1 //===- LowerGpuOpsToNVVMOps.cpp - MLIR GPU to NVVM 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 NVVMIR operations for higher-level
10 // GPU operations.
11 //
12 //===----------------------------------------------------------------------===//
13 
14 #include "mlir/Conversion/GPUToNVVM/GPUToNVVMPass.h"
15 
16 #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h"
17 #include "mlir/Dialect/GPU/GPUDialect.h"
18 #include "mlir/Dialect/GPU/Passes.h"
19 #include "mlir/Dialect/LLVMIR/NVVMDialect.h"
20 #include "mlir/Dialect/Math/IR/Math.h"
21 #include "mlir/IR/BlockAndValueMapping.h"
22 #include "mlir/Transforms/DialectConversion.h"
23 #include "mlir/Transforms/GreedyPatternRewriteDriver.h"
24 #include "llvm/Support/FormatVariadic.h"
25 
26 #include "../GPUCommon/GPUOpsLowering.h"
27 #include "../GPUCommon/IndexIntrinsicsOpLowering.h"
28 #include "../GPUCommon/OpToFuncCallLowering.h"
29 #include "../PassDetail.h"
30 
31 using namespace mlir;
32 
33 namespace {
34 
35 struct GPUShuffleOpLowering : public ConvertOpToLLVMPattern<gpu::ShuffleOp> {
36   using ConvertOpToLLVMPattern<gpu::ShuffleOp>::ConvertOpToLLVMPattern;
37 
38   /// Lowers a shuffle to the corresponding NVVM op.
39   ///
40   /// Convert the `width` argument into an activeMask (a bitmask which specifies
41   /// which threads participate in the shuffle) and a maskAndClamp (specifying
42   /// the highest lane which participates in the shuffle).
43   ///
44   ///     %one = llvm.constant(1 : i32) : i32
45   ///     %shl = llvm.shl %one, %width : i32
46   ///     %active_mask = llvm.sub %shl, %one : i32
47   ///     %mask_and_clamp = llvm.sub %width, %one : i32
48   ///     %shfl = nvvm.shfl.sync.bfly %active_mask, %value, %offset,
49   ///         %mask_and_clamp : !llvm<"{ float, i1 }">
50   ///     %shfl_value = llvm.extractvalue %shfl[0 : index] :
51   ///         !llvm<"{ float, i1 }">
52   ///     %shfl_pred = llvm.extractvalue %shfl[1 : index] :
53   ///         !llvm<"{ float, i1 }">
54   LogicalResult
55   matchAndRewrite(gpu::ShuffleOp op, ArrayRef<Value> operands,
56                   ConversionPatternRewriter &rewriter) const override {
57     Location loc = op->getLoc();
58     gpu::ShuffleOpAdaptor adaptor(operands);
59 
60     auto valueTy = adaptor.value().getType();
61     auto int32Type = IntegerType::get(rewriter.getContext(), 32);
62     auto predTy = IntegerType::get(rewriter.getContext(), 1);
63     auto resultTy = LLVM::LLVMStructType::getLiteral(rewriter.getContext(),
64                                                      {valueTy, predTy});
65 
66     Value one = rewriter.create<LLVM::ConstantOp>(
67         loc, int32Type, rewriter.getI32IntegerAttr(1));
68     // Bit mask of active lanes: `(1 << activeWidth) - 1`.
69     Value activeMask = rewriter.create<LLVM::SubOp>(
70         loc, int32Type,
71         rewriter.create<LLVM::ShlOp>(loc, int32Type, one, adaptor.width()),
72         one);
73     // Clamp lane: `activeWidth - 1`
74     Value maskAndClamp =
75         rewriter.create<LLVM::SubOp>(loc, int32Type, adaptor.width(), one);
76 
77     auto returnValueAndIsValidAttr = rewriter.getUnitAttr();
78     Value shfl = rewriter.create<NVVM::ShflBflyOp>(
79         loc, resultTy, activeMask, adaptor.value(), adaptor.offset(),
80         maskAndClamp, returnValueAndIsValidAttr);
81     Value shflValue = rewriter.create<LLVM::ExtractValueOp>(
82         loc, valueTy, shfl, rewriter.getIndexArrayAttr(0));
83     Value isActiveSrcLane = rewriter.create<LLVM::ExtractValueOp>(
84         loc, predTy, shfl, rewriter.getIndexArrayAttr(1));
85 
86     rewriter.replaceOp(op, {shflValue, isActiveSrcLane});
87     return success();
88   }
89 };
90 
91 /// Import the GPU Ops to NVVM Patterns.
