[MLIR][NFC] Retire let constructor for GPU (#129849)

`let constructor` is legacy (do not use in tree!) since the table gen
backend emits most of the glue logic to build a pass.
This commit is contained in:
lorenzo chelini 2025-03-06 04:48:24 -06:00 committed by GitHub
parent 5ce4045384
commit 556a64507b
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6 changed files with 18 additions and 70 deletions

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@ -35,25 +35,6 @@ class FuncOp;
#define GEN_PASS_DECL
#include "mlir/Dialect/GPU/Transforms/Passes.h.inc"
/// Pass that moves ops which are likely an index computation into gpu.launch
/// body.
std::unique_ptr<Pass> createGpuLauchSinkIndexComputationsPass();
/// Replaces `gpu.launch` with `gpu.launch_func` by moving the region into
/// a separate kernel function.
std::unique_ptr<OperationPass<ModuleOp>>
createGpuKernelOutliningPass(StringRef dataLayoutStr = StringRef());
/// Rewrites a function region so that GPU ops execute asynchronously.
std::unique_ptr<OperationPass<func::FuncOp>> createGpuAsyncRegionPass();
/// Maps the parallel loops found in the given function to workgroups. The first
/// loop encountered will be mapped to the global workgroup and the second loop
/// encountered to the local workgroup. Within each mapping, the first three
/// dimensions are mapped to x/y/z hardware ids and all following dimensions are
/// mapped to sequential loops.
std::unique_ptr<OperationPass<func::FuncOp>> createGpuMapParallelLoopsPass();
/// Collect a set of patterns to rewrite GlobalIdOp op within the GPU dialect.
void populateGpuGlobalIdPatterns(RewritePatternSet &patterns);
@ -110,9 +91,6 @@ LogicalResult transformGpuModulesToBinaries(
/// Collect a set of patterns to decompose memrefs ops.
void populateGpuDecomposeMemrefsPatterns(RewritePatternSet &patterns);
/// Pass decomposes memref ops inside `gpu.launch` body.
std::unique_ptr<Pass> createGpuDecomposeMemrefsPass();
/// Erase barriers that do not enforce conflicting memory side effects.
void populateGpuEliminateBarriersPatterns(RewritePatternSet &patterns);

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@ -11,29 +11,35 @@
include "mlir/Pass/PassBase.td"
def GpuLaunchSinkIndexComputations : Pass<"gpu-launch-sink-index-computations"> {
def GpuLaunchSinkIndexComputationsPass
: Pass<"gpu-launch-sink-index-computations"> {
let summary = "Sink index computations into gpu.launch body";
let constructor = "mlir::createGpuLauchSinkIndexComputationsPass()";
let dependentDialects = ["mlir::gpu::GPUDialect"];
}
def GpuKernelOutlining : Pass<"gpu-kernel-outlining", "ModuleOp"> {
def GpuKernelOutliningPass : Pass<"gpu-kernel-outlining", "ModuleOp"> {
let summary = "Outline gpu.launch bodies to kernel functions";
let constructor = "mlir::createGpuKernelOutliningPass()";
let dependentDialects = ["mlir::DLTIDialect", "cf::ControlFlowDialect"];
let options = [Option<"dataLayoutStr", "data-layout-str", "std::string",
/*default=*/"",
"String description of the data layout">];
}
def GpuAsyncRegionPass : Pass<"gpu-async-region", "func::FuncOp"> {
let summary = "Make GPU ops async";
let constructor = "mlir::createGpuAsyncRegionPass()";
let dependentDialects = ["async::AsyncDialect"];
}
def GpuMapParallelLoopsPass
: Pass<"gpu-map-parallel-loops", "mlir::func::FuncOp"> {
let summary = "Greedily maps loops to GPU hardware dimensions.";
let constructor = "mlir::createGpuMapParallelLoopsPass()";
let description = "Greedily maps loops to GPU hardware dimensions.";
let description = [{
Maps the parallel loops found in the given function to workgroups. The first
loop encountered will be mapped to the global workgroup and the second loop
encountered to the local workgroup. Within each mapping, the first three
dimensions are mapped to x/y/z hardware ids and all following dimensions are
mapped to sequential loops.
}];
let dependentDialects = ["mlir::gpu::GPUDialect"];
}
@ -66,7 +72,6 @@ def GpuDecomposeMemrefsPass : Pass<"gpu-decompose-memrefs"> {
and sizes/strides for dynamically-sized memrefs are not available inside
`gpu.launch`.
}];
let constructor = "mlir::createGpuDecomposeMemrefsPass()";
let dependentDialects = [
"mlir::gpu::GPUDialect", "mlir::memref::MemRefDialect",
"mlir::affine::AffineDialect"

