e21adfa32d
This makes ignoring a result explicit by the user, and helps to prevent accidental errors with dropped results. Marking LogicalResult as no discard was always the intention from the beginning, but got lost along the way. Differential Revision: https://reviews.llvm.org/D95841
212 lines
9.9 KiB
C++
212 lines
9.9 KiB
C++
//===- LowerGpuOpsToNVVMOps.cpp - MLIR GPU to NVVM lowering passes --------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// This file implements a pass to generate NVVMIR operations for higher-level
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// GPU operations.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Conversion/GPUToNVVM/GPUToNVVMPass.h"
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#include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h"
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#include "mlir/Dialect/GPU/GPUDialect.h"
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#include "mlir/Dialect/GPU/Passes.h"
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#include "mlir/Dialect/LLVMIR/NVVMDialect.h"
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#include "mlir/IR/BlockAndValueMapping.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
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#include "llvm/Support/FormatVariadic.h"
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#include "../GPUCommon/GPUOpsLowering.h"
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#include "../GPUCommon/IndexIntrinsicsOpLowering.h"
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#include "../GPUCommon/OpToFuncCallLowering.h"
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#include "../PassDetail.h"
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using namespace mlir;
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namespace {
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struct GPUShuffleOpLowering : public ConvertOpToLLVMPattern<gpu::ShuffleOp> {
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using ConvertOpToLLVMPattern<gpu::ShuffleOp>::ConvertOpToLLVMPattern;
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/// Lowers a shuffle to the corresponding NVVM op.
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///
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/// Convert the `width` argument into an activeMask (a bitmask which specifies
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/// which threads participate in the shuffle) and a maskAndClamp (specifying
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/// the highest lane which participates in the shuffle).
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///
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/// %one = llvm.constant(1 : i32) : i32
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/// %shl = llvm.shl %one, %width : i32
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/// %active_mask = llvm.sub %shl, %one : i32
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/// %mask_and_clamp = llvm.sub %width, %one : i32
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/// %shfl = nvvm.shfl.sync.bfly %active_mask, %value, %offset,
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/// %mask_and_clamp : !llvm<"{ float, i1 }">
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/// %shfl_value = llvm.extractvalue %shfl[0 : index] :
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/// !llvm<"{ float, i1 }">
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/// %shfl_pred = llvm.extractvalue %shfl[1 : index] :
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/// !llvm<"{ float, i1 }">
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LogicalResult
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matchAndRewrite(gpu::ShuffleOp op, ArrayRef<Value> operands,
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ConversionPatternRewriter &rewriter) const override {
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Location loc = op->getLoc();
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gpu::ShuffleOpAdaptor adaptor(operands);
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auto valueTy = adaptor.value().getType();
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auto int32Type = IntegerType::get(rewriter.getContext(), 32);
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auto predTy = IntegerType::get(rewriter.getContext(), 1);
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auto resultTy = LLVM::LLVMStructType::getLiteral(rewriter.getContext(),
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{valueTy, predTy});
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Value one = rewriter.create<LLVM::ConstantOp>(
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loc, int32Type, rewriter.getI32IntegerAttr(1));
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// Bit mask of active lanes: `(1 << activeWidth) - 1`.
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Value activeMask = rewriter.create<LLVM::SubOp>(
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loc, int32Type,
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rewriter.create<LLVM::ShlOp>(loc, int32Type, one, adaptor.width()),
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one);
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// Clamp lane: `activeWidth - 1`
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Value maskAndClamp =
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rewriter.create<LLVM::SubOp>(loc, int32Type, adaptor.width(), one);
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auto returnValueAndIsValidAttr = rewriter.getUnitAttr();
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Value shfl = rewriter.create<NVVM::ShflBflyOp>(
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loc, resultTy, activeMask, adaptor.value(), adaptor.offset(),
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maskAndClamp, returnValueAndIsValidAttr);
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Value shflValue = rewriter.create<LLVM::ExtractValueOp>(
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loc, valueTy, shfl, rewriter.getIndexArrayAttr(0));
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Value isActiveSrcLane = rewriter.create<LLVM::ExtractValueOp>(
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loc, predTy, shfl, rewriter.getIndexArrayAttr(1));
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rewriter.replaceOp(op, {shflValue, isActiveSrcLane});
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return success();
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}
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};
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/// Import the GPU Ops to NVVM Patterns.
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#include "GPUToNVVM.cpp.inc"
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/// A pass that replaces all occurrences of GPU device operations with their
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/// corresponding NVVM equivalent.
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///
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/// This pass only handles device code and is not meant to be run on GPU host
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/// code.
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struct LowerGpuOpsToNVVMOpsPass
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: public ConvertGpuOpsToNVVMOpsBase<LowerGpuOpsToNVVMOpsPass> {
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LowerGpuOpsToNVVMOpsPass() = default;
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LowerGpuOpsToNVVMOpsPass(unsigned indexBitwidth) {
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this->indexBitwidth = indexBitwidth;
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}
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void runOnOperation() override {
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gpu::GPUModuleOp m = getOperation();
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/// Customize the bitwidth used for the device side index computations.
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LowerToLLVMOptions options = {/*useBarePtrCallConv =*/false,
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/*emitCWrappers =*/true,
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/*indexBitwidth =*/indexBitwidth,
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/*useAlignedAlloc =*/false};
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/// MemRef conversion for GPU to NVVM lowering. The GPU dialect uses memory
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/// space 5 for private memory attributions, but NVVM represents private
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/// memory allocations as local `alloca`s in the default address space. This
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/// converter drops the private memory space to support the use case above.
