38   }
39 }
40 
41 // Add operations generating block/thread ids and gird/block dimensions at the
42 // beginning of `kernelFunc` and replace uses of the respective function args.
43 static void injectGpuIndexOperations(Location loc, FuncOp kernelFunc) {
44   OpBuilder OpBuilder(kernelFunc.getBody());
45   SmallVector<Value *, 12> indexOps;
46   createForAllDimensions<gpu::BlockId>(OpBuilder, loc, indexOps);
47   createForAllDimensions<gpu::ThreadId>(OpBuilder, loc, indexOps);
48   createForAllDimensions<gpu::GridDim>(OpBuilder, loc, indexOps);
49   createForAllDimensions<gpu::BlockDim>(OpBuilder, loc, indexOps);
50   // Replace the leading 12 function args with the respective thread/block index
51   // operations. Iterate backwards since args are erased and indices change.
52   for (int i = 11; i >= 0; --i) {
53     auto &firstBlock = kernelFunc.front();
54     firstBlock.getArgument(i)->replaceAllUsesWith(indexOps[i]);
55     firstBlock.eraseArgument(i);
56   }
57 }
58 
59 // Move all constant arguments of the given kernel function into the function,
60 // thereby reducing the number of kernel arguments.
61 static gpu::LaunchFuncOp inlineConstants(FuncOp kernelFunc,
62                                          gpu::LaunchFuncOp launch) {
63   OpBuilder kernelBuilder(kernelFunc.getBody());
64   auto &firstBlock = kernelFunc.getBody().front();
65   llvm::SmallVector<Value *, 8> newLaunchArgs;
66   for (int i = launch.getNumKernelOperands() - 1; i >= 0; --i) {
67     auto operandOp = launch.getKernelOperand(i)->getDefiningOp();
68     auto constant = dyn_cast_or_null<ConstantOp>(operandOp);
69     if (!constant) {
70       newLaunchArgs.push_back(launch.getKernelOperand(i));
71       continue;
72     }
73     auto newConstant = kernelBuilder.clone(*operandOp);
74     firstBlock.getArgument(i)->replaceAllUsesWith(newConstant->getResult(0));
75     firstBlock.eraseArgument(i);
76   }
77   if (newLaunchArgs.size() == launch.getNumKernelOperands())
78     return launch;
79 
80   std::reverse(newLaunchArgs.begin(), newLaunchArgs.end());
81   OpBuilder LaunchBuilder(launch);
82   SmallVector<Type, 8> newArgumentTypes;
83   newArgumentTypes.reserve(firstBlock.getNumArguments());
84   for (auto value : firstBlock.getArguments()) {
85     newArgumentTypes.push_back(value->getType());
86   }
87   kernelFunc.setType(LaunchBuilder.getFunctionType(newArgumentTypes, {}));
88   auto newLaunch = LaunchBuilder.create<gpu::LaunchFuncOp>(
89       launch.getLoc(), kernelFunc, launch.getGridSizeOperandValues(),
90       launch.getBlockSizeOperandValues(), newLaunchArgs);
91   launch.erase();
92   return newLaunch;
93 }
94 
95 // Outline the `gpu.launch` operation body into a kernel function. Replace
96 // `gpu.return` operations by `std.return` in the generated functions.
97 static FuncOp outlineKernelFunc(gpu::LaunchOp launchOp) {
98   Location loc = launchOp.getLoc();
99   SmallVector<Type, 4> kernelOperandTypes(launchOp.getKernelOperandTypes());
100   FunctionType type =
101       FunctionType::get(kernelOperandTypes, {}, launchOp.getContext());
102   std::string kernelFuncName =
103       Twine(launchOp.getParentOfType<FuncOp>().getName(), "_kernel").str();
104   FuncOp outlinedFunc = FuncOp::create(loc, kernelFuncName, type);
105   outlinedFunc.getBody().takeBody(launchOp.getBody());
106   Builder builder(launchOp.getContext());
107   outlinedFunc.setAttr(gpu::GPUDialect::getKernelFuncAttrName(),
108                        builder.getUnitAttr());
109   injectGpuIndexOperations(loc, outlinedFunc);
110   outlinedFunc.walk([](mlir::gpu::Return op) {
111     OpBuilder replacer(op);
112     replacer.create<ReturnOp>(op.getLoc());
113     op.erase();
114   });
115   return outlinedFunc;
116 }
117 
118 // Replace `gpu.launch` operations with an `gpu.launch_func` operation launching
119 // `kernelFunc`. The kernel func contains the body of the `gpu.launch` with
120 // constant region arguments inlined.
121 static void convertToLaunchFuncOp(gpu::LaunchOp &launchOp, FuncOp kernelFunc) {
122   OpBuilder builder(launchOp);
123   SmallVector<Value *, 4> kernelOperandValues(
124       launchOp.getKernelOperandValues());
125   auto launchFuncOp = builder.create<gpu::LaunchFuncOp>(
126       launchOp.getLoc(), kernelFunc, launchOp.getGridSizeOperandValues(),
127       launchOp.getBlockSizeOperandValues(), kernelOperandValues);
128   inlineConstants(kernelFunc, launchFuncOp);
129   launchOp.erase();
130 }
131 
132 namespace {
133 
134 class GpuKernelOutliningPass : public ModulePass<GpuKernelOutliningPass> {
135 public:
136   void runOnModule() override {
137     ModuleManager moduleManager(getModule());
138     for (auto func : getModule().getOps<FuncOp>()) {
139       func.walk([&](mlir::gpu::LaunchOp op) {
140         FuncOp outlinedFunc = outlineKernelFunc(op);
141         moduleManager.insert(outlinedFunc);
142         convertToLaunchFuncOp(op, outlinedFunc);
143       });
144     }
145   }
146 };
147 
148 } // namespace
149 
150 std::unique_ptr<OpPassBase<ModuleOp>> mlir::createGpuKernelOutliningPass() {
151   return std::make_unique<GpuKernelOutliningPass>();
152 }
153 
154 static PassRegistration<GpuKernelOutliningPass>
155     pass("gpu-kernel-outlining",
156          "Outline gpu.launch bodies to kernel functions.");
157