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@ -347,7 +347,3 @@ void GpuAsyncRegionPass::runOnOperation() {
// Makes each !gpu.async.token returned from async.execute op have single use.
getOperation().getRegion().walk(SingleTokenUseCallback());
}
std::unique_ptr<OperationPass<func::FuncOp>> mlir::createGpuAsyncRegionPass() {
return std::make_unique<GpuAsyncRegionPass>();
}

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@ -238,7 +238,3 @@ void mlir::populateGpuDecomposeMemrefsPatterns(RewritePatternSet &patterns) {
patterns.insert<FlattenLoad, FlattenStore, FlattenSubview>(
patterns.getContext());
}
std::unique_ptr<Pass> mlir::createGpuDecomposeMemrefsPass() {
return std::make_unique<GpuDecomposeMemrefsPass>();
}

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@ -30,8 +30,8 @@
#include <limits>
namespace mlir {
#define GEN_PASS_DEF_GPULAUNCHSINKINDEXCOMPUTATIONS
#define GEN_PASS_DEF_GPUKERNELOUTLINING
#define GEN_PASS_DEF_GPULAUNCHSINKINDEXCOMPUTATIONSPASS
#define GEN_PASS_DEF_GPUKERNELOUTLININGPASS
#include "mlir/Dialect/GPU/Transforms/Passes.h.inc"
} // namespace mlir
@ -302,7 +302,7 @@ namespace {
/// Pass that moves ops which are likely an index computation into gpu.launch
/// body.
class GpuLaunchSinkIndexComputationsPass
: public impl::GpuLaunchSinkIndexComputationsBase<
: public impl::GpuLaunchSinkIndexComputationsPassBase<
GpuLaunchSinkIndexComputationsPass> {
public:
void runOnOperation() override {
@ -329,17 +329,9 @@ public:
/// a separate pass. The external functions can then be annotated with the
/// symbol of the cubin accessor function.
class GpuKernelOutliningPass
: public impl::GpuKernelOutliningBase<GpuKernelOutliningPass> {
: public impl::GpuKernelOutliningPassBase<GpuKernelOutliningPass> {
public:
GpuKernelOutliningPass(StringRef dlStr) {
if (!dlStr.empty() && !dataLayoutStr.hasValue())
dataLayoutStr = dlStr.str();
}
GpuKernelOutliningPass(const GpuKernelOutliningPass &other)
: GpuKernelOutliningBase(other), dataLayoutSpec(other.dataLayoutSpec) {
dataLayoutStr = other.dataLayoutStr.getValue();
}
using Base::Base;
LogicalResult initialize(MLIRContext *context) override {
// Initialize the data layout specification from the data layout string.
@ -457,21 +449,7 @@ private:
return kernelModule;
}
Option<std::string> dataLayoutStr{
*this, "data-layout-str",
llvm::cl::desc("String containing the data layout specification to be "
"attached to the GPU kernel module")};
DataLayoutSpecInterface dataLayoutSpec;
};
} // namespace
std::unique_ptr<Pass> mlir::createGpuLauchSinkIndexComputationsPass() {
return std::make_unique<GpuLaunchSinkIndexComputationsPass>();
}
std::unique_ptr<OperationPass<ModuleOp>>
mlir::createGpuKernelOutliningPass(StringRef dataLayoutStr) {
return std::make_unique<GpuKernelOutliningPass>(dataLayoutStr);
}

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@ -146,8 +146,3 @@ struct GpuMapParallelLoopsPass
} // namespace
} // namespace gpu
} // namespace mlir
std::unique_ptr<mlir::OperationPass<mlir::func::FuncOp>>
mlir::createGpuMapParallelLoopsPass() {
return std::make_unique<gpu::GpuMapParallelLoopsPass>();
}