xref: /llvm-project/mlir/lib/Conversion/GPUToROCDL/LowerGpuOpsToROCDLOps.cpp (revision f6076bd81fce06bb29f83d370b8298110ecc2f99)
1 //===- LowerGpuOpsToROCDLOps.cpp - MLIR GPU to ROCDL lowering passes ------===//
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 a pass to generate ROCDLIR operations for higher-level
10 // GPU operations.
11 //
12 //===----------------------------------------------------------------------===//
13 
14 #include "mlir/Conversion/ControlFlowToLLVM/ControlFlowToLLVM.h"
15 #include "mlir/Conversion/GPUToROCDL/GPUToROCDLPass.h"
16 
17 #include "mlir/Conversion/AMDGPUToROCDL/AMDGPUToROCDL.h"
18 #include "mlir/Conversion/ArithToLLVM/ArithToLLVM.h"
19 #include "mlir/Conversion/FuncToLLVM/ConvertFuncToLLVM.h"
20 #include "mlir/Conversion/LLVMCommon/ConversionTarget.h"
21 #include "mlir/Conversion/LLVMCommon/LoweringOptions.h"
22 #include "mlir/Conversion/LLVMCommon/Pattern.h"
23 #include "mlir/Conversion/LLVMCommon/TypeConverter.h"
24 #include "mlir/Conversion/MemRefToLLVM/MemRefToLLVM.h"
25 #include "mlir/Conversion/VectorToLLVM/ConvertVectorToLLVM.h"
26 #include "mlir/Dialect/Func/IR/FuncOps.h"
27 #include "mlir/Dialect/GPU/IR/GPUDialect.h"
28 #include "mlir/Dialect/GPU/Transforms/Passes.h"
29 #include "mlir/Dialect/LLVMIR/LLVMDialect.h"
30 #include "mlir/Dialect/LLVMIR/ROCDLDialect.h"
31 #include "mlir/Dialect/Math/IR/Math.h"
32 #include "mlir/Dialect/Vector/IR/VectorOps.h"
33 #include "mlir/IR/BuiltinAttributes.h"
34 #include "mlir/Pass/Pass.h"
35 #include "mlir/Transforms/DialectConversion.h"
36 #include "mlir/Transforms/GreedyPatternRewriteDriver.h"
37 #include "llvm/Support/FormatVariadic.h"
38 
39 #include "../GPUCommon/GPUOpsLowering.h"
40 #include "../GPUCommon/IndexIntrinsicsOpLowering.h"
41 #include "../GPUCommon/OpToFuncCallLowering.h"
42 
43 namespace mlir {
44 #define GEN_PASS_DEF_CONVERTGPUOPSTOROCDLOPS
45 #include "mlir/Conversion/Passes.h.inc"
46 } // namespace mlir
47 
48 using namespace mlir;
49 
50 /// Returns true if the given `gpu.func` can be safely called using the bare
51 /// pointer calling convention.
52 static bool canBeCalledWithBarePointers(gpu::GPUFuncOp func) {
53   bool canBeBare = true;
54   for (Type type : func.getArgumentTypes())
55     if (auto memrefTy = type.dyn_cast<BaseMemRefType>())
56       canBeBare &= LLVMTypeConverter::canConvertToBarePtr(memrefTy);
57   return canBeBare;
58 }
59 
60 namespace {
61 
62 /// Import the GPU Ops to ROCDL Patterns.
63 #include "GPUToROCDL.cpp.inc"
64 
65 // A pass that replaces all occurrences of GPU device operations with their
66 // corresponding ROCDL equivalent.
67 //
68 // This pass only handles device code and is not meant to be run on GPU host
69 // code.
70 struct LowerGpuOpsToROCDLOpsPass
71     : public impl::ConvertGpuOpsToROCDLOpsBase<LowerGpuOpsToROCDLOpsPass> {
72   LowerGpuOpsToROCDLOpsPass() = default;
73   LowerGpuOpsToROCDLOpsPass(const std::string &chipset, unsigned indexBitwidth,
74                             bool useBarePtrCallConv,
75                             gpu::amd::Runtime runtime) {
76     if (this->chipset.getNumOccurrences() == 0)
77       this->chipset = chipset;
78     if (this->indexBitwidth.getNumOccurrences() == 0)
79       this->indexBitwidth = indexBitwidth;
80     if (this->useBarePtrCallConv.getNumOccurrences() == 0)
81       this->useBarePtrCallConv = useBarePtrCallConv;
82     if (this->runtime.getNumOccurrences() == 0)
83       this->runtime = runtime;
84   }
85 
86   void runOnOperation() override {
87     gpu::GPUModuleOp m = getOperation();
88     MLIRContext *ctx = m.getContext();
89 
90     // Request C wrapper emission.