92 #include "GPUToNVVM.cpp.inc"
93 
94 /// A pass that replaces all occurrences of GPU device operations with their
95 /// corresponding NVVM equivalent.
96 ///
97 /// This pass only handles device code and is not meant to be run on GPU host
98 /// code.
99 struct LowerGpuOpsToNVVMOpsPass
100     : public ConvertGpuOpsToNVVMOpsBase<LowerGpuOpsToNVVMOpsPass> {
101   LowerGpuOpsToNVVMOpsPass() = default;
102   LowerGpuOpsToNVVMOpsPass(unsigned indexBitwidth) {
103     this->indexBitwidth = indexBitwidth;
104   }
105 
106   void runOnOperation() override {
107     gpu::GPUModuleOp m = getOperation();
108 
109     /// Customize the bitwidth used for the device side index computations.
110     LowerToLLVMOptions options = {/*useBarePtrCallConv =*/false,
111                                   /*emitCWrappers =*/true,
112                                   /*indexBitwidth =*/indexBitwidth,
113                                   /*useAlignedAlloc =*/false};
114 
115     /// MemRef conversion for GPU to NVVM lowering. The GPU dialect uses memory
116     /// space 5 for private memory attributions, but NVVM represents private
117     /// memory allocations as local `alloca`s in the default address space. This
118     /// converter drops the private memory space to support the use case above.
119     LLVMTypeConverter converter(m.getContext(), options);
120     converter.addConversion([&](MemRefType type) -> Optional<Type> {
121       if (type.getMemorySpace() != gpu::GPUDialect::getPrivateAddressSpace())
122         return llvm::None;
123       return converter.convertType(MemRefType::Builder(type).setMemorySpace(0));
124     });
125 
126     OwningRewritePatternList patterns, llvmPatterns;
127 
128     // Apply in-dialect lowering first. In-dialect lowering will replace ops
129     // which need to be lowered further, which is not supported by a single
130     // conversion pass.
131     populateGpuRewritePatterns(m.getContext(), patterns);
132     (void)applyPatternsAndFoldGreedily(m, std::move(patterns));
133 
134     populateStdToLLVMConversionPatterns(converter, llvmPatterns);
135     populateGpuToNVVMConversionPatterns(converter, llvmPatterns);
136     LLVMConversionTarget target(getContext());
137     configureGpuToNVVMConversionLegality(target);
138     if (failed(applyPartialConversion(m, target, std::move(llvmPatterns))))
139       signalPassFailure();
140   }
141 };
142 
143 } // anonymous namespace
144 
145 void mlir::configureGpuToNVVMConversionLegality(ConversionTarget &target) {
146   target.addIllegalOp<FuncOp>();
147   target.addLegalDialect<::mlir::LLVM::LLVMDialect>();
148   target.addLegalDialect<::mlir::NVVM::NVVMDialect>();
149   target.addIllegalDialect<gpu::GPUDialect>();
150   target.addIllegalOp<LLVM::CosOp, LLVM::ExpOp, LLVM::FAbsOp, LLVM::FCeilOp,
151                       LLVM::FFloorOp, LLVM::LogOp, LLVM::Log10Op, LLVM::Log2Op,
152                       LLVM::PowOp, LLVM::SinOp, LLVM::SqrtOp>();
153 
154   // TODO: Remove once we support replacing non-root ops.