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LLVMTypeConverter converter(m.getContext(), options);
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converter.addConversion([&](MemRefType type) -> Optional<Type> {
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if (type.getMemorySpace() != gpu::GPUDialect::getPrivateAddressSpace())
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return llvm::None;
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return converter.convertType(MemRefType::Builder(type).setMemorySpace(0));
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});
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OwningRewritePatternList patterns, llvmPatterns;
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// Apply in-dialect lowering first. In-dialect lowering will replace ops
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// which need to be lowered further, which is not supported by a single
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// conversion pass.
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populateGpuRewritePatterns(m.getContext(), patterns);
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(void)applyPatternsAndFoldGreedily(m, std::move(patterns));
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populateStdToLLVMConversionPatterns(converter, llvmPatterns);
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populateGpuToNVVMConversionPatterns(converter, llvmPatterns);
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LLVMConversionTarget target(getContext());
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configureGpuToNVVMConversionLegality(target);
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if (failed(applyPartialConversion(m, target, std::move(llvmPatterns))))
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signalPassFailure();
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}
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};
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} // anonymous namespace
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void mlir::configureGpuToNVVMConversionLegality(ConversionTarget &target) {
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target.addIllegalOp<FuncOp>();
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target.addLegalDialect<::mlir::LLVM::LLVMDialect>();
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target.addLegalDialect<::mlir::NVVM::NVVMDialect>();
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target.addIllegalDialect<gpu::GPUDialect>();
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target.addIllegalOp<LLVM::CosOp, LLVM::ExpOp, LLVM::FAbsOp, LLVM::FCeilOp,
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LLVM::FFloorOp, LLVM::LogOp, LLVM::Log10Op, LLVM::Log2Op,
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LLVM::PowOp, LLVM::SinOp, LLVM::SqrtOp>();
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// TODO: Remove once we support replacing non-root ops.
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target.addLegalOp<gpu::YieldOp, gpu::GPUModuleOp, gpu::ModuleEndOp>();
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}
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void mlir::populateGpuToNVVMConversionPatterns(
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LLVMTypeConverter &converter, OwningRewritePatternList &patterns) {
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populateWithGenerated(converter.getDialect()->getContext(), patterns);
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patterns
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.insert<GPUIndexIntrinsicOpLowering<gpu::ThreadIdOp, NVVM::ThreadIdXOp,
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NVVM::ThreadIdYOp, NVVM::ThreadIdZOp>,
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GPUIndexIntrinsicOpLowering<gpu::BlockDimOp, NVVM::BlockDimXOp,
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NVVM::BlockDimYOp, NVVM::BlockDimZOp>,
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GPUIndexIntrinsicOpLowering<gpu::BlockIdOp, NVVM::BlockIdXOp,
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NVVM::BlockIdYOp, NVVM::BlockIdZOp>,
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GPUIndexIntrinsicOpLowering<gpu::GridDimOp, NVVM::GridDimXOp,
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NVVM::GridDimYOp, NVVM::GridDimZOp>,
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GPUShuffleOpLowering, GPUReturnOpLowering,
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// Explicitly drop memory space when lowering private memory
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// attributions since NVVM models it as `alloca`s in the default
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// memory space and does not support `alloca`s with addrspace(5).
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GPUFuncOpLowering<0>>(converter);
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patterns.insert<OpToFuncCallLowering<AbsFOp>>(converter, "__nv_fabsf",
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"__nv_fabs");
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patterns.insert<OpToFuncCallLowering<AtanOp>>(converter, "__nv_atanf",
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"__nv_atan");
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patterns.insert<OpToFuncCallLowering<Atan2Op>>(converter, "__nv_atan2f",
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"__nv_atan2");
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patterns.insert<OpToFuncCallLowering<CeilFOp>>(converter, "__nv_ceilf",
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"__nv_ceil");
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patterns.insert<OpToFuncCallLowering<CosOp>>(converter, "__nv_cosf",
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"__nv_cos");
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patterns.insert<OpToFuncCallLowering<ExpOp>>(converter, "__nv_expf",
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"__nv_exp");
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patterns.insert<OpToFuncCallLowering<FloorFOp>>(converter, "__nv_floorf",
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"__nv_floor");
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patterns.insert<OpToFuncCallLowering<LogOp>>(converter, "__nv_logf",
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"__nv_log");
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patterns.insert<OpToFuncCallLowering<Log1pOp>>(converter, "__nv_log1pf",
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"__nv_log1p");
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patterns.insert<OpToFuncCallLowering<Log10Op>>(converter, "__nv_log10f",
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"__nv_log10");
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patterns.insert<OpToFuncCallLowering<Log2Op>>(converter, "__nv_log2f",
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"__nv_log2");
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patterns.insert<OpToFuncCallLowering<PowFOp>>(converter, "__nv_powf",
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"__nv_pow");
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patterns.insert<OpToFuncCallLowering<RsqrtOp>>(converter, "__nv_rsqrtf",
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"__nv_rsqrt");
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patterns.insert<OpToFuncCallLowering<SinOp>>(converter, "__nv_sinf",
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"__nv_sin");
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patterns.insert<OpToFuncCallLowering<SqrtOp>>(converter, "__nv_sqrtf",
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"__nv_sqrt");
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patterns.insert<OpToFuncCallLowering<TanhOp>>(converter, "__nv_tanhf",
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"__nv_tanh");
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}
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std::unique_ptr<OperationPass<gpu::GPUModuleOp>>
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mlir::createLowerGpuOpsToNVVMOpsPass(unsigned indexBitwidth) {
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return std::make_unique<LowerGpuOpsToNVVMOpsPass>(indexBitwidth);
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}
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