91     for (auto func : m.getOps<func::FuncOp>()) {
92       func->setAttr(LLVM::LLVMDialect::getEmitCWrapperAttrName(),
93                     UnitAttr::get(ctx));
94     }
95 
96     FailureOr<amdgpu::Chipset> maybeChipset = amdgpu::Chipset::parse(chipset);
97     if (failed(maybeChipset)) {
98       emitError(UnknownLoc::get(ctx), "Invalid chipset name: " + chipset);
99       return signalPassFailure();
100     }
101 
102     /// Customize the bitwidth used for the device side index computations.
103     LowerToLLVMOptions options(
104         ctx, DataLayout(cast<DataLayoutOpInterface>(m.getOperation())));
105     if (indexBitwidth != kDeriveIndexBitwidthFromDataLayout)
106       options.overrideIndexBitwidth(indexBitwidth);
107 
108     if (useBarePtrCallConv) {
109       options.useBarePtrCallConv = true;
110       WalkResult canUseBarePointers =
111           m.walk([](gpu::GPUFuncOp func) -> WalkResult {
112             if (canBeCalledWithBarePointers(func))
113               return WalkResult::advance();
114             return WalkResult::interrupt();
115           });
116       if (canUseBarePointers.wasInterrupted()) {
117         emitError(UnknownLoc::get(ctx),
118                   "bare pointer calling convention requires all memrefs to "
119                   "have static shape and use the identity map");
120         return signalPassFailure();
121       }
122     }
123 
124     LLVMTypeConverter converter(ctx, options);
125 
126     RewritePatternSet patterns(ctx);
127     RewritePatternSet llvmPatterns(ctx);
128 
129     populateGpuRewritePatterns(patterns);
130     (void)applyPatternsAndFoldGreedily(m, std::move(patterns));
131 
132     mlir::arith::populateArithToLLVMConversionPatterns(converter, llvmPatterns);
133     populateAMDGPUToROCDLConversionPatterns(converter, llvmPatterns,
134                                             *maybeChipset);
135     populateVectorToLLVMConversionPatterns(converter, llvmPatterns);
136     cf::populateControlFlowToLLVMConversionPatterns(converter, llvmPatterns);
137     populateFuncToLLVMConversionPatterns(converter, llvmPatterns);
138     populateMemRefToLLVMConversionPatterns(converter, llvmPatterns);
139     populateGpuToROCDLConversionPatterns(converter, llvmPatterns, runtime);
140     LLVMConversionTarget target(getContext());
141     configureGpuToROCDLConversionLegality(target);
142     if (failed(applyPartialConversion(m, target, std::move(llvmPatterns))))
143       signalPassFailure();
144 
145     // Manually rewrite known block size attributes so the LLVMIR translation
146     // infrastructure can pick them up.
147     m.walk([ctx](LLVM::LLVMFuncOp op) {
148       if (auto blockSizes =
149               op->removeAttr(gpu::GPUFuncOp::getKnownBlockSizeAttrName())
150                   .dyn_cast_or_null<DenseI32ArrayAttr>()) {
151         op->setAttr(ROCDL::ROCDLDialect::getReqdWorkGroupSizeAttrName(),
152                     blockSizes);
153         // Also set up the rocdl.flat_work_group_size attribute to prevent
154         // conflicting metadata.
155         uint32_t flatSize = 1;
156         for (uint32_t size : blockSizes.asArrayRef()) {
157           flatSize *= size;
158         }
159         StringAttr flatSizeAttr =
160             StringAttr::get(ctx, Twine(flatSize) + "," + Twine(flatSize));
161         op->setAttr(ROCDL::ROCDLDialect::getFlatWorkGroupSizeAttrName(),
162                     flatSizeAttr);
163       }
164     });
165   }
166 };
167 
168 } // namespace
169 
170 void mlir::configureGpuToROCDLConversionLegality(ConversionTarget &target) {
171   target.addIllegalOp<func::FuncOp>();
172   target.addLegalDialect<::mlir::LLVM::LLVMDialect>();
173   target.addLegalDialect<ROCDL::ROCDLDialect>();
174   target.addIllegalDialect<gpu::GPUDialect>();
175   target.addIllegalOp<LLVM::CosOp, LLVM::ExpOp, LLVM::Exp2Op, LLVM::FAbsOp,
176                       LLVM::FCeilOp, LLVM::FFloorOp, LLVM::LogOp, LLVM::Log10Op,
177                       LLVM::Log2Op, LLVM::PowOp, LLVM::SinOp, LLVM::SqrtOp>();
178 
179   // TODO: Remove once we support replacing non-root ops.
