[BACKEND] Extracting numWarps from tritonGPU module (#39)
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@@ -37,12 +37,6 @@ def ConvertTritonGPUToLLVM : Pass<"convert-triton-gpu-to-llvm", "mlir::ModuleOp"
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"mlir::scf::SCFDialect",
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"mlir::triton::TritonDialect",
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"mlir::triton::gpu::TritonGPUDialect"];
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let options = [
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Option<"numWarps", "num-warps",
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"int32_t", /*default*/"4",
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"number of warps">
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];
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}
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#endif
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@@ -10,10 +10,16 @@ template <typename T> class OperationPass;
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namespace triton {
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std::unique_ptr<OperationPass<ModuleOp>>
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createConvertTritonToTritonGPUPass(int numWarps = 4);
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constexpr static char AttrNumWarpsName[] = "triton_gpu.num-warps";
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}
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// Create the pass with numWarps passed from cl::opt.
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std::unique_ptr<OperationPass<ModuleOp>> createConvertTritonToTritonGPUPass();
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// Create the pass with numWarps set explicitly.
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std::unique_ptr<OperationPass<ModuleOp>>
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createConvertTritonToTritonGPUPass(int numWarps);
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} // namespace triton
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} // namespace mlir
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#endif
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@@ -5,8 +5,10 @@
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#include "mlir/Dialect/Arithmetic/IR/Arithmetic.h"
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#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "triton/Conversion/TritonToTritonGPU/TritonToTritonGPU.h"
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#include "triton/Dialect/Triton/IR/Dialect.h"
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#include "triton/Dialect/TritonGPU/IR/Dialect.h"
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#include <numeric>
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using namespace mlir;
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using namespace mlir::triton;
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@@ -163,7 +165,7 @@ struct FuncOpConversion : public FuncOpConversionBase {
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}
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private:
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int NumWarps{-1};
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int NumWarps{0};
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};
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struct ReturnOpConversion : public ConvertOpToLLVMPattern<::mlir::ReturnOp> {
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@@ -188,6 +190,24 @@ struct ReturnOpConversion : public ConvertOpToLLVMPattern<::mlir::ReturnOp> {
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}
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};
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// Extract numWarps information from TritonGPU module, return 0 if failed.
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// This is a naive implementation, it assumes that all the blocked layout should
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// have the same numWarps setting in a module, it just find a blocked layout
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// encoding and return the warpsPerCTA field.
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int extractNumWarps(mlir::ModuleOp module) {
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int numWarps{};
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if (module->hasAttr(AttrNumWarpsName))
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numWarps = module->getAttr(AttrNumWarpsName)
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.dyn_cast<IntegerAttr>()
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.getValue()
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.getZExtValue();
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else
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llvm::report_fatal_error(
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"TritonGPU module should contain a triton_gpu.num-warps attribute");
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return numWarps;
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}
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} // namespace
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void populateTritonToLLVMPatterns(mlir::LLVMTypeConverter &typeConverter,
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@@ -200,8 +220,6 @@ class ConvertTritonGPUToLLVM
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: public ConvertTritonGPUToLLVMBase<ConvertTritonGPUToLLVM> {
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public:
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ConvertTritonGPUToLLVM() = default;
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// For manually overwrite the numWarps option
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explicit ConvertTritonGPUToLLVM(int numWarps) { this->numWarps = numWarps; }
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void runOnOperation() override {
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MLIRContext *context = &getContext();
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@@ -215,6 +233,8 @@ public:
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mlir::arith::populateArithmeticToLLVMConversionPatterns(typeConverter,
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patterns);
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int numWarps = extractNumWarps(mod);
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populateTritonToLLVMPatterns(typeConverter, patterns, numWarps);
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if (failed(applyPartialConversion(mod, target, std::move(patterns))))
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@@ -5,6 +5,7 @@
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#include "triton/Dialect/Triton/IR/Dialect.h"
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#include "triton/Dialect/TritonGPU/IR/Dialect.h"
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#include "triton/Dialect/TritonGPU/Transforms/TritonGPUConversion.h"
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#include "llvm/ADT/APSInt.h"
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#include <numeric>
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using namespace mlir;
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@@ -375,6 +376,8 @@ void populateSCFPatterns(TritonGPUTypeConverter &typeConverter,
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class ConvertTritonToTritonGPU
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: public ConvertTritonToTritonGPUBase<ConvertTritonToTritonGPU> {
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public:
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ConvertTritonToTritonGPU() = default;
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// constructor with some parameters set explicitly.