155   target.addLegalOp<gpu::YieldOp, gpu::GPUModuleOp, gpu::ModuleEndOp>();
156 }
157 
158 void mlir::populateGpuToNVVMConversionPatterns(
159     LLVMTypeConverter &converter, OwningRewritePatternList &patterns) {
160   populateWithGenerated(converter.getDialect()->getContext(), patterns);
161   patterns
162       .insert<GPUIndexIntrinsicOpLowering<gpu::ThreadIdOp, NVVM::ThreadIdXOp,
163                                           NVVM::ThreadIdYOp, NVVM::ThreadIdZOp>,
164               GPUIndexIntrinsicOpLowering<gpu::BlockDimOp, NVVM::BlockDimXOp,
165                                           NVVM::BlockDimYOp, NVVM::BlockDimZOp>,
166               GPUIndexIntrinsicOpLowering<gpu::BlockIdOp, NVVM::BlockIdXOp,
167                                           NVVM::BlockIdYOp, NVVM::BlockIdZOp>,
168               GPUIndexIntrinsicOpLowering<gpu::GridDimOp, NVVM::GridDimXOp,
169                                           NVVM::GridDimYOp, NVVM::GridDimZOp>,
170               GPUShuffleOpLowering, GPUReturnOpLowering>(converter);
171 
172   // Explicitly drop memory space when lowering private memory
173   // attributions since NVVM models it as `alloca`s in the default
174   // memory space and does not support `alloca`s with addrspace(5).
175   patterns.insert<GPUFuncOpLowering>(
176       converter, /*allocaAddrSpace=*/0,
177       Identifier::get(NVVM::NVVMDialect::getKernelFuncAttrName(),
178                       &converter.getContext()));
179 
180   patterns.insert<OpToFuncCallLowering<AbsFOp>>(converter, "__nv_fabsf",
181                                                 "__nv_fabs");
182   patterns.insert<OpToFuncCallLowering<math::AtanOp>>(converter, "__nv_atanf",
183                                                       "__nv_atan");
184   patterns.insert<OpToFuncCallLowering<math::Atan2Op>>(converter, "__nv_atan2f",
185                                                        "__nv_atan2");
186   patterns.insert<OpToFuncCallLowering<CeilFOp>>(converter, "__nv_ceilf",
187                                                  "__nv_ceil");
188   patterns.insert<OpToFuncCallLowering<math::CosOp>>(converter, "__nv_cosf",
189                                                      "__nv_cos");
190   patterns.insert<OpToFuncCallLowering<math::ExpOp>>(converter, "__nv_expf",
191                                                      "__nv_exp");
192   patterns.insert<OpToFuncCallLowering<math::ExpM1Op>>(converter, "__nv_expm1f",
193                                                        "__nv_expm1");
194   patterns.insert<OpToFuncCallLowering<FloorFOp>>(converter, "__nv_floorf",
195                                                   "__nv_floor");
196   patterns.insert<OpToFuncCallLowering<math::LogOp>>(converter, "__nv_logf",
197                                                      "__nv_log");
198   patterns.insert<OpToFuncCallLowering<math::Log1pOp>>(converter, "__nv_log1pf",
199                                                        "__nv_log1p");
200   patterns.insert<OpToFuncCallLowering<math::Log10Op>>(converter, "__nv_log10f",
201                                                        "__nv_log10");
202   patterns.insert<OpToFuncCallLowering<math::Log2Op>>(converter, "__nv_log2f",
203                                                       "__nv_log2");
204   patterns.insert<OpToFuncCallLowering<math::PowFOp>>(converter, "__nv_powf",
205                                                       "__nv_pow");
206   patterns.insert<OpToFuncCallLowering<math::RsqrtOp>>(converter, "__nv_rsqrtf",
207                                                        "__nv_rsqrt");
208   patterns.insert<OpToFuncCallLowering<math::SinOp>>(converter, "__nv_sinf",
209                                                      "__nv_sin");
210   patterns.insert<OpToFuncCallLowering<math::SqrtOp>>(converter, "__nv_sqrtf",
211                                                       "__nv_sqrt");
212   patterns.insert<OpToFuncCallLowering<math::TanhOp>>(converter, "__nv_tanhf",
213                                                       "__nv_tanh");
214 }
215 
216 std::unique_ptr<OperationPass<gpu::GPUModuleOp>>
217 mlir::createLowerGpuOpsToNVVMOpsPass(unsigned indexBitwidth) {
218   return std::make_unique<LowerGpuOpsToNVVMOpsPass>(indexBitwidth);
219 }
220