diff options
Diffstat (limited to 'mlir')
66 files changed, 2674 insertions, 216 deletions
diff --git a/mlir/include/mlir/Analysis/DataFlow/StridedMetadataRangeAnalysis.h b/mlir/include/mlir/Analysis/DataFlow/StridedMetadataRangeAnalysis.h new file mode 100644 index 0000000..72ac247 --- /dev/null +++ b/mlir/include/mlir/Analysis/DataFlow/StridedMetadataRangeAnalysis.h @@ -0,0 +1,54 @@ +//===- StridedMetadataRange.h - Strided metadata range analysis -*- C++ -*-===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// + +#ifndef MLIR_ANALYSIS_DATAFLOW_STRIDEDMETADATARANGE_H +#define MLIR_ANALYSIS_DATAFLOW_STRIDEDMETADATARANGE_H + +#include "mlir/Analysis/DataFlow/SparseAnalysis.h" +#include "mlir/Interfaces/InferStridedMetadataInterface.h" + +namespace mlir { +namespace dataflow { + +/// This lattice element represents the strided metadata of an SSA value. +class StridedMetadataRangeLattice : public Lattice<StridedMetadataRange> { +public: + using Lattice::Lattice; +}; + +/// Strided metadata range analysis determines the strided metadata ranges of +/// SSA values using operations that define `InferStridedMetadataInterface`. +/// +/// This analysis depends on DeadCodeAnalysis, SparseConstantPropagation, and +/// IntegerRangeAnalysis, and will be a silent no-op if the analyses are not +/// loaded in the same solver context. +class StridedMetadataRangeAnalysis + : public SparseForwardDataFlowAnalysis<StridedMetadataRangeLattice> { +public: + StridedMetadataRangeAnalysis(DataFlowSolver &solver, + int32_t indexBitwidth = 64); + + /// At an entry point, we cannot reason about strided metadata ranges unless + /// the type also encodes the data. For example, a memref with static layout. + void setToEntryState(StridedMetadataRangeLattice *lattice) override; + + /// Visit an operation. Invoke the transfer function on each operation that + /// implements `InferStridedMetadataInterface`. + LogicalResult + visitOperation(Operation *op, + ArrayRef<const StridedMetadataRangeLattice *> operands, + ArrayRef<StridedMetadataRangeLattice *> results) override; + +private: + /// Index bitwidth to use when operating with the int-ranges. + int32_t indexBitwidth = 64; +}; +} // namespace dataflow +} // end namespace mlir + +#endif // MLIR_ANALYSIS_DATAFLOW_STRIDEDMETADATARANGE_H diff --git a/mlir/include/mlir/Conversion/MathToXeVM/MathToXeVM.h b/mlir/include/mlir/Conversion/MathToXeVM/MathToXeVM.h new file mode 100644 index 0000000..91d3c92 --- /dev/null +++ b/mlir/include/mlir/Conversion/MathToXeVM/MathToXeVM.h @@ -0,0 +1,27 @@ +//===- MathToXeVM.h - Utils for converting Math to XeVM -------------------===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// +#ifndef MLIR_CONVERSION_MATHTOXEVM_MATHTOXEVM_H_ +#define MLIR_CONVERSION_MATHTOXEVM_MATHTOXEVM_H_ + +#include "mlir/Conversion/LLVMCommon/TypeConverter.h" +#include "mlir/Dialect/LLVMIR/XeVMDialect.h" +#include "mlir/IR/PatternMatch.h" +#include <memory> + +namespace mlir { +class Pass; + +#define GEN_PASS_DECL_CONVERTMATHTOXEVM +#include "mlir/Conversion/Passes.h.inc" + +/// Populate the given list with patterns that convert from Math to XeVM calls. +void populateMathToXeVMConversionPatterns(RewritePatternSet &patterns, + bool convertArith); +} // namespace mlir + +#endif // MLIR_CONVERSION_MATHTOXEVM_MATHTOXEVM_H_ diff --git a/mlir/include/mlir/Conversion/Passes.h b/mlir/include/mlir/Conversion/Passes.h index da061b2..40d866e 100644 --- a/mlir/include/mlir/Conversion/Passes.h +++ b/mlir/include/mlir/Conversion/Passes.h @@ -49,6 +49,7 @@ #include "mlir/Conversion/MathToLibm/MathToLibm.h" #include "mlir/Conversion/MathToROCDL/MathToROCDL.h" #include "mlir/Conversion/MathToSPIRV/MathToSPIRVPass.h" +#include "mlir/Conversion/MathToXeVM/MathToXeVM.h" #include "mlir/Conversion/MemRefToEmitC/MemRefToEmitCPass.h" #include "mlir/Conversion/MemRefToLLVM/MemRefToLLVM.h" #include "mlir/Conversion/MemRefToSPIRV/MemRefToSPIRVPass.h" diff --git a/mlir/include/mlir/Conversion/Passes.td b/mlir/include/mlir/Conversion/Passes.td index 3c18ecc..25e9d34 100644 --- a/mlir/include/mlir/Conversion/Passes.td +++ b/mlir/include/mlir/Conversion/Passes.td @@ -797,6 +797,31 @@ def ConvertMathToSPIRVPass : Pass<"convert-math-to-spirv"> { } //===----------------------------------------------------------------------===// +// MathToXeVM +//===----------------------------------------------------------------------===// + +def ConvertMathToXeVM : Pass<"convert-math-to-xevm", "ModuleOp"> { + let summary = + "Convert (fast) math operations to native XeVM/SPIRV equivalents"; + let description = [{ + This pass converts supported math ops marked with the `afn` fastmath flag + to function calls for OpenCL `native_` math intrinsics: These intrinsics + are typically mapped directly to native device instructions, often resulting + in better performance. However, the precision/error of these intrinsics + are implementation-defined, and thus math ops are only converted when they + have the `afn` fastmath flag enabled. + }]; + let options = [Option< + "convertArith", "convert-arith", "bool", /*default=*/"true", + "Convert supported Arith ops (e.g. arith.divf) as well.">]; + let dependentDialects = [ + "arith::ArithDialect", + "xevm::XeVMDialect", + "LLVM::LLVMDialect", + ]; +} + +//===----------------------------------------------------------------------===// // MathToEmitC //===----------------------------------------------------------------------===// diff --git a/mlir/include/mlir/Dialect/LLVMIR/NVVMOps.td b/mlir/include/mlir/Dialect/LLVMIR/NVVMOps.td index 89fbeb7..ce9ff7e 100644 --- a/mlir/include/mlir/Dialect/LLVMIR/NVVMOps.td +++ b/mlir/include/mlir/Dialect/LLVMIR/NVVMOps.td @@ -1655,6 +1655,40 @@ def NVVM_ConvertFloatToTF32Op : NVVM_Op<"convert.float.to.tf32"> { }]; } +def NVVM_ConvertF32x2ToF4x2Op : NVVM_Op<"convert.f32x2.to.f4x2"> { + let summary = "Convert a pair of float inputs to f4x2"; + let description = [{ + This Op converts each of the given float inputs to the specified fp4 type. + The result `dst` is returned as an i8 type where the converted values are + packed such that the value converted from `a` is stored in the upper 4 bits + of `dst` and the value converted from `b` is stored in the lower 4 bits of + `dst`. + The `relu` attribute, when set, lowers to the '.relu' variant of + the cvt instruction. + + [For more information, see PTX ISA](https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#data-movement-and-conversion-instructions-cvt) + }]; + + let results = (outs I8:$dst); + let arguments = (ins F32:$a, F32:$b, + DefaultValuedAttr<BoolAttr, "false">:$relu, + TypeAttr:$dstTy); + let assemblyFormat = "$a `,` $b attr-dict `:` type($dst) `(` $dstTy `)`"; + let hasVerifier = 1; + + let extraClassDeclaration = [{ + static mlir::NVVM::IDArgPair + getIntrinsicIDAndArgs(NVVM::ConvertF32x2ToF4x2Op op, + LLVM::ModuleTranslation &mt, llvm::IRBuilderBase &builder); + }]; + + string llvmBuilder = [{ + auto [intId, args] = NVVM::ConvertF32x2ToF4x2Op::getIntrinsicIDAndArgs(op, moduleTranslation, builder); + llvm::Value *packedI16 = createIntrinsicCall(builder, intId, args); + $dst = builder.CreateTruncOrBitCast(packedI16, llvm::Type::getInt8Ty(builder.getContext())); + }]; +} + def NVVM_ConvertF32x2ToF6x2Op : NVVM_Op<"convert.f32x2.to.f6x2"> { let summary = "Convert a pair of float inputs to f6x2"; let description = [{ diff --git a/mlir/include/mlir/Dialect/MemRef/IR/MemRef.h b/mlir/include/mlir/Dialect/MemRef/IR/MemRef.h index 30f33ed..69447f7 100644 --- a/mlir/include/mlir/Dialect/MemRef/IR/MemRef.h +++ b/mlir/include/mlir/Dialect/MemRef/IR/MemRef.h @@ -17,6 +17,7 @@ #include "mlir/Interfaces/CastInterfaces.h" #include "mlir/Interfaces/ControlFlowInterfaces.h" #include "mlir/Interfaces/InferIntRangeInterface.h" +#include "mlir/Interfaces/InferStridedMetadataInterface.h" #include "mlir/Interfaces/InferTypeOpInterface.h" #include "mlir/Interfaces/MemOpInterfaces.h" #include "mlir/Interfaces/MemorySlotInterfaces.h" diff --git a/mlir/include/mlir/Dialect/MemRef/IR/MemRefOps.td b/mlir/include/mlir/Dialect/MemRef/IR/MemRefOps.td index 89bd0f1..b39207f 100644 --- a/mlir/include/mlir/Dialect/MemRef/IR/MemRefOps.td +++ b/mlir/include/mlir/Dialect/MemRef/IR/MemRefOps.td @@ -14,6 +14,7 @@ include "mlir/Dialect/MemRef/IR/MemRefBase.td" include "mlir/Interfaces/CastInterfaces.td" include "mlir/Interfaces/ControlFlowInterfaces.td" include "mlir/Interfaces/InferIntRangeInterface.td" +include "mlir/Interfaces/InferStridedMetadataInterface.td" include "mlir/Interfaces/InferTypeOpInterface.td" include "mlir/Interfaces/MemOpInterfaces.td" include "mlir/Interfaces/MemorySlotInterfaces.td" @@ -2085,6 +2086,7 @@ def MemRef_StoreOp : MemRef_Op<"store", def SubViewOp : MemRef_OpWithOffsetSizesAndStrides<"subview", [ DeclareOpInterfaceMethods<OpAsmOpInterface, ["getAsmResultNames"]>, + DeclareOpInterfaceMethods<InferStridedMetadataOpInterface>, DeclareOpInterfaceMethods<MemorySpaceCastConsumerOpInterface>, DeclareOpInterfaceMethods<ViewLikeOpInterface>, AttrSizedOperandSegments, diff --git a/mlir/include/mlir/Dialect/OpenACC/OpenACCOps.td b/mlir/include/mlir/Dialect/OpenACC/OpenACCOps.td index 77e833f..fecf81b 100644 --- a/mlir/include/mlir/Dialect/OpenACC/OpenACCOps.td +++ b/mlir/include/mlir/Dialect/OpenACC/OpenACCOps.td @@ -1316,6 +1316,24 @@ def OpenACC_PrivateRecipeOp }]; let hasRegionVerifier = 1; + + let extraClassDeclaration = [{ + /// Creates a PrivateRecipeOp and populates its regions based on the + /// variable type as long as the type implements MappableType or + /// PointerLikeType interface. If a type implements both, the MappableType + /// API will be preferred. Returns std::nullopt if the recipe cannot be + /// created or populated. The builder's current insertion point will be used + /// and it must be a valid place for this operation to be inserted. The + /// `recipeName` must be a unique name to prevent "redefinition of symbol" + /// IR errors. + static std::optional<PrivateRecipeOp> createAndPopulate( + ::mlir::OpBuilder &builder, + ::mlir::Location loc, + ::llvm::StringRef recipeName, + ::mlir::Type varType, + ::llvm::StringRef varName = "", + ::mlir::ValueRange bounds = {}); + }]; } //===----------------------------------------------------------------------===// @@ -1410,6 +1428,24 @@ def OpenACC_FirstprivateRecipeOp }]; let hasRegionVerifier = 1; + + let extraClassDeclaration = [{ + /// Creates a FirstprivateRecipeOp and populates its regions based on the + /// variable type as long as the type implements MappableType or + /// PointerLikeType interface. If a type implements both, the MappableType + /// API will be preferred. Returns std::nullopt if the recipe cannot be + /// created or populated. The builder's current insertion point will be used + /// and it must be a valid place for this operation to be inserted. The + /// `recipeName` must be a unique name to prevent "redefinition of symbol" + /// IR errors. + static std::optional<FirstprivateRecipeOp> createAndPopulate( + ::mlir::OpBuilder &builder, + ::mlir::Location loc, + ::llvm::StringRef recipeName, + ::mlir::Type varType, + ::llvm::StringRef varName = "", + ::mlir::ValueRange bounds = {}); + }]; } //===----------------------------------------------------------------------===// diff --git a/mlir/include/mlir/Dialect/OpenACC/OpenACCTypeInterfaces.td b/mlir/include/mlir/Dialect/OpenACC/OpenACCTypeInterfaces.td index 0d16255..6736bc8 100644 --- a/mlir/include/mlir/Dialect/OpenACC/OpenACCTypeInterfaces.td +++ b/mlir/include/mlir/Dialect/OpenACC/OpenACCTypeInterfaces.td @@ -83,7 +83,15 @@ def OpenACC_PointerLikeTypeInterface : TypeInterface<"PointerLikeType"> { The `originalVar` parameter is optional but enables support for dynamic types (e.g., dynamic memrefs). When provided, implementations can extract runtime dimension information from the original variable to create - allocations with matching dynamic sizes. + allocations with matching dynamic sizes. When generating recipe bodies, + `originalVar` should be the block argument representing the original + variable in the recipe region. + + The `needsFree` output parameter indicates whether the allocated memory + requires explicit deallocation. Implementations should set this to true + for heap allocations that need a matching deallocation operation (e.g., + alloc) and false for stack-based allocations (e.g., alloca). During + recipe generation, this determines whether a destroy region is created. Returns a Value representing the result of the allocation. If no value is returned, it means the allocation was not successfully generated. @@ -94,7 +102,8 @@ def OpenACC_PointerLikeTypeInterface : TypeInterface<"PointerLikeType"> { "::mlir::Location":$loc, "::llvm::StringRef":$varName, "::mlir::Type":$varType, - "::mlir::Value":$originalVar), + "::mlir::Value":$originalVar, + "bool &":$needsFree), /*methodBody=*/"", /*defaultImplementation=*/[{ return {}; @@ -102,23 +111,34 @@ def OpenACC_PointerLikeTypeInterface : TypeInterface<"PointerLikeType"> { >, InterfaceMethod< /*description=*/[{ - Generates deallocation operations for the pointer-like type. It deallocates - the instance provided. + Generates deallocation operations for the pointer-like type. - The `varPtr` parameter is required and must represent an instance that was - previously allocated. If the current type is represented in a way that it - does not capture the pointee type, `varType` must be passed in to provide - the necessary type information. Nothing is generated in case the allocate - is `alloca`-like. + The `varToFree` parameter is required and must represent an instance + that was previously allocated. When generating recipe bodies, this + should be the block argument representing the private variable in the + destroy region. + + The `allocRes` parameter is optional and provides the result of the + corresponding allocation from the init region. This allows implementations + to inspect the allocation operation to determine the appropriate + deallocation strategy. This is necessary because in recipe generation, + the allocation and deallocation occur in separate regions. Dialects that + use only one allocation type or can determine deallocation from type + information alone may ignore this parameter. - Returns true if deallocation was successfully generated or successfully - deemed as not needed to be generated, false otherwise. + The `varType` parameter must be provided if the current type does not + capture the pointee type information. No deallocation is generated for + stack-based allocations (e.g., alloca). + + Returns true if deallocation was successfully generated or determined to + be unnecessary, false otherwise. }], /*retTy=*/"bool", /*methodName=*/"genFree", /*args=*/(ins "::mlir::OpBuilder &":$builder, "::mlir::Location":$loc, - "::mlir::TypedValue<::mlir::acc::PointerLikeType>":$varPtr, + "::mlir::TypedValue<::mlir::acc::PointerLikeType>":$varToFree, + "::mlir::Value":$allocRes, "::mlir::Type":$varType), /*methodBody=*/"", /*defaultImplementation=*/[{ @@ -274,6 +294,14 @@ def OpenACC_MappableTypeInterface : TypeInterface<"MappableType"> { The `initVal` can be empty - it is primarily needed for reductions to ensure the variable is also initialized with appropriate value. + The `needsDestroy` out-parameter is set by implementations to indicate + that destruction code must be generated after the returned private + variable usages, typically in the destroy region of recipe operations + (for example, when heap allocations or temporaries requiring cleanup + are created during initialization). When `needsDestroy` is set, callers + should invoke `generatePrivateDestroy` in the recipe's destroy region + with the privatized value returned by this method. + If the return value is empty, it means that recipe body was not successfully generated. }], @@ -284,12 +312,38 @@ def OpenACC_MappableTypeInterface : TypeInterface<"MappableType"> { "::mlir::TypedValue<::mlir::acc::MappableType>":$var, "::llvm::StringRef":$varName, "::mlir::ValueRange":$extents, - "::mlir::Value":$initVal), + "::mlir::Value":$initVal, + "bool &":$needsDestroy), /*methodBody=*/"", /*defaultImplementation=*/[{ return {}; }] >, + InterfaceMethod< + /*description=*/[{ + Generates destruction operations for a privatized value previously + produced by `generatePrivateInit`. This is typically inserted in a + recipe's destroy region, after all uses of the privatized value. + + The `privatized` value is the SSA value yielded by the init region + (and passed as the privatized argument to the destroy region). + Implementations should free heap-allocated storage or perform any + cleanup required for the given type. If no destruction is required, + this function should be a no-op and return `true`. + + Returns true if destruction was successfully generated or deemed not + necessary, false otherwise. + }], + /*retTy=*/"bool", + /*methodName=*/"generatePrivateDestroy", + /*args=*/(ins "::mlir::OpBuilder &":$builder, + "::mlir::Location":$loc, + "::mlir::Value":$privatized), + /*methodBody=*/"", + /*defaultImplementation=*/[{ + return true; + }] + >, ]; } diff --git a/mlir/include/mlir/IR/Remarks.h b/mlir/include/mlir/IR/Remarks.h index 20e84ec..9877926 100644 --- a/mlir/include/mlir/IR/Remarks.h +++ b/mlir/include/mlir/IR/Remarks.h @@ -18,7 +18,6 @@ #include "llvm/Remarks/Remark.h" #include "llvm/Support/FormatVariadic.h" #include "llvm/Support/Regex.h" -#include <optional> #include "mlir/IR/Diagnostics.h" #include "mlir/IR/MLIRContext.h" @@ -144,7 +143,7 @@ public: llvm::StringRef getCategoryName() const { return categoryName; } - llvm::StringRef getFullCategoryName() const { + llvm::StringRef getCombinedCategoryName() const { if (categoryName.empty() && subCategoryName.empty()) return {}; if (subCategoryName.empty()) @@ -318,7 +317,7 @@ private: }; //===----------------------------------------------------------------------===// -// MLIR Remark Streamer +// Pluggable Remark Utilities //===----------------------------------------------------------------------===// /// Base class for MLIR remark streamers that is used to stream @@ -338,6 +337,26 @@ public: virtual void finalize() {} // optional }; +using ReportFn = llvm::unique_function<void(const Remark &)>; + +/// Base class for MLIR remark emitting policies that is used to emit +/// optimization remarks to the underlying remark streamer. The derived classes +/// should implement the `reportRemark` method to provide the actual emitting +/// implementation. +class RemarkEmittingPolicyBase { +protected: + ReportFn reportImpl; + +public: + RemarkEmittingPolicyBase() = default; + virtual ~RemarkEmittingPolicyBase() = default; + + void initialize(ReportFn fn) { reportImpl = std::move(fn); } + + virtual void reportRemark(const Remark &remark) = 0; + virtual void finalize() = 0; +}; + //===----------------------------------------------------------------------===// // Remark Engine (MLIR Context will own this class) //===----------------------------------------------------------------------===// @@ -355,6 +374,8 @@ private: std::optional<llvm::Regex> failedFilter; /// The MLIR remark streamer that will be used to emit the remarks. std::unique_ptr<MLIRRemarkStreamerBase> remarkStreamer; + /// The MLIR remark policy that will be used to emit the remarks. + std::unique_ptr<RemarkEmittingPolicyBase> remarkEmittingPolicy; /// When is enabled, engine also prints remarks as mlir::emitRemarks. bool printAsEmitRemarks = false; @@ -392,6 +413,8 @@ private: InFlightRemark emitIfEnabled(Location loc, RemarkOpts opts, bool (RemarkEngine::*isEnabled)(StringRef) const); + /// Report a remark. + void reportImpl(const Remark &remark); public: /// Default constructor is deleted, use the other constructor. @@ -407,8 +430,15 @@ public: ~RemarkEngine(); /// Setup the remark engine with the given output path and format. - LogicalResult initialize(std::unique_ptr<MLIRRemarkStreamerBase> streamer, - std::string *errMsg); + LogicalResult + initialize(std::unique_ptr<MLIRRemarkStreamerBase> streamer, + std::unique_ptr<RemarkEmittingPolicyBase> remarkEmittingPolicy, + std::string *errMsg); + + /// Get the remark emitting policy. + RemarkEmittingPolicyBase *getRemarkEmittingPolicy() const { + return remarkEmittingPolicy.get(); + } /// Report a remark. void report(const Remark &&remark); @@ -446,6 +476,46 @@ inline InFlightRemark withEngine(Fn fn, Location loc, Args &&...args) { namespace mlir::remark { +//===----------------------------------------------------------------------===// +// Remark Emitting Policies +//===----------------------------------------------------------------------===// + +/// Policy that emits all remarks. +class RemarkEmittingPolicyAll : public detail::RemarkEmittingPolicyBase { +public: + RemarkEmittingPolicyAll(); + + void reportRemark(const detail::Remark &remark) override { + assert(reportImpl && "reportImpl is not set"); + reportImpl(remark); + } + void finalize() override {} +}; + +/// Policy that emits final remarks. +class RemarkEmittingPolicyFinal : public detail::RemarkEmittingPolicyBase { +private: + /// user can intercept them for custom processing via a registered callback, + /// otherwise they will be reported on engine destruction. + llvm::DenseSet<detail::Remark> postponedRemarks; + +public: + RemarkEmittingPolicyFinal(); + + void reportRemark(const detail::Remark &remark) override { + postponedRemarks.erase(remark); + postponedRemarks.insert(remark); + } + + void finalize() override { + assert(reportImpl && "reportImpl is not set"); + for (auto &remark : postponedRemarks) { + if (reportImpl) + reportImpl(remark); + } + } +}; + /// Create a Reason with llvm::formatv formatting. template <class... Ts> inline detail::LazyTextBuild reason(const char *fmt, Ts &&...ts) { @@ -505,16 +575,72 @@ inline detail::InFlightRemark analysis(Location loc, RemarkOpts opts) { /// Setup remarks for the context. This function will enable the remark engine /// and set the streamer to be used for optimization remarks. The remark -/// categories are used to filter the remarks that will be emitted by the remark -/// engine. If a category is not specified, it will not be emitted. If +/// categories are used to filter the remarks that will be emitted by the +/// remark engine. If a category is not specified, it will not be emitted. If /// `printAsEmitRemarks` is true, the remarks will be printed as /// mlir::emitRemarks. 