180   target.addLegalOp<gpu::YieldOp, gpu::GPUModuleOp, gpu::ModuleEndOp>();
181 }
182 
183 template <typename OpTy>
184 static void populateOpPatterns(LLVMTypeConverter &converter,
185                                RewritePatternSet &patterns, StringRef f32Func,
186                                StringRef f64Func) {
187   patterns.add<ScalarizeVectorOpLowering<OpTy>>(converter);
188   patterns.add<OpToFuncCallLowering<OpTy>>(converter, f32Func, f64Func);
189 }
190 
191 void mlir::populateGpuToROCDLConversionPatterns(
192     LLVMTypeConverter &converter, RewritePatternSet &patterns,
193     mlir::gpu::amd::Runtime runtime) {
194   using mlir::gpu::amd::Runtime;
195 
196   populateWithGenerated(patterns);
197   patterns
198       .add<GPUIndexIntrinsicOpLowering<gpu::ThreadIdOp, ROCDL::ThreadIdXOp,
199                                        ROCDL::ThreadIdYOp, ROCDL::ThreadIdZOp>>(
200           converter, gpu::GPUFuncOp::getKnownBlockSizeAttrName());
201   patterns.add<GPUIndexIntrinsicOpLowering<
202       gpu::BlockIdOp, ROCDL::BlockIdXOp, ROCDL::BlockIdYOp, ROCDL::BlockIdZOp>>(
203       converter, gpu::GPUFuncOp::getKnownGridSizeAttrName());
204   patterns
205       .add<GPUIndexIntrinsicOpLowering<gpu::BlockDimOp, ROCDL::BlockDimXOp,
206                                        ROCDL::BlockDimYOp, ROCDL::BlockDimZOp>,
207            GPUIndexIntrinsicOpLowering<gpu::GridDimOp, ROCDL::GridDimXOp,
208                                        ROCDL::GridDimYOp, ROCDL::GridDimZOp>,
209            GPUReturnOpLowering>(converter);
210   patterns.add<GPUFuncOpLowering>(
211       converter, /*allocaAddrSpace=*/5,
212       StringAttr::get(&converter.getContext(),
213                       ROCDL::ROCDLDialect::getKernelFuncAttrName()));
214   if (Runtime::HIP == runtime) {
215     patterns.add<GPUPrintfOpToHIPLowering>(converter);
216   } else if (Runtime::OpenCL == runtime) {
217     // Use address space = 4 to match the OpenCL definition of printf()
218     patterns.add<GPUPrintfOpToLLVMCallLowering>(converter, /*addressSpace=*/4);
219   }
220 
221   populateOpPatterns<math::AbsFOp>(converter, patterns, "__ocml_fabs_f32",
222                                    "__ocml_fabs_f64");
223   populateOpPatterns<math::AtanOp>(converter, patterns, "__ocml_atan_f32",
224                                    "__ocml_atan_f64");
225   populateOpPatterns<math::Atan2Op>(converter, patterns, "__ocml_atan2_f32",
226                                     "__ocml_atan2_f64");
227   populateOpPatterns<math::CeilOp>(converter, patterns, "__ocml_ceil_f32",
228                                    "__ocml_ceil_f64");
229   populateOpPatterns<math::CosOp>(converter, patterns, "__ocml_cos_f32",
230                                   "__ocml_cos_f64");
231   populateOpPatterns<math::ExpOp>(converter, patterns, "__ocml_exp_f32",
232                                   "__ocml_exp_f64");
233   populateOpPatterns<math::Exp2Op>(converter, patterns, "__ocml_exp2_f32",
234                                    "__ocml_exp2_f64");
235   populateOpPatterns<math::ExpM1Op>(converter, patterns, "__ocml_expm1_f32",
236                                     "__ocml_expm1_f64");
237   populateOpPatterns<math::FloorOp>(converter, patterns, "__ocml_floor_f32",
238                                     "__ocml_floor_f64");
239   populateOpPatterns<math::LogOp>(converter, patterns, "__ocml_log_f32",
240                                   "__ocml_log_f64");
241   populateOpPatterns<math::Log10Op>(converter, patterns, "__ocml_log10_f32",
242                                     "__ocml_log10_f64");
243   populateOpPatterns<math::Log1pOp>(converter, patterns, "__ocml_log1p_f32",
244                                     "__ocml_log1p_f64");
245   populateOpPatterns<math::Log2Op>(converter, patterns, "__ocml_log2_f32",
246                                    "__ocml_log2_f64");
247   populateOpPatterns<math::PowFOp>(converter, patterns, "__ocml_pow_f32",
248                                    "__ocml_pow_f64");
249   populateOpPatterns<math::RsqrtOp>(converter, patterns, "__ocml_rsqrt_f32",
250                                     "__ocml_rsqrt_f64");
251   populateOpPatterns<math::SinOp>(converter, patterns, "__ocml_sin_f32",
252                                   "__ocml_sin_f64");
253   populateOpPatterns<math::SqrtOp>(converter, patterns, "__ocml_sqrt_f32",
254                                    "__ocml_sqrt_f64");
255   populateOpPatterns<math::TanhOp>(converter, patterns, "__ocml_tanh_f32",
256                                    "__ocml_tanh_f64");
257 }
258 
259 std::unique_ptr<OperationPass<gpu::GPUModuleOp>>
260 mlir::createLowerGpuOpsToROCDLOpsPass(const std::string &chipset,
261                                       unsigned indexBitwidth,
262                                       bool useBarePtrCallConv,
263                                       gpu::amd::Runtime runtime) {
264   return std::make_unique<LowerGpuOpsToROCDLOpsPass>(
265       chipset, indexBitwidth, useBarePtrCallConv, runtime);
266 }
267