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ConvertTritonToTritonGPU(int numWarps) { this->numWarps = numWarps; }
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void runOnOperation() override {
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@@ -395,6 +398,13 @@ public:
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if (failed(applyPartialConversion(mod, target, std::move(patterns))))
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return signalPassFailure();
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auto inti = llvm::APSInt(32, false);
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auto i32_ty = IntegerType::get(mod->getContext(), 32);
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mod->setAttr(
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AttrNumWarpsName,
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IntegerAttr::get(i32_ty, llvm::APInt(32, numWarps.getValue())));
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// update layouts
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// broadcast src => multicast, dst => broadcasted
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// if (failed(target.refineLayouts(mod, numWarps)))
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@@ -408,3 +418,8 @@ std::unique_ptr<OperationPass<ModuleOp>>
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mlir::triton::createConvertTritonToTritonGPUPass(int numWarps) {
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return std::make_unique<::ConvertTritonToTritonGPU>(numWarps);
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}
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std::unique_ptr<OperationPass<ModuleOp>>
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mlir::triton::createConvertTritonToTritonGPUPass() {
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return std::make_unique<::ConvertTritonToTritonGPU>();
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}
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@@ -1,6 +1,7 @@
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// RUN: triton-opt %s -convert-triton-to-tritongpu
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// RUN: triton-opt %s -convert-triton-to-tritongpu=num-warps=2 | FileCheck %s
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func @ops() {
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// CHECK: module attributes {"triton_gpu.num-warps" = 2 : i32} {{.*}}
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%a = arith.constant dense<1.00e+00> : tensor<128x32xf16>
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%b = arith.constant dense<2.00e+00> : tensor<32x128xf16>
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%c = arith.constant dense<3.00e+00> : tensor<128x128xf32>
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@@ -1,9 +1,15 @@
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// RUN: triton-opt %s -split-input-file --convert-triton-gpu-to-llvm=num-warps=8
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// RUN: triton-opt %s -split-input-file --convert-triton-gpu-to-llvm | FileCheck %s
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module attributes {"triton_gpu.num-warps" = 4 : i32} {
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// CHECK: llvm.func @test_empty_kernel(%arg0: i64, %arg1: !llvm.ptr<f16, 1>)
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// CHECK: attributes {nvvm.maxntidx = 96 : i32}
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// Here the 128 comes from the 4 in module attribute multiples 32
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// CHECK: attributes {nvvm.maxntid = 128 : i32} {{.*}}
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func @test_empty_kernel(%lb : index, %A : !tt.ptr<f16>) {
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// CHECK: llvm.return
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return
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}
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} // end module
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@@ -6,8 +6,11 @@
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// CHECK: !nvvm.annotations
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// CHECK: !{void (i64, half addrspace(1)*)* @test_empty_kernel, !"maxntidx", i32 128}
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module attributes {"triton_gpu.num-warps" = 4 : i32} {
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func @test_empty_kernel(%lb : index, %A : !tt.ptr<f16>) {
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return
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}
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}
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@@ -5,7 +5,11 @@
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// CHECK: .target sm_80
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// CHECK: .address_size 64
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module attributes {"triton_gpu.num-warps" = 4 : i32} {
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func @test_empty_kernel(%lb : index, %A : !tt.ptr<f16>) {
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return
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}
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}
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