'streamer' must inherit from MLIRRemarkStreamerBase and /// will be used to stream the remarks. LogicalResult enableOptimizationRemarks( MLIRContext &ctx, std::unique_ptr<remark::detail::MLIRRemarkStreamerBase> streamer, + std::unique_ptr<remark::detail::RemarkEmittingPolicyBase> + remarkEmittingPolicy, const remark::RemarkCategories &cats, bool printAsEmitRemarks = false); } // namespace mlir::remark +// DenseMapInfo specialization for Remark +namespace llvm { +template <> +struct DenseMapInfo<mlir::remark::detail::Remark> { + static constexpr StringRef kEmptyKey = "<EMPTY_KEY>"; + static constexpr StringRef kTombstoneKey = "<TOMBSTONE_KEY>"; + + /// Helper to provide a static dummy context for sentinel keys. + static mlir::MLIRContext *getStaticDummyContext() { + static mlir::MLIRContext dummyContext; + return &dummyContext; + } + + /// Create an empty remark + static inline mlir::remark::detail::Remark getEmptyKey() { + return mlir::remark::detail::Remark( + mlir::remark::RemarkKind::RemarkUnknown, mlir::DiagnosticSeverity::Note, + mlir::UnknownLoc::get(getStaticDummyContext()), + mlir::remark::RemarkOpts::name(kEmptyKey)); + } + + /// Create a dead remark + static inline mlir::remark::detail::Remark getTombstoneKey() { + return mlir::remark::detail::Remark( + mlir::remark::RemarkKind::RemarkUnknown, mlir::DiagnosticSeverity::Note, + mlir::UnknownLoc::get(getStaticDummyContext()), + mlir::remark::RemarkOpts::name(kTombstoneKey)); + } + + /// Compute the hash value of the remark + static unsigned getHashValue(const mlir::remark::detail::Remark &remark) { + return llvm::hash_combine( + remark.getLocation().getAsOpaquePointer(), + llvm::hash_value(remark.getRemarkName()), + llvm::hash_value(remark.getCombinedCategoryName())); + } + + static bool isEqual(const mlir::remark::detail::Remark &lhs, + const mlir::remark::detail::Remark &rhs) { + // Check for empty/tombstone keys first + if (lhs.getRemarkName() == kEmptyKey || + lhs.getRemarkName() == kTombstoneKey || + rhs.getRemarkName() == kEmptyKey || + rhs.getRemarkName() == kTombstoneKey) { + return lhs.getRemarkName() == rhs.getRemarkName(); + } + + // For regular remarks, compare key identifying fields + return lhs.getLocation() == rhs.getLocation() && + lhs.getRemarkName() == rhs.getRemarkName() && + lhs.getCombinedCategoryName() == rhs.getCombinedCategoryName(); + } +}; +} // namespace llvm #endif // MLIR_IR_REMARKS_H diff --git a/mlir/include/mlir/Interfaces/CMakeLists.txt b/mlir/include/mlir/Interfaces/CMakeLists.txt index a5feb59..72ed046 100644 --- a/mlir/include/mlir/Interfaces/CMakeLists.txt +++ b/mlir/include/mlir/Interfaces/CMakeLists.txt @@ -6,6 +6,7 @@ add_mlir_interface(DestinationStyleOpInterface) add_mlir_interface(FunctionInterfaces) add_mlir_interface(IndexingMapOpInterface) add_mlir_interface(InferIntRangeInterface) +add_mlir_interface(InferStridedMetadataInterface) add_mlir_interface(InferTypeOpInterface) add_mlir_interface(LoopLikeInterface) add_mlir_interface(MemOpInterfaces) diff --git a/mlir/include/mlir/Interfaces/InferIntRangeInterface.h b/mlir/include/mlir/Interfaces/InferIntRangeInterface.h index 0e107e8..a6de3d1 100644 --- a/mlir/include/mlir/Interfaces/InferIntRangeInterface.h +++ b/mlir/include/mlir/Interfaces/InferIntRangeInterface.h @@ -117,7 +117,8 @@ public: IntegerValueRange(ConstantIntRanges value) : value(std::move(value)) {} /// Create an integer value range lattice value. - IntegerValueRange(std::optional<ConstantIntRanges> value = std::nullopt) + explicit IntegerValueRange( + std::optional<ConstantIntRanges> value = std::nullopt) : value(std::move(value)) {} /// Whether the range is uninitialized. This happens when the state hasn't @@ -167,6 +168,15 @@ using SetIntRangeFn = using SetIntLatticeFn = llvm::function_ref<void(Value, const IntegerValueRange &)>; +/// Helper callback type to get the integer range of a value. +using GetIntRangeFn = function_ref<IntegerValueRange(Value)>; + +/// Helper function to collect the integer range values of an array of op fold +/// results. +SmallVector<IntegerValueRange> getIntValueRanges(ArrayRef<OpFoldResult> values, + GetIntRangeFn getIntRange, + int32_t indexBitwidth); + class InferIntRangeInterface; namespace intrange::detail { diff --git a/mlir/include/mlir/Interfaces/InferStridedMetadataInterface.h b/mlir/include/mlir/Interfaces/InferStridedMetadataInterface.h new file mode 100644 index 0000000..0c572e0 --- /dev/null +++ b/mlir/include/mlir/Interfaces/InferStridedMetadataInterface.h @@ -0,0 +1,145 @@ +//===- InferStridedMetadataInterface.h - Strided Metadata Inference -C++-*-===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// +// +// This file contains definitions of the strided metadata inference interface +// defined in `InferStridedMetadataInterface.td` +// +//===----------------------------------------------------------------------===// + +#ifndef MLIR_INTERFACES_INFERSTRIDEDMETADATAINTERFACE_H +#define MLIR_INTERFACES_INFERSTRIDEDMETADATAINTERFACE_H + +#include "mlir/Interfaces/InferIntRangeInterface.h" + +namespace mlir { +/// A class that represents the strided metadata range information, including +/// offsets, sizes, and strides as integer ranges. +class StridedMetadataRange { +public: + /// Default constructor creates uninitialized ranges. + StridedMetadataRange() = default; + + /// Returns a ranked strided metadata range. + static StridedMetadataRange + getRanked(SmallVectorImpl<ConstantIntRanges> &&offsets, + SmallVectorImpl<ConstantIntRanges> &&sizes, + SmallVectorImpl<ConstantIntRanges> &&strides) { + return StridedMetadataRange(std::move(offsets), std::move(sizes), + std::move(strides)); + } + + /// Returns a strided metadata range with maximum ranges. + static StridedMetadataRange getMaxRanges(int32_t indexBitwidth, + int32_t offsetsRank, + int32_t sizeRank, + int32_t stridedRank) { + return StridedMetadataRange( + SmallVector<ConstantIntRanges>( + offsetsRank, ConstantIntRanges::maxRange(indexBitwidth)), + SmallVector<ConstantIntRanges>( + sizeRank, ConstantIntRanges::maxRange(indexBitwidth)), + SmallVector<ConstantIntRanges>( + stridedRank, ConstantIntRanges::maxRange(indexBitwidth))); + } + + static StridedMetadataRange getMaxRanges(int32_t indexBitwidth, + int32_t rank) { + return getMaxRanges(indexBitwidth, 1, rank, rank); + } + + /// Returns whether the metadata is uninitialized. + bool isUninitialized() const { return !offsets.has_value(); } + + /// Get the offsets range. + ArrayRef<ConstantIntRanges> getOffsets() const { + return offsets ? *offsets : ArrayRef<ConstantIntRanges>(); + } + MutableArrayRef<ConstantIntRanges> getOffsets() { + return offsets ? *offsets : MutableArrayRef<ConstantIntRanges>(); + } + + /// Get the sizes ranges. + ArrayRef<ConstantIntRanges> getSizes() const { return sizes; } + MutableArrayRef<ConstantIntRanges> getSizes() { return sizes; } + + /// Get the strides ranges. + ArrayRef<ConstantIntRanges> getStrides() const { return strides; } + MutableArrayRef<ConstantIntRanges> getStrides() { return strides; } + + /// Compare two strided metadata ranges. + bool operator==(const StridedMetadataRange &other) const { + return offsets == other.offsets && sizes == other.sizes && + strides == other.strides; + } + + /// Print the strided metadata range. + void print(raw_ostream &os) const; + + /// Join two strided metadata ranges, by taking the element-wise union of the + /// metadata. + static StridedMetadataRange join(const StridedMetadataRange &lhs, + const StridedMetadataRange &rhs) { + if (lhs.isUninitialized()) + return rhs; + if (rhs.isUninitialized()) + return lhs; + + // Helper fuction to compute the range union of constant ranges. + auto rangeUnion = + +[](const std::tuple<ConstantIntRanges, ConstantIntRanges> &lhsRhs) + -> ConstantIntRanges { + return std::get<0>(lhsRhs).rangeUnion(std::get<1>(lhsRhs)); + }; + + // Get the elementwise range union. Note, that `zip_equal` will assert if + // sizes are not equal. + SmallVector<ConstantIntRanges> offsets = llvm::map_to_vector( + llvm::zip_equal(*lhs.offsets, *rhs.offsets), rangeUnion); + SmallVector<ConstantIntRanges> sizes = + llvm::map_to_vector(llvm::zip_equal(lhs.sizes, rhs.sizes), rangeUnion); + SmallVector<ConstantIntRanges> strides = llvm::map_to_vector( + llvm::zip_equal(lhs.strides, rhs.strides), rangeUnion); + + // Return the joined metadata. + return StridedMetadataRange(std::move(offsets), std::move(sizes), + std::move(strides)); + } + +private: + /// Create a strided metadata range with the given offset, sizes, and strides. + StridedMetadataRange(SmallVectorImpl<ConstantIntRanges> &&offsets, + SmallVectorImpl<ConstantIntRanges> &&sizes, + SmallVectorImpl<ConstantIntRanges> &&strides) + : offsets(std::move(offsets)), sizes(std::move(sizes)), + strides(std::move(strides)) {} + + /// The offsets range. + std::optional<SmallVector<ConstantIntRanges>> offsets; + + /// The sizes ranges. + SmallVector<ConstantIntRanges> sizes; + + /// The strides ranges. + SmallVector<ConstantIntRanges> strides; +}; + +/// Print the strided metadata to `os`. +inline raw_ostream &operator<<(raw_ostream &os, + const StridedMetadataRange &range) { + range.print(os); + return os; +} + +/// Callback function type for setting the strided metadata of a value. +using SetStridedMetadataRangeFn = + function_ref<void(Value, const StridedMetadataRange &)>; +} // end namespace mlir + +#include "mlir/Interfaces/InferStridedMetadataInterface.h.inc" + +#endif // MLIR_INTERFACES_INFERSTRIDEDMETADATAINTERFACE_H diff --git a/mlir/include/mlir/Interfaces/InferStridedMetadataInterface.td b/mlir/include/mlir/Interfaces/InferStridedMetadataInterface.td new file mode 100644 index 0000000..ee5b094 --- /dev/null +++ b/mlir/include/mlir/Interfaces/InferStridedMetadataInterface.td @@ -0,0 +1,45 @@ +//===- InferStridedMetadataInterface.td - Strided MD Inference ----------*-===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// +// +// Defines the interface for strided metadata range analysis +// +//===----------------------------------------------------------------------===// + +#ifndef MLIR_INTERFACES_INFERSTRIDEDMETADATAINTERFACE +#define MLIR_INTERFACES_INFERSTRIDEDMETADATAINTERFACE + +include "mlir/IR/OpBase.td" + +def InferStridedMetadataOpInterface : + OpInterface<"InferStridedMetadataOpInterface"> { + let description = [{ + Allows operations to participate in strided metadata analysis by providing + methods that allow them to specify bounds on offsets, sizes, and strides + of their result(s) given bounds on their input(s) if known. + }]; + let cppNamespace = "::mlir"; + + let methods = [ + InterfaceMethod<[{ + Infer the strided metadata bounds on the results of this op given + the bounds on its operands. + For each result value or block argument of interest, the method should + call `setMetadata` with that `Value` as an argument. + The `operands` parameter contains the strided metadata ranges for all the + operands of the operation in order. + The `getIntRange` callback is provided for obtaining the int-range + analysis result for a given value. + }], + "void", "inferStridedMetadataRanges", + (ins "::llvm::ArrayRef<::mlir::StridedMetadataRange>":$operands, + "::mlir::GetIntRangeFn":$getIntRange, + "::mlir::SetStridedMetadataRangeFn":$setMetadata, + "int32_t":$indexBitwidth)> + ]; +} +#endif // MLIR_INTERFACES_INFERSTRIDEDMETADATAINTERFACE diff --git a/mlir/include/mlir/Remark/RemarkStreamer.h b/mlir/include/mlir/Remark/RemarkStreamer.h index 170d6b4..19a70fa 100644 --- a/mlir/include/mlir/Remark/RemarkStreamer.h +++ b/mlir/include/mlir/Remark/RemarkStreamer.h @@ -45,6 +45,7 @@ namespace mlir::remark { /// mlir::emitRemarks. LogicalResult enableOptimizationRemarksWithLLVMStreamer( MLIRContext &ctx, StringRef filePath, llvm::remarks::Format fmt, + std::unique_ptr<detail::RemarkEmittingPolicyBase> remarkEmittingPolicy, const RemarkCategories &cat, bool printAsEmitRemarks = false); } // namespace mlir::remark diff --git a/mlir/include/mlir/Tools/mlir-opt/MlirOptMain.h b/mlir/include/mlir/Tools/mlir-opt/MlirOptMain.h index 0fbe15f..b739438 100644 --- a/mlir/include/mlir/Tools/mlir-opt/MlirOptMain.h +++ b/mlir/include/mlir/Tools/mlir-opt/MlirOptMain.h @@ -44,6 +44,11 @@ enum class RemarkFormat { REMARK_FORMAT_BITSTREAM, }; +enum class RemarkPolicy { + REMARK_POLICY_ALL, + REMARK_POLICY_FINAL, +}; + /// Configuration options for the mlir-opt tool. /// This is intended to help building tools like mlir-opt by collecting the /// supported options. @@ -242,6 +247,8 @@ public: /// Set the reproducer output filename RemarkFormat getRemarkFormat() const { return remarkFormatFlag; } + /// Set the remark policy to use. + RemarkPolicy getRemarkPolicy() const { return remarkPolicyFlag; } /// Set the remark format to use. std::string getRemarksAllFilter() const { return remarksAllFilterFlag; } /// Set the remark output file. @@ -265,6 +272,8 @@ protected: /// Remark format RemarkFormat remarkFormatFlag = RemarkFormat::REMARK_FORMAT_STDOUT; + /// Remark policy + RemarkPolicy remarkPolicyFlag = RemarkPolicy::REMARK_POLICY_ALL; /// Remark file to output to std::string remarksOutputFileFlag = ""; /// Remark filters diff --git a/mlir/lib/Analysis/CMakeLists.txt b/mlir/lib/Analysis/CMakeLists.txt index 609cb34..db10ebc 100644 --- a/mlir/lib/Analysis/CMakeLists.txt +++ b/mlir/lib/Analysis/CMakeLists.txt @@ -40,6 +40,7 @@ add_mlir_library(MLIRAnalysis DataFlow/IntegerRangeAnalysis.cpp DataFlow/LivenessAnalysis.cpp DataFlow/SparseAnalysis.cpp + DataFlow/StridedMetadataRangeAnalysis.cpp ADDITIONAL_HEADER_DIRS ${MLIR_MAIN_INCLUDE_DIR}/mlir/Analysis @@ -53,6 +54,7 @@ add_mlir_library(MLIRAnalysis MLIRDataLayoutInterfaces MLIRFunctionInterfaces MLIRInferIntRangeInterface + MLIRInferStridedMetadataInterface MLIRInferTypeOpInterface MLIRLoopLikeInterface MLIRPresburger diff --git a/mlir/lib/Analysis/DataFlow/StridedMetadataRangeAnalysis.cpp b/mlir/lib/Analysis/DataFlow/StridedMetadataRangeAnalysis.cpp new file mode 100644 index 0000000..01c9daf --- /dev/null +++ b/mlir/lib/Analysis/DataFlow/StridedMetadataRangeAnalysis.cpp @@ -0,0 +1,127 @@ +//===- StridedMetadataRangeAnalysis.cpp - Integer range analysis --------*- C++ +//-*-===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// +// +// This file defines the dataflow analysis class for integer range inference +// which is used in transformations over the `arith` dialect such as +// branch elimination or signed->unsigned rewriting +// +//===----------------------------------------------------------------------===// + +#include "mlir/Analysis/DataFlow/StridedMetadataRangeAnalysis.h" +#include "mlir/Analysis/DataFlow/IntegerRangeAnalysis.h" +#include "mlir/Dialect/Utils/IndexingUtils.h" +#include "mlir/IR/Operation.h" +#include "mlir/IR/Value.h" +#include "mlir/Support/DebugStringHelper.h" +#include "llvm/Support/Debug.h" +#include "llvm/Support/DebugLog.h" + +#define DEBUG_TYPE "strided-metadata-range-analysis" + +using namespace mlir; +using namespace mlir::dataflow; + +/// Get the entry state for a value. For any value that is not a ranked memref, +/// this function sets the metadata to a top state with no offsets, sizes, or +/// strides. For `memref` types, this function will use the metadata in the type +/// to try to deduce as much informaiton as possible. +static StridedMetadataRange getEntryStateImpl(Value v, int32_t indexBitwidth) { + // TODO: generalize this method with a type interface. + auto mTy = dyn_cast<BaseMemRefType>(v.getType()); + + // If not a memref or it's un-ranked, don't infer any metadata. + if (!mTy || !mTy.hasRank()) + return StridedMetadataRange::getMaxRanges(indexBitwidth, 0, 0, 0); + + // Get the top state. + auto metadata = + StridedMetadataRange::getMaxRanges(indexBitwidth, mTy.getRank()); + + // Compute the offset and strides. + int64_t offset; + SmallVector<int64_t> strides; + if (failed(cast<MemRefType>(mTy).getStridesAndOffset(strides, offset))) + return metadata; + + // Refine the metadata if we know it from the type. + if (!ShapedType::isDynamic(offset)) { + metadata.getOffsets()[0] = + ConstantIntRanges::constant(APInt(indexBitwidth, offset)); + } + for (auto &&[size, range] : + llvm::zip_equal(mTy.getShape(), metadata.getSizes())) { + if (ShapedType::isDynamic(size)) + continue; + range = ConstantIntRanges::constant(APInt(indexBitwidth, size)); + } + for (auto &&[stride, range] : + llvm::zip_equal(strides, metadata.getStrides())) { + if (ShapedType::isDynamic(stride)) + continue; + range = ConstantIntRanges::constant(APInt(indexBitwidth, stride)); + } + + return metadata; +} + +StridedMetadataRangeAnalysis::StridedMetadataRangeAnalysis( + DataFlowSolver &solver, int32_t indexBitwidth) + : SparseForwardDataFlowAnalysis(solver), indexBitwidth(indexBitwidth) { + assert(indexBitwidth > 0 && "invalid bitwidth"); +} + +void StridedMetadataRangeAnalysis::setToEntryState( + StridedMetadataRangeLattice *lattice) { + propagateIfChanged(lattice, lattice->join(getEntryStateImpl( + lattice->getAnchor(), indexBitwidth))); +} + +LogicalResult StridedMetadataRangeAnalysis::visitOperation( + Operation *op, ArrayRef<const StridedMetadataRangeLattice *> operands, + ArrayRef<StridedMetadataRangeLattice *> results) { + auto inferrable = dyn_cast<InferStridedMetadataOpInterface>(op); + + // Bail if we cannot reason about the op. + if (!inferrable) { + setAllToEntryStates(results); + return success(); + } + + LDBG() << "Inferring metadata for: " + << OpWithFlags(op, OpPrintingFlags().skipRegions()); + + // Helper function to retrieve int range values. + auto getIntRange = [&](Value value) -> IntegerValueRange { + auto lattice = getOrCreateFor<IntegerValueRangeLattice>( + getProgramPointAfter(op), value); + return lattice ? lattice->getValue() : IntegerValueRange(); + }; + + // Convert the arguments lattices to a vector. + SmallVector<StridedMetadataRange> argRanges = llvm::map_to_vector( + operands, [](const StridedMetadataRangeLattice *lattice) { + return lattice->getValue(); + }); + + // Callback to set metadata on a result. + auto joinCallback = [&](Value v, const StridedMetadataRange &md) { + auto result = cast<OpResult>(v); + assert(llvm::is_contained(op->getResults(), result)); + LDBG() << "- Inferred metadata: " << md; + StridedMetadataRangeLattice *lattice = results[result.getResultNumber()]; + ChangeResult changed = lattice->join(md); + LDBG() << "- Joined metadata: " << lattice->getValue(); + propagateIfChanged(lattice, changed); + }; + + // Infer the metadata. + inferrable.inferStridedMetadataRanges(argRanges, getIntRange, joinCallback, + indexBitwidth); + return success(); +} diff --git a/mlir/lib/Conversion/CMakeLists.txt b/mlir/lib/Conversion/CMakeLists.txt index 71986f8..bebf1b8 100644 --- a/mlir/lib/Conversion/CMakeLists.txt +++ b/mlir/lib/Conversion/CMakeLists.txt @@ -40,6 +40,7 @@ add_subdirectory(MathToLibm) add_subdirectory(MathToLLVM) add_subdirectory(MathToROCDL) add_subdirectory(MathToSPIRV) +add_subdirectory(MathToXeVM) add_subdirectory(MemRefToEmitC) add_subdirectory(MemRefToLLVM) add_subdirectory(MemRefToSPIRV) diff --git a/mlir/lib/Conversion/MathToXeVM/CMakeLists.txt b/mlir/lib/Conversion/MathToXeVM/CMakeLists.txt new file mode 100644 index 0000000..050c0ed --- /dev/null +++ b/mlir/lib/Conversion/MathToXeVM/CMakeLists.txt @@ -0,0 +1,22 @@ +add_mlir_conversion_library(MLIRMathToXeVM + MathToXeVM.cpp + + ADDITIONAL_HEADER_DIRS + ${MLIR_MAIN_INCLUDE_DIR}/mlir/Conversion/MathToXeVM + + DEPENDS + MLIRConversionPassIncGen + + LINK_COMPONENTS + Core + + LINK_LIBS PUBLIC + MLIRArithAttrToLLVMConversion + MLIRArithDialect + MLIRLLVMCommonConversion + MLIRLLVMDialect + MLIRMathDialect + MLIRXeVMDialect + MLIRPass + MLIRTransforms + ) diff --git a/mlir/lib/Conversion/MathToXeVM/MathToXeVM.cpp b/mlir/lib/Conversion/MathToXeVM/MathToXeVM.cpp new file mode 100644 index 0000000..0fe31d0 --- /dev/null +++ b/mlir/lib/Conversion/MathToXeVM/MathToXeVM.cpp @@ -0,0 +1,167 @@ +//===-- MathToXeVM.cpp - conversion from Math to XeVM ---------------------===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// + +#include "mlir/Conversion/MathToXeVM/MathToXeVM.h" +#include "mlir/Conversion/ArithCommon/AttrToLLVMConverter.h" +#include "mlir/Dialect/LLVMIR/FunctionCallUtils.h" +#include "mlir/Dialect/LLVMIR/LLVMDialect.h" +#include "mlir/Dialect/Math/IR/Math.h" +#include "mlir/IR/BuiltinDialect.h" +#include "mlir/Pass/Pass.h" +#include "llvm/Support/FormatVariadic.h" + +namespace mlir { +#define GEN_PASS_DEF_CONVERTMATHTOXEVM +#include "mlir/Conversion/Passes.h.inc" +} // namespace mlir + +using namespace mlir; + +#define DEBUG_TYPE "math-to-xevm" + +/// Convert math ops marked with `fast` (`afn`) to native OpenCL intrinsics. +template <typename Op> +struct ConvertNativeFuncPattern final : public OpConversionPattern<Op> { + + ConvertNativeFuncPattern(MLIRContext *context, StringRef nativeFunc, + PatternBenefit benefit = 1) + : OpConversionPattern<Op>(context, benefit), nativeFunc(nativeFunc) {} + + LogicalResult + matchAndRewrite(Op op, typename Op::Adaptor adaptor, + ConversionPatternRewriter &rewriter) const override { + if (!isSPIRVCompatibleFloatOrVec(op.getType())) + return failure(); + + arith::FastMathFlags fastFlags = op.getFastmath(); + if (!arith::bitEnumContainsAll(fastFlags, arith::FastMathFlags::afn)) + return rewriter.notifyMatchFailure(op, "not a fastmath `afn` operation"); + + SmallVector<Type, 1> operandTypes; + for (auto operand : adaptor.getOperands()) { + Type opTy = operand.getType(); + // This pass only supports operations on vectors that are already in SPIRV + // supported vector sizes: Distributing unsupported vector sizes to SPIRV + // supported vector sizes are done in other blocking optimization passes. + if (!isSPIRVCompatibleFloatOrVec(opTy)) + return rewriter.notifyMatchFailure( + op, llvm::formatv("incompatible operand type: '{0}'", opTy)); + operandTypes.push_back(opTy); + } + + auto moduleOp = op->template getParentWithTrait<OpTrait::SymbolTable>(); + auto funcOpRes = LLVM::lookupOrCreateFn( + rewriter, moduleOp, getMangledNativeFuncName(operandTypes), + operandTypes, op.getType()); + assert(!failed(funcOpRes)); + LLVM::LLVMFuncOp funcOp = funcOpRes.value(); + + auto callOp = rewriter.replaceOpWithNewOp<LLVM::CallOp>( + op, funcOp, adaptor.getOperands()); + // Preserve fastmath flags in our MLIR op when converting to llvm function + // calls, in order to allow further fastmath optimizations: We thus need to + // convert arith fastmath attrs into attrs recognized by llvm. + arith::AttrConvertFastMathToLLVM<Op, LLVM::CallOp> fastAttrConverter(op); + mlir::NamedAttribute fastAttr = fastAttrConverter.getAttrs()[0]; + callOp->setAttr(fastAttr.getName(), fastAttr.getValue()); + return success(); + } + + inline bool isSPIRVCompatibleFloatOrVec(Type type) const { + if (type.isFloat()) + return true; + if (auto vecType = dyn_cast<VectorType>(type)) { + if (!vecType.getElementType().isFloat()) + return false; + // SPIRV distinguishes between vectors and matrices: OpenCL native math + // intrsinics are not compatible with matrices. + ArrayRef<int64_t> shape = vecType.getShape(); + if (shape.size() != 1) + return false; + // SPIRV only allows vectors of size 2, 3, 4, 8, 16. + if (shape[0] == 2 || shape[0] == 3 || shape[0] == 4 || shape[0] == 8 || + shape[0] == 16) + return true; + } + return false; + } + + inline std::string + getMangledNativeFuncName(const ArrayRef<Type> operandTypes) const { + std::string mangledFuncName = + "_Z" + std::to_string(nativeFunc.size()) + nativeFunc.str(); + + auto appendFloatToMangledFunc = [&mangledFuncName](Type type) { + if (type.isF32()) + mangledFuncName += "f"; + else if (type.isF16()) + mangledFuncName += "Dh"; + else if (type.isF64()) + mangledFuncName += "d"; + }; + + for (auto type : operandTypes) { + if (auto vecType = dyn_cast<VectorType>(type)) { + mangledFuncName += "Dv" + std::to_string(vecType.getShape()[0]) + "_"; + appendFloatToMangledFunc(vecType.getElementType()); + } else + appendFloatToMangledFunc(type); + } + + return mangledFuncName; + } + + const StringRef nativeFunc; +}; + +void mlir::populateMathToXeVMConversionPatterns(RewritePatternSet &patterns, + bool convertArith) { + patterns.add<ConvertNativeFuncPattern<math::ExpOp>>(patterns.getContext(), + "__spirv_ocl_native_exp"); + patterns.add<ConvertNativeFuncPattern<math::CosOp>>(patterns.getContext(), + "__spirv_ocl_native_cos"); + patterns.add<ConvertNativeFuncPattern<math::Exp2Op>>( + patterns.getContext(), "__spirv_ocl_native_exp2"); + patterns.add<ConvertNativeFuncPattern<math::LogOp>>(patterns.getContext(), + "__spirv_ocl_native_log"); + patterns.add<ConvertNativeFuncPattern<math::Log2Op>>( + patterns.getContext(), "__spirv_ocl_native_log2"); + patterns.add<ConvertNativeFuncPattern<math::Log10Op>>( + patterns.getContext(), "__spirv_ocl_native_log10"); + patterns.add<ConvertNativeFuncPattern<math::PowFOp>>( + patterns.getContext(), "__spirv_ocl_native_powr"); + patterns.add<ConvertNativeFuncPattern<math::RsqrtOp>>( + patterns.getContext(), "__spirv_ocl_native_rsqrt"); + patterns.add<ConvertNativeFuncPattern<math::SinOp>>(patterns.getContext(), + "__spirv_ocl_native_sin"); + patterns.add<ConvertNativeFuncPattern<math::SqrtOp>>( + patterns.getContext(), "__spirv_ocl_native_sqrt"); + patterns.add<ConvertNativeFuncPattern<math::TanOp>>(patterns.getContext(), + "__spirv_ocl_native_tan"); + if (convertArith) + patterns.add<ConvertNativeFuncPattern<arith::DivFOp>>( + patterns.getContext(), "__spirv_ocl_native_divide"); +} + +namespace { +struct ConvertMathToXeVMPass + : public impl::ConvertMathToXeVMBase<ConvertMathToXeVMPass> { + using Base::Base; + void runOnOperation() override; +}; +} // namespace + +void ConvertMathToXeVMPass::runOnOperation() { + RewritePatternSet patterns(&getContext()); + populateMathToXeVMConversionPatterns(patterns, convertArith); + ConversionTarget target(getContext()); + target.addLegalDialect<BuiltinDialect, LLVM::LLVMDialect>(); + if (failed( + applyPartialConversion(getOperation(), target, std::move(patterns)))) + signalPassFailure(); +} diff --git a/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp b/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp index a5336ed..00df14b1 100644 --- a/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp +++ b/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp @@ -1392,6 +1392,137 @@ public: } }; +// Collapse tensor<1xiN> into tensor<iN> +// E.g. tensor.collapse_shape %arg1 [] : tensor<1xi16> into tensor<i16> +static Value collapse1xNTensorToN(PatternRewriter &rewriter, Value input, + Location loc) { + SmallVector<ReassociationExprs, 1> reassociation; + // Create the collapsed type + auto inputType = cast<RankedTensorType>(input.getType()); + auto elemType = inputType.getElementType(); + auto collapsedType = RankedTensorType::get({}, elemType); + // Emit the collapse op + return rewriter.create<tensor::CollapseShapeOp>(loc, collapsedType, input, + reassociation); +} + +static llvm::SmallVector<int8_t> +convertToI8(const llvm::SmallVector<int32_t> &input) { + llvm::SmallVector<int8_t> output; + output.reserve(input.size()); + + for (auto v : llvm::map_range( + input, [](int32_t val) { return static_cast<int8_t>(val); })) { + output.push_back(v); + } + return output; +} + +// The shift or multiplier may be either constant or non-constant, depending on +// whether dynamic extension is enabled. +// - If the shift or multiplier is non-constant, add it as an input to +// linalg::GenericOp by: +// 1. Pushing it into 'genericInputs'. +// 2. Appending a corresponding affine map to 'indexingMaps'. +// - If the shift or multiplier is constant, set 'constant' instead. +static void setupLinalgGenericOpInputAndIndexingMap( + PatternRewriter &rewriter, llvm::SmallVector<int32_t> &values, + SmallVector<Value, 4> &genericInputs, SmallVector<AffineMap> &indexingMaps, + bool isConstant, tosa::RescaleOp op, Value &constant, int64_t &arg, + bool isShift = false) { + + auto loc = op.getLoc(); + auto inputTy = cast<ShapedType>(op.getInput().getType()); + unsigned rank = inputTy.getRank(); + SmallVector<AffineExpr, 2> exprs = {rewriter.getAffineDimExpr(rank - 1)}; + + if (isConstant) { + // If we are rescaling per-channel then we need to store the + // values in a buffer. + if (values.size() == 1) { + IntegerAttr intAttr = isShift + ? rewriter.getI8IntegerAttr(values.front()) + : rewriter.getI32IntegerAttr(values.front()); + constant = rewriter.create<arith::ConstantOp>(loc, intAttr); + } else { + auto elementType = + isShift ? rewriter.getIntegerType(8) : rewriter.getI32Type(); + auto tensorType = RankedTensorType::get( + {static_cast<int64_t>(values.size())}, elementType); + DenseIntElementsAttr EltAttr; + if (isShift) + EltAttr = DenseIntElementsAttr::get(tensorType, convertToI8(values)); + else + EltAttr = DenseIntElementsAttr::get(tensorType, values); + genericInputs.push_back( + arith::ConstantOp::create(rewriter, loc, EltAttr)); + indexingMaps.push_back(AffineMap::get(/*dimCount=*/rank, + /*symbolCount=*/0, exprs, + rewriter.getContext())); + } + } else { + // If we are not rescaling per-channel then we need to collapse 1xN to N + // and push broadcastMap. + auto operand = isShift ? op.getShift() : op.getMultiplier(); + auto tensorType = dyn_cast<RankedTensorType>(operand.getType()); + if (tensorType && tensorType.hasStaticShape() && + tensorType.getShape()[0] == 1) { + // broadcastMap = affine_map<(d0, d1) -> ()> + // It would affect as broadcast for scalar values in linalg::GenericOp. + AffineMap broadcastMap = + AffineMap::get(rank, 0, {}, rewriter.getContext()); + genericInputs.push_back(collapse1xNTensorToN(rewriter, operand, loc)); + indexingMaps.push_back(broadcastMap); + } else { + genericInputs.push_back(operand); + indexingMaps.push_back(AffineMap::get(/*dimCount=*/rank, + /*symbolCount=*/0, exprs, + rewriter.getContext())); + } + } + arg = indexingMaps.size() - 1; +} + +// Return the extended Zp to be used in subsequent arithmetic operations. +static Value getExtendZp(OpBuilder &builder, Type valueTy, + FailureOr<int64_t> maybeZp, Location loc, + ValueRange blockArgs, int64_t zpArg, + bool isOutputZp = false) { + Value result; + const int32_t bitwidth = valueTy.getIntOrFloatBitWidth(); + const uint32_t attrBitwidth = + isOutputZp ? 32 : (bitwidth > 32 ? bitwidth : 32); + auto extendType = builder.getIntegerType(attrBitwidth); + // The Zp value can be either constant or non-constant, depending on + // whether dynamic extension is enabled. + // If 'maybeZp' fails, it indicates that Zp is non-constant and will + // be passed as an input to linalg::GenericOp. + if (failed(maybeZp)) { + result = blockArgs[zpArg]; + auto zpTy = result.getType(); + if (zpTy.getIntOrFloatBitWidth() < attrBitwidth) { + // For ExtUIOp, the input must be signless. + // UnrealizedConversionCastOp will cast the input to signless type. + if (zpTy.isUnsignedInteger()) { + result = + UnrealizedConversionCastOp::create( + builder, loc, + builder.getIntegerType(zpTy.getIntOrFloatBitWidth()), result) + .getResult(0); + } + if (zpTy.isUnsignedInteger()) { + return builder.create<arith::ExtUIOp>(loc, extendType, result); + } else { + return builder.create<arith::ExtSIOp>(loc, extendType, result); + } + } + } else { + return builder.create<arith::ConstantOp>( + loc, IntegerAttr::get(extendType, *maybeZp)); + } + return result; +} + class RescaleConverter : public OpRewritePattern<tosa::RescaleOp> { public: using OpRewritePattern<tosa::RescaleOp>::OpRewritePattern; @@ -1423,40 +1554,46 @@ public: } } - // The shift and multiplier values. DenseElementsAttr shiftElems; - if (!matchPattern(op.getShift(), m_Constant(&shiftElems))) - return rewriter.notifyMatchFailure( - op, "tosa.rescale requires constant shift input values"); + bool isShiftConstant = false; + if (matchPattern(op.getShift(), m_Constant(&shiftElems))) + isShiftConstant = true; DenseElementsAttr multiplierElems; - if (!matchPattern(op.getMultiplier(), m_Constant(&multiplierElems))) - return rewriter.notifyMatchFailure( - op, "tosa.rescale requires constant multiplier input values"); - - llvm::SmallVector<int8_t> shiftValues = - llvm::to_vector(shiftElems.getValues<int8_t>()); - // explicit cast is required here - llvm::SmallVector<int32_t> multiplierValues = llvm::to_vector( - llvm::map_range(multiplierElems.getValues<IntegerAttr>(), - [](IntegerAttr attr) -> int32_t { - return static_cast<int32_t>(attr.getInt()); - })); - - // If we shift by more than the bitwidth, this just sets to 0. - for (int i = 0, s = multiplierValues.size(); i < s; i++) { - if (shiftValues[i] > 63) { - shiftValues[i] = 0; - multiplierValues[i] = 0; + bool isMultiplierConstant = false; + if (matchPattern(op.getMultiplier(), m_Constant(&multiplierElems))) + isMultiplierConstant = true; + + llvm::SmallVector<int32_t> shiftValues; + llvm::SmallVector<int32_t> multiplierValues; + bool doubleRound; + + if (isMultiplierConstant && isShiftConstant) { + // explicit cast is required here + shiftValues = llvm::to_vector(llvm::map_range( + shiftElems.getValues<IntegerAttr>(), [](IntegerAttr attr) -> int32_t { + return static_cast<int32_t>(attr.getInt()); + })); + multiplierValues = llvm::to_vector( + llvm::map_range(multiplierElems.getValues<IntegerAttr>(), + [](IntegerAttr attr) -> int32_t { + return static_cast<int32_t>(attr.getInt()); + })); + + // If we shift by more than the bitwidth, this just sets to 0. + for (int i = 0, s = multiplierValues.size(); i < s; i++) { + if (shiftValues[i] > 63) { + shiftValues[i] = 0; + multiplierValues[i] = 0; + } } - } + // Double round only occurs if shift is greater than 31, check that this + // is ever true. + doubleRound = op.getRoundingMode() == RoundingMode::DOUBLE_ROUND && + llvm::any_of(shiftValues, [](int32_t v) { return v > 31; }); + } else + doubleRound = op.getRoundingMode() == RoundingMode::DOUBLE_ROUND; - // Double round only occurs if shift is greater than 31, check that this - // is ever true. - - bool doubleRound = - op.getRoundingMode() == RoundingMode::DOUBLE_ROUND && - llvm::any_of(shiftValues, [](int32_t v) { return v > 31; }); RoundingMode roundingMode = doubleRound ? RoundingMode::DOUBLE_ROUND : RoundingMode::SINGLE_ROUND; @@ -1468,45 +1605,43 @@ public: // values in a buffer. Value multiplierConstant; int64_t multiplierArg = 0; - if (multiplierValues.size() == 1) { - multiplierConstant = arith::ConstantOp::create( - rewriter, loc, rewriter.getI32IntegerAttr(multiplierValues.front())); - } else { - SmallVector<AffineExpr, 2> multiplierExprs{ - rewriter.getAffineDimExpr(rank - 1)}; - auto multiplierType = - RankedTensorType::get({static_cast<int64_t>(multiplierValues.size())}, - rewriter.getI32Type()); - genericInputs.push_back(arith::ConstantOp::create( - rewriter, loc, - DenseIntElementsAttr::get(multiplierType, multiplierValues))); - - indexingMaps.push_back(AffineMap::get(/*dimCount=*/rank, - /*symbolCount=*/0, multiplierExprs, - rewriter.getContext())); - - multiplierArg = indexingMaps.size() - 1; - } + setupLinalgGenericOpInputAndIndexingMap( + rewriter, multiplierValues, genericInputs, indexingMaps, + isMultiplierConstant, op, multiplierConstant, multiplierArg); // If we are rescaling per-channel then we need to store the shift // values in a buffer. Value shiftConstant; int64_t shiftArg = 0; - if (shiftValues.size() == 1) { - shiftConstant = arith::ConstantOp::create( - rewriter, loc, rewriter.getI8IntegerAttr(shiftValues.front())); - } else { - SmallVector<AffineExpr, 2> shiftExprs = { - rewriter.getAffineDimExpr(rank - 1)}; - auto shiftType = - RankedTensorType::get({static_cast<int64_t>(shiftValues.size())}, - rewriter.getIntegerType(8)); - genericInputs.push_back(arith::ConstantOp::create( - rewriter, loc, DenseIntElementsAttr::get(shiftType, shiftValues))); - indexingMaps.push_back(AffineMap::get(/*dimCount=*/rank, - /*symbolCount=*/0, shiftExprs, - rewriter.getContext())); - shiftArg = indexingMaps.size() - 1; + setupLinalgGenericOpInputAndIndexingMap( + rewriter, shiftValues, genericInputs, indexingMaps, isShiftConstant, op, + shiftConstant, shiftArg, true); + + // broadcastMap = affine_map<(d0, d1) -> ()> + // It would affect as broadcast for scalar values in linalg::GenericOp. + AffineMap broadcastMap = AffineMap::get(rank, 0, {}, rewriter.getContext()); + FailureOr<int64_t> maybeIZp = op.getInputZeroPoint(); + FailureOr<int64_t> maybeOZp = op.getOutputZeroPoint(); + // The inputZp and outputZp may be either constant or non-constant, + // depending on whether dynamic extension is enabled. + // - If the zp's are non-constant, add them as an inputs to + // linalg::GenericOp by: + // 1. Pushing it into 'genericInputs'. + // 2. Appending a corresponding affine map to 'indexingMaps'. + // - If the zp's are constant, they would be generated as arith.constant. + int64_t iZpArg = 0; + if (failed(maybeIZp)) { + genericInputs.push_back( + collapse1xNTensorToN(rewriter, op->getOperand(3), loc)); + indexingMaps.push_back(broadcastMap); + iZpArg = indexingMaps.size() - 1; + } + int64_t oZpArg = 0; + if (failed(maybeOZp)) { + genericInputs.push_back( + collapse1xNTensorToN(rewriter, op->getOperand(4), loc)); + indexingMaps.push_back(broadcastMap); + oZpArg = indexingMaps.size() - 1; } // Indexing maps for output values. @@ -1526,36 +1661,17 @@ public: Type valueTy = value.getType(); FailureOr<int64_t> maybeIZp = op.getInputZeroPoint(); - if (failed(maybeIZp)) { - (void)rewriter.notifyMatchFailure( - op, "input zero point cannot be statically determined"); - return; - } - - const int32_t inBitwidth = valueTy.getIntOrFloatBitWidth(); - // Extend zeropoint for sub-32bits widths. - const int32_t inAttrBitwidth = inBitwidth > 32 ? inBitwidth : 32; - auto inputZp = arith::ConstantOp::create( - nestedBuilder, loc, - IntegerAttr::get(rewriter.getIntegerType(inAttrBitwidth), - *maybeIZp)); + auto inputZp = getExtendZp(nestedBuilder, valueTy, maybeIZp, + nestedLoc, blockArgs, iZpArg); FailureOr<int64_t> maybeOZp = op.getOutputZeroPoint(); - if (failed(maybeOZp)) { - (void)rewriter.notifyMatchFailure( - op, "output zero point cannot be statically determined"); - return; - }; + auto outputZp = getExtendZp(nestedBuilder, valueTy, maybeOZp, + nestedLoc, blockArgs, oZpArg, true); IntegerType outIntType = cast<IntegerType>(blockArgs.back().getType()); unsigned outBitWidth = outIntType.getWidth(); - const int32_t outAttrBitwidth = 32; assert(outBitWidth <= 32 && "Unexpected output zeropoint bitwidth"); - auto outputZp = arith::ConstantOp::create( - nestedBuilder, loc, - IntegerAttr::get(rewriter.getIntegerType(outAttrBitwidth), - *maybeOZp)); Value multiplier = multiplierConstant ? multiplierConstant : blockArgs[multiplierArg]; diff --git a/mlir/lib/Dialect/Bufferization/Transforms/DropEquivalentBufferResults.cpp b/mlir/lib/Dialect/Bufferization/Transforms/DropEquivalentBufferResults.cpp index 624519f..70faa71 100644 --- a/mlir/lib/Dialect/Bufferization/Transforms/DropEquivalentBufferResults.cpp +++ b/mlir/lib/Dialect/Bufferization/Transforms/DropEquivalentBufferResults.cpp @@ -64,12 +64,13 @@ mlir::bufferization::dropEquivalentBufferResults(ModuleOp module) { module.walk([&](func::CallOp callOp) { if (func::FuncOp calledFunc = dyn_cast_or_null<func::FuncOp>(callOp.resolveCallable())) { - callerMap[calledFunc].insert(callOp); + if (!calledFunc.isPublic() && !calledFunc.isExternal()) + callerMap[calledFunc].insert(callOp); } }); for (auto funcOp : module.getOps<func::FuncOp>()) { - if (funcOp.isExternal()) + if (funcOp.isExternal() || funcOp.isPublic()) continue; func::ReturnOp returnOp = getAssumedUniqueReturnOp(funcOp); // TODO: Support functions with multiple blocks. diff --git a/mlir/lib/Dialect/LLVMIR/IR/NVVMDialect.cpp b/mlir/lib/Dialect/LLVMIR/IR/NVVMDialect.cpp index 5edcc40b..ab54183 100644 --- a/mlir/lib/Dialect/LLVMIR/IR/NVVMDialect.cpp +++ b/mlir/lib/Dialect/LLVMIR/IR/NVVMDialect.cpp @@ -309,6 +309,17 @@ LogicalResult ConvertBF16x2ToF8x2Op::verify() { return success(); } +LogicalResult ConvertF32x2ToF4x2Op::verify() { + mlir::MLIRContext *ctx = getContext(); + + if (!llvm::isa<mlir::Float4E2M1FNType>(getDstTy())) + return emitOpError("Only ") + << mlir::Float4E2M1FNType::get(ctx) + << " type is supported for conversions from f32x2 to f4x2."; + + return success(); +} + LogicalResult BulkStoreOp::verify() { if (getInitVal() != 0) return emitOpError("only 0 is supported for initVal, got ") << getInitVal(); @@ -2047,6 +2058,23 @@ ConvertFloatToTF32Op::getIntrinsicID(NVVM::FPRoundingMode rnd, } } +NVVM::IDArgPair +ConvertF32x2ToF4x2Op::getIntrinsicIDAndArgs(NVVM::ConvertF32x2ToF4x2Op op, + LLVM::ModuleTranslation &mt, + llvm::IRBuilderBase &builder) { + llvm::SmallVector<llvm::Value *> args; + args.push_back(mt.lookupValue(op.getA())); + args.push_back(mt.lookupValue(op.getB())); + + bool hasRelu = op.getRelu(); + + llvm::Intrinsic::ID intId = + hasRelu ? llvm::Intrinsic::nvvm_ff_to_e2m1x2_rn_relu_satfinite + : llvm::Intrinsic::nvvm_ff_to_e2m1x2_rn_satfinite; + + return {intId, std::move(args)}; +} + #define GET_F32x2_TO_F6x2_ID(type, has_relu) \ has_relu ? llvm::Intrinsic::nvvm_ff_to_##type##_rn_relu_satfinite \ : llvm::Intrinsic::nvvm_ff_to_##type##_rn_satfinite diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgInterfaces.cpp b/mlir/lib/Dialect/Linalg/IR/LinalgInterfaces.cpp index c477c6c..dcc1ef9 100644 --- a/mlir/lib/Dialect/Linalg/IR/LinalgInterfaces.cpp +++ b/mlir/lib/Dialect/Linalg/IR/LinalgInterfaces.cpp @@ -315,7 +315,8 @@ bool mlir::linalg::detail::isContractionBody( Value yielded = getSourceSkipUnary(terminator->getOperand(0)); Operation *reductionOp = yielded.getDefiningOp(); - if (reductionOp->getNumResults() != 1 || reductionOp->getNumOperands() != 2) { + if (!reductionOp || reductionOp->getNumResults() != 1 || + reductionOp->getNumOperands() != 2) { errs << "expected reduction op to be binary"; return false; } diff --git a/mlir/lib/Dialect/MemRef/IR/CMakeLists.txt b/mlir/lib/Dialect/MemRef/IR/CMakeLists.txt index e25a012..1382c7ac 100644 --- a/mlir/lib/Dialect/MemRef/IR/CMakeLists.txt +++ b/mlir/lib/Dialect/MemRef/IR/CMakeLists.txt @@ -5,7 +5,7 @@ add_mlir_dialect_library(MLIRMemRefDialect ValueBoundsOpInterfaceImpl.cpp ADDITIONAL_HEADER_DIRS - ${PROJECT_SOURCE_DIR}/inlude/mlir/Dialect/MemRefDialect + ${PROJECT_SOURCE_DIR}/inlude/mlir/Dialect/MemRef/IR DEPENDS MLIRMemRefOpsIncGen @@ -18,6 +18,7 @@ add_mlir_dialect_library(MLIRMemRefDialect MLIRDialectUtils MLIRInferIntRangeCommon MLIRInferIntRangeInterface + MLIRInferStridedMetadataInterface MLIRInferTypeOpInterface MLIRIR MLIRMemOpInterfaces diff --git a/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp b/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp index e9bdcda..507597b 100644 --- a/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp +++ b/mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp @@ -3437,6 +3437,65 @@ SubViewOp::bubbleDownCasts(OpBuilder &builder) { return bubbleDownCastsPassthroughOpImpl(*this, builder, getSourceMutable()); } +void SubViewOp::inferStridedMetadataRanges( + ArrayRef<StridedMetadataRange> ranges, GetIntRangeFn getIntRange, + SetStridedMetadataRangeFn setMetadata, int32_t indexBitwidth) { + auto isUninitialized = + +[](IntegerValueRange range) { return range.isUninitialized(); }; + + // Bail early if any of the operands metadata is not ready: + SmallVector<IntegerValueRange> offsetOperands = + getIntValueRanges(getMixedOffsets(), getIntRange, indexBitwidth); + if (llvm::any_of(offsetOperands, isUninitialized)) + return; + + SmallVector<IntegerValueRange> sizeOperands = + getIntValueRanges(getMixedSizes(), getIntRange, indexBitwidth); + if (llvm::any_of(sizeOperands, isUninitialized)) + return; + + SmallVector<IntegerValueRange> stridesOperands = + getIntValueRanges(getMixedStrides(), getIntRange, indexBitwidth); + if (llvm::any_of(stridesOperands, isUninitialized)) + return; + + StridedMetadataRange sourceRange = + ranges[getSourceMutable().getOperandNumber()]; + if (sourceRange.isUninitialized()) + return; + + ArrayRef<ConstantIntRanges> srcStrides = sourceRange.getStrides(); + + // Get the dropped dims. + llvm::SmallBitVector droppedDims = getDroppedDims(); + + // Compute the new offset, strides and sizes. + ConstantIntRanges offset = sourceRange.getOffsets()[0]; + SmallVector<ConstantIntRanges> strides, sizes; + + for (size_t i = 0, e = droppedDims.size(); i < e; ++i) { + bool dropped = droppedDims.test(i); + // Compute the new offset. + ConstantIntRanges off = + intrange::inferMul({offsetOperands[i].getValue(), srcStrides[i]}); + offset = intrange::inferAdd({offset, off}); + + // Skip dropped dimensions. + if (dropped) + continue; + // Multiply the strides. + strides.push_back( + intrange::inferMul({stridesOperands[i].getValue(), srcStrides[i]})); + // Get the sizes. + sizes.push_back(sizeOperands[i].getValue()); + } + + setMetadata(getResult(), + StridedMetadataRange::getRanked( + SmallVector<ConstantIntRanges>({std::move(offset)}), + std::move(sizes), std::move(strides))); +} + //===----------------------------------------------------------------------===// // TransposeOp //===----------------------------------------------------------------------===// diff --git a/mlir/lib/Dialect/OpenACC/IR/OpenACC.cpp b/mlir/lib/Dialect/OpenACC/IR/OpenACC.cpp index 6564a4e..642ced9 100644 --- a/mlir/lib/Dialect/OpenACC/IR/OpenACC.cpp +++ b/mlir/lib/Dialect/OpenACC/IR/OpenACC.cpp @@ -17,6 +17,7 @@ #include "mlir/IR/DialectImplementation.h" #include "mlir/IR/Matchers.h" #include "mlir/IR/OpImplementation.h" +#include "mlir/IR/SymbolTable.h" #include "mlir/Support/LLVM.h" #include "mlir/Transforms/DialectConversion.h" #include "llvm/ADT/SmallSet.h" @@ -74,14 +75,16 @@ struct MemRefPointerLikeModel } mlir::Value genAllocate(Type pointer, OpBuilder &builder, Location loc, - StringRef varName, Type varType, - Value originalVar) const { + StringRef varName, Type varType, Value originalVar, + bool &needsFree) const { auto memrefTy = cast<MemRefType>(pointer); // Check if this is a static memref (all dimensions are known) - if yes // then we can generate an alloca operation. - if (memrefTy.hasStaticShape()) + if (memrefTy.hasStaticShape()) { + needsFree = false; // alloca doesn't need deallocation return memref::AllocaOp::create(builder, loc, memrefTy).getResult(); + } // For dynamic memrefs, extract sizes from the original variable if // provided. Otherwise they cannot be handled. @@ -99,6 +102,7 @@ struct MemRefPointerLikeModel // Note: We only add dynamic sizes to the dynamicSizes array // Static dimensions are handled automatically by AllocOp } + needsFree = true; // alloc needs deallocation return memref::AllocOp::create(builder, loc, memrefTy, dynamicSizes) .getResult(); } @@ -108,10 +112,14 @@ struct MemRefPointerLikeModel } bool genFree(Type pointer, OpBuilder &builder, Location loc, - TypedValue<PointerLikeType> varPtr, Type varType) const { - if (auto memrefValue = dyn_cast<TypedValue<MemRefType>>(varPtr)) { + TypedValue<PointerLikeType> varToFree, Value allocRes, + Type varType) const { + if (auto memrefValue = dyn_cast<TypedValue<MemRefType>>(varToFree)) { + // Use allocRes if provided to determine the allocation type + Value valueToInspect = allocRes ? allocRes : memrefValue; + // Walk through casts to find the original allocation - Value currentValue = memrefValue; + Value currentValue = valueToInspect; Operation *originalAlloc = nullptr; // Follow the chain of operations to find the original allocation @@ -150,7 +158,7 @@ struct MemRefPointerLikeModel return true; } if (isa<memref::AllocOp>(originalAlloc)) { - // This is an alloc - generate dealloc + // This is an alloc - generate dealloc on varToFree memref::DeallocOp::create(builder, loc, memrefValue); return true; } @@ -1003,6 +1011,142 @@ struct RemoveConstantIfConditionWithRegion : public OpRewritePattern<OpTy> { } }; +//===----------------------------------------------------------------------===// +// Recipe Region Helpers +//===----------------------------------------------------------------------===// + +/// Create and populate an init region for privatization recipes. +/// Returns the init block on success, or nullptr on failure. +/// Sets needsFree to indicate if the allocated memory requires deallocation. +static std::unique_ptr<Block> createInitRegion(OpBuilder &builder, Location loc, + Type varType, StringRef varName, + ValueRange bounds, + bool &needsFree) { + // Create init block with arguments: original value + bounds + SmallVector<Type> argTypes{varType}; + SmallVector<Location> argLocs{loc}; + for (Value bound : bounds) { + argTypes.push_back(bound.getType()); + argLocs.push_back(loc); + } + + auto initBlock = std::make_unique<Block>(); + initBlock->addArguments(argTypes, argLocs); + builder.setInsertionPointToStart(initBlock.get()); + + Value privatizedValue; + + // Get the block argument that represents the original variable + Value blockArgVar = initBlock->getArgument(0); + + // Generate init region body based on variable type + if (isa<MappableType>(varType)) { + auto mappableTy = cast<MappableType>(varType); + auto typedVar = cast<TypedValue<MappableType>>(blockArgVar); + privatizedValue = mappableTy.generatePrivateInit( + builder, loc, typedVar, varName, bounds, {}, needsFree); + if (!privatizedValue) + return nullptr; + } else { + assert(isa<PointerLikeType>(varType) && "Expected PointerLikeType"); + auto pointerLikeTy = cast<PointerLikeType>(varType); + // Use PointerLikeType's allocation API with the block argument + privatizedValue = pointerLikeTy.genAllocate(builder, loc, varName, varType, + blockArgVar, needsFree); + if (!privatizedValue) + return nullptr; + } + + // Add yield operation to init block + acc::YieldOp::create(builder, loc, privatizedValue); + + return initBlock; +} + +/// Create and populate a copy region for firstprivate recipes. +/// Returns the copy block on success, or nullptr on failure. +/// TODO: Handle MappableType - it does not yet have a copy API. +static std::unique_ptr<Block> createCopyRegion(OpBuilder &builder, Location loc, + Type varType, + ValueRange bounds) { + // Create copy block with arguments: original value + privatized value + + // bounds + SmallVector<Type> copyArgTypes{varType, varType}; + SmallVector<Location> copyArgLocs{loc, loc}; + for (Value bound : bounds) { + copyArgTypes.push_back(bound.getType()); + copyArgLocs.push_back(loc); + } + + auto copyBlock = std::make_unique<Block>(); + copyBlock->addArguments(copyArgTypes, copyArgLocs); + builder.setInsertionPointToStart(copyBlock.get()); + + bool isMappable = isa<MappableType>(varType); + bool isPointerLike = isa<PointerLikeType>(varType); + // TODO: Handle MappableType - it does not yet have a copy API. + // Otherwise, for now just fallback to pointer-like behavior. + if (isMappable && !isPointerLike) + return nullptr; + + // Generate copy region body based on variable type + if (isPointerLike) { + auto pointerLikeTy = cast<PointerLikeType>(varType); + Value originalArg = copyBlock->getArgument(0); + Value privatizedArg = copyBlock->getArgument(1); + + // Generate copy operation using PointerLikeType interface + if (!pointerLikeTy.genCopy( + builder, loc, cast<TypedValue<PointerLikeType>>(privatizedArg), + cast<TypedValue<PointerLikeType>>(originalArg), varType)) + return nullptr; + } + + // Add terminator to copy block + acc::TerminatorOp::create(builder, loc); + + return copyBlock; +} + +/// Create and populate a destroy region for privatization recipes. +/// Returns the destroy block on success, or nullptr if not needed. +static std::unique_ptr<Block> createDestroyRegion(OpBuilder &builder, + Location loc, Type varType, + Value allocRes, + ValueRange bounds) { + // Create destroy block with arguments: original value + privatized value + + // bounds + SmallVector<Type> destroyArgTypes{varType, varType}; + SmallVector<Location> destroyArgLocs{loc, loc}; + for (Value bound : bounds) { + destroyArgTypes.push_back(bound.getType()); + destroyArgLocs.push_back(loc); + } + + auto destroyBlock = std::make_unique<Block>(); + destroyBlock->addArguments(destroyArgTypes, destroyArgLocs); + builder.setInsertionPointToStart(destroyBlock.get()); + + bool isMappable = isa<MappableType>(varType); + bool isPointerLike = isa<PointerLikeType>(varType); + // TODO: Handle MappableType - it does not yet have a deallocation API. + // Otherwise, for now just fallback to pointer-like behavior. + if (isMappable && !isPointerLike) + return nullptr; + + assert(isa<PointerLikeType>(varType) && "Expected PointerLikeType"); + auto pointerLikeTy = cast<PointerLikeType>(varType); + auto privatizedArg = + cast<TypedValue<PointerLikeType>>(destroyBlock->getArgument(1)); + // Pass allocRes to help determine the allocation type + if (!pointerLikeTy.genFree(builder, loc, privatizedArg, allocRes, varType)) + return nullptr; + + acc::TerminatorOp::create(builder, loc); + + return destroyBlock; +} + } // namespace //===----------------------------------------------------------------------===// @@ -1050,6 +1194,55 @@ LogicalResult acc::PrivateRecipeOp::verifyRegions() { return success(); } +std::optional<PrivateRecipeOp> +PrivateRecipeOp::createAndPopulate(OpBuilder &builder, Location loc, + StringRef recipeName, Type varType, + StringRef varName, ValueRange bounds) { + // First, validate that we can handle this variable type + bool isMappable = isa<MappableType>(varType); + bool isPointerLike = isa<PointerLikeType>(varType); + + // Unsupported type + if (!isMappable && !isPointerLike) + return std::nullopt; + + // Create init and destroy blocks using shared helpers + OpBuilder::InsertionGuard guard(builder); + + // Save the original insertion point for creating the recipe operation later + auto originalInsertionPoint = builder.saveInsertionPoint(); + + bool needsFree = false; + auto initBlock = + createInitRegion(builder, loc, varType, varName, bounds, needsFree); + if (!initBlock) + return std::nullopt; + + // Only create destroy region if the allocation needs deallocation + std::unique_ptr<Block> destroyBlock; + if (needsFree) { + // Extract the allocated value from the init block's yield operation + auto yieldOp = cast<acc::YieldOp>(initBlock->getTerminator()); + Value allocRes = yieldOp.getOperand(0); + + destroyBlock = createDestroyRegion(builder, loc, varType, allocRes, bounds); + if (!destroyBlock) + return std::nullopt; + } + + // Now create the recipe operation at the original insertion point and attach + // the blocks + builder.restoreInsertionPoint(originalInsertionPoint); + auto recipe = PrivateRecipeOp::create(builder, loc, recipeName, varType); + + // Move the blocks into the recipe's regions + recipe.getInitRegion().push_back(initBlock.release()); + if (destroyBlock) + recipe.getDestroyRegion().push_back(destroyBlock.release()); + + return recipe; +} + //===----------------------------------------------------------------------===// // FirstprivateRecipeOp //===----------------------------------------------------------------------===// @@ -1080,6 +1273,60 @@ LogicalResult acc::FirstprivateRecipeOp::verifyRegions() { return success(); } +std::optional<FirstprivateRecipeOp> +FirstprivateRecipeOp::createAndPopulate(OpBuilder &builder, Location loc, + StringRef recipeName, Type varType, + StringRef varName, ValueRange bounds) { + // First, validate that we can handle this variable type + bool isMappable = isa<MappableType>(varType); + bool isPointerLike = isa<PointerLikeType>(varType); + + // Unsupported type + if (!isMappable && !isPointerLike) + return std::nullopt; + + // Create init, copy, and destroy blocks using shared helpers + OpBuilder::InsertionGuard guard(builder); + + // Save the original insertion point for creating the recipe operation later + auto originalInsertionPoint = builder.saveInsertionPoint(); + + bool needsFree = false; + auto initBlock = + createInitRegion(builder, loc, varType, varName, bounds, needsFree); + if (!initBlock) + return std::nullopt; + + auto copyBlock = createCopyRegion(builder, loc, varType, bounds); + if (!copyBlock) + return std::nullopt; + + // Only create destroy region if the allocation needs deallocation + std::unique_ptr<Block> destroyBlock; + if (needsFree) { + // Extract the allocated value from the init block's yield operation + auto yieldOp = cast<acc::YieldOp>(initBlock->getTerminator()); + Value allocRes = yieldOp.getOperand(0); + + destroyBlock = createDestroyRegion(builder, loc, varType, allocRes, bounds); + if (!destroyBlock) + return std::nullopt; + } + + // Now create the recipe operation at the original insertion point and attach + // the blocks + builder.restoreInsertionPoint(originalInsertionPoint); + auto recipe = FirstprivateRecipeOp::create(builder, loc, recipeName, varType); + + // Move the blocks into the recipe's regions + recipe.getInitRegion().push_back(initBlock.release()); + recipe.getCopyRegion().push_back(copyBlock.release()); + if (destroyBlock) + recipe.getDestroyRegion().push_back(destroyBlock.release()); + + return recipe; +} + //===----------------------------------------------------------------------===// // ReductionRecipeOp //===----------------------------------------------------------------------===// diff --git a/mlir/lib/IR/MLIRContext.cpp b/mlir/lib/IR/MLIRContext.cpp index 1fa04ed..89b81cf 100644 --- a/mlir/lib/IR/MLIRContext.cpp +++ b/mlir/lib/IR/MLIRContext.cpp @@ -121,6 +121,11 @@ namespace mlir { class MLIRContextImpl { public: //===--------------------------------------------------------------------===// + // Remark + //===--------------------------------------------------------------------===// + std::unique_ptr<remark::detail::RemarkEngine> remarkEngine; + + //===--------------------------------------------------------------------===// // Debugging //===--------------------------------------------------------------------===// @@ -135,11 +140,6 @@ public: DiagnosticEngine diagEngine; //===--------------------------------------------------------------------===// - // Remark - //===--------------------------------------------------------------------===// - std::unique_ptr<remark::detail::RemarkEngine> remarkEngine; - - //===--------------------------------------------------------------------===// // Options //===--------------------------------------------------------------------===// @@ -357,7 +357,10 @@ MLIRContext::MLIRContext(const DialectRegistry ®istry, Threading setting) impl->affineUniquer.registerParametricStorageType<IntegerSetStorage>(); } -MLIRContext::~MLIRContext() = default; +MLIRContext::~MLIRContext() { + // finalize remark engine before destroying anything else. + impl->remarkEngine.reset(); +} /// Copy the specified array of elements into memory managed by the provided /// bump pointer allocator. This assumes the elements are all PODs. diff --git a/mlir/lib/IR/Remarks.cpp b/mlir/lib/IR/Remarks.cpp index a55f61a..031eae2 100644 --- a/mlir/lib/IR/Remarks.cpp +++ b/mlir/lib/IR/Remarks.cpp @@ -16,7 +16,7 @@ #include "llvm/ADT/StringRef.h" using namespace mlir::remark::detail; - +using namespace mlir::remark; //------------------------------------------------------------------------------ // Remark //------------------------------------------------------------------------------ @@ -70,7 +70,7 @@ static void printArgs(llvm::raw_ostream &os, llvm::ArrayRef<Remark::Arg> args) { void Remark::print(llvm::raw_ostream &os, bool printLocation) const { // Header: [Type] pass:remarkName StringRef type = getRemarkTypeString(); - StringRef categoryName = getFullCategoryName(); + StringRef categoryName = getCombinedCategoryName(); StringRef name = remarkName; os << '[' << type << "] "; @@ -81,9 +81,10 @@ void Remark::print(llvm::raw_ostream &os, bool printLocation) const { os << "Function=" << getFunction() << " | "; if (printLocation) { - if (auto flc = mlir::dyn_cast<mlir::FileLineColLoc>(getLocation())) + if (auto flc = mlir::dyn_cast<mlir::FileLineColLoc>(getLocation())) { os << " @" << flc.getFilename() << ":" << flc.getLine() << ":" << flc.getColumn(); + } } printArgs(os, getArgs()); @@ -140,7 +141,7 @@ llvm::remarks::Remark Remark::generateRemark() const { r.RemarkType = getRemarkType(); r.RemarkName = getRemarkName(); // MLIR does not use passes; instead, it has categories and sub-categories. - r.PassName = getFullCategoryName(); + r.PassName = getCombinedCategoryName(); r.FunctionName = getFunction(); r.Loc = locLambda(); for (const Remark::Arg &arg : getArgs()) { @@ -225,26 +226,42 @@ InFlightRemark RemarkEngine::emitOptimizationRemarkAnalysis(Location loc, // RemarkEngine //===----------------------------------------------------------------------===// -void RemarkEngine::report(const Remark &&remark) { +void RemarkEngine::reportImpl(const Remark &remark) { // Stream the remark - if (remarkStreamer) + if (remarkStreamer) { remarkStreamer->streamOptimizationRemark(remark); + } // Print using MLIR's diagnostic if (printAsEmitRemarks) emitRemark(remark.getLocation(), remark.getMsg()); } +void RemarkEngine::report(const Remark &&remark) { + if (remarkEmittingPolicy) + remarkEmittingPolicy->reportRemark(remark); +} + RemarkEngine::~RemarkEngine() { + if (remarkEmittingPolicy) + remarkEmittingPolicy->finalize(); + if (remarkStreamer) remarkStreamer->finalize(); } -llvm::LogicalResult -RemarkEngine::initialize(std::unique_ptr<MLIRRemarkStreamerBase> streamer, - std::string *errMsg) { - // If you need to validate categories/filters, do so here and set errMsg. +llvm::LogicalResult RemarkEngine::initialize( + std::unique_ptr<MLIRRemarkStreamerBase> streamer, + std::unique_ptr<RemarkEmittingPolicyBase> remarkEmittingPolicy, + std::string *errMsg) { + remarkStreamer = std::move(streamer); + + auto reportFunc = + std::bind(&RemarkEngine::reportImpl, this, std::placeholders::_1); + remarkEmittingPolicy->initialize(ReportFn(std::move(reportFunc))); + + this->remarkEmittingPolicy = std::move(remarkEmittingPolicy); return success(); } @@ -301,14 +318,15 @@ RemarkEngine::RemarkEngine(bool printAsEmitRemarks, } llvm::LogicalResult mlir::remark::enableOptimizationRemarks( - MLIRContext &ctx, - std::unique_ptr<remark::detail::MLIRRemarkStreamerBase> streamer, - const remark::RemarkCategories &cats, bool printAsEmitRemarks) { + MLIRContext &ctx, std::unique_ptr<detail::MLIRRemarkStreamerBase> streamer, + std::unique_ptr<detail::RemarkEmittingPolicyBase> remarkEmittingPolicy, + const RemarkCategories &cats, bool printAsEmitRemarks) { auto engine = - std::make_unique<remark::detail::RemarkEngine>(printAsEmitRemarks, cats); + std::make_unique<detail::RemarkEngine>(printAsEmitRemarks, cats); std::string errMsg; - if (failed(engine->initialize(std::move(streamer), &errMsg))) { + if (failed(engine->initialize(std::move(streamer), + std::move(remarkEmittingPolicy), &errMsg))) { llvm::report_fatal_error( llvm::Twine("Failed to initialize remark engine. Error: ") + errMsg); } @@ -316,3 +334,12 @@ llvm::LogicalResult mlir::remark::enableOptimizationRemarks( return success(); } + +//===----------------------------------------------------------------------===// +// Remark emitting policies +//===----------------------------------------------------------------------===// + +namespace mlir::remark { +RemarkEmittingPolicyAll::RemarkEmittingPolicyAll() = default; +RemarkEmittingPolicyFinal::RemarkEmittingPolicyFinal() = default; +} // namespace mlir::remark diff --git a/mlir/lib/Interfaces/CMakeLists.txt b/mlir/lib/Interfaces/CMakeLists.txt index 388de1c..f96af02 100644 --- a/mlir/lib/Interfaces/CMakeLists.txt +++ b/mlir/lib/Interfaces/CMakeLists.txt @@ -9,6 +9,7 @@ set(LLVM_OPTIONAL_SOURCES FunctionInterfaces.cpp IndexingMapOpInterface.cpp InferIntRangeInterface.cpp + InferStridedMetadataInterface.cpp InferTypeOpInterface.cpp LoopLikeInterface.cpp MemOpInterfaces.cpp @@ -64,6 +65,21 @@ add_mlir_library(MLIRFunctionInterfaces add_mlir_interface_library(IndexingMapOpInterface) add_mlir_interface_library(InferIntRangeInterface) + +add_mlir_library(MLIRInferStridedMetadataInterface + InferStridedMetadataInterface.cpp + + ADDITIONAL_HEADER_DIRS + ${MLIR_MAIN_INCLUDE_DIR}/mlir/Interfaces + + DEPENDS + MLIRInferStridedMetadataInterfaceIncGen + + LINK_LIBS PUBLIC + MLIRInferIntRangeInterface + MLIRIR +) + add_mlir_interface_library(InferTypeOpInterface) add_mlir_library(MLIRLoopLikeInterface diff --git a/mlir/lib/Interfaces/InferIntRangeInterface.cpp b/mlir/lib/Interfaces/InferIntRangeInterface.cpp index 9f3e97d..84fc9b8 100644 --- a/mlir/lib/Interfaces/InferIntRangeInterface.cpp +++ b/mlir/lib/Interfaces/InferIntRangeInterface.cpp @@ -146,6 +146,25 @@ raw_ostream &mlir::operator<<(raw_ostream &os, const IntegerValueRange &range) { return os; } +SmallVector<IntegerValueRange> +mlir::getIntValueRanges(ArrayRef<OpFoldResult> values, + GetIntRangeFn getIntRange, int32_t indexBitwidth) { + SmallVector<IntegerValueRange> ranges; + ranges.reserve(values.size()); + for (OpFoldResult ofr : values) { + if (auto value = dyn_cast<Value>(ofr)) { + ranges.push_back(getIntRange(value)); + continue; + } + + // Create a constant range. + auto attr = cast<IntegerAttr>(cast<Attribute>(ofr)); + ranges.emplace_back(ConstantIntRanges::constant( + attr.getValue().sextOrTrunc(indexBitwidth))); + } + return ranges; +} + void mlir::intrange::detail::defaultInferResultRanges( InferIntRangeInterface interface, ArrayRef<IntegerValueRange> argRanges, SetIntLatticeFn setResultRanges) { diff --git a/mlir/lib/Interfaces/InferStridedMetadataInterface.cpp b/mlir/lib/Interfaces/InferStridedMetadataInterface.cpp new file mode 100644 index 0000000..483e9f1 --- /dev/null +++ b/mlir/lib/Interfaces/InferStridedMetadataInterface.cpp @@ -0,0 +1,36 @@ +//===- InferStridedMetadataInterface.cpp - Strided md inference interface -===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// + +#include "mlir/Interfaces/InferStridedMetadataInterface.h" +#include "mlir/IR/BuiltinTypes.h" +#include "mlir/IR/TypeUtilities.h" +#include <optional> + +using namespace mlir; + +#include "mlir/Interfaces/InferStridedMetadataInterface.cpp.inc" + +void StridedMetadataRange::print(raw_ostream &os) const { + if (isUninitialized()) { + os << "strided_metadata<None>"; + return; + } + os << "strided_metadata<offset = ["; + llvm::interleaveComma(*offsets, os, [&](const ConstantIntRanges &range) { + os << "{" << range << "}"; + }); + os << "], sizes = ["; + llvm::interleaveComma(sizes, os, [&](const ConstantIntRanges &range) { + os << "{" << range << "}"; + }); + os << "], strides = ["; + llvm::interleaveComma(strides, os, [&](const ConstantIntRanges &range) { + os << "{" << range << "}"; + }); + os << "]>"; +} diff --git a/mlir/lib/Remark/RemarkStreamer.cpp b/mlir/lib/Remark/RemarkStreamer.cpp index d213a1a..bf36286 100644 --- a/mlir/lib/Remark/RemarkStreamer.cpp +++ b/mlir/lib/Remark/RemarkStreamer.cpp @@ -60,6 +60,7 @@ void LLVMRemarkStreamer::finalize() { namespace mlir::remark { LogicalResult enableOptimizationRemarksWithLLVMStreamer( MLIRContext &ctx, StringRef path, llvm::remarks::Format fmt, + std::unique_ptr<detail::RemarkEmittingPolicyBase> remarkEmittingPolicy, const RemarkCategories &cat, bool printAsEmitRemarks) { FailureOr<std::unique_ptr<detail::MLIRRemarkStreamerBase>> sOr = @@ -67,7 +68,8 @@ LogicalResult enableOptimizationRemarksWithLLVMStreamer( if (failed(sOr)) return failure(); - return remark::enableOptimizationRemarks(ctx, std::move(*sOr), cat, + return remark::enableOptimizationRemarks(ctx, std::move(*sOr), + std::move(remarkEmittingPolicy), cat, printAsEmitRemarks); } diff --git a/mlir/lib/Target/LLVMIR/DebugImporter.cpp b/mlir/lib/Target/LLVMIR/DebugImporter.cpp index 4bbcd8e..db39c70 100644 --- a/mlir/lib/Target/LLVMIR/DebugImporter.cpp +++ b/mlir/lib/Target/LLVMIR/DebugImporter.cpp @@ -34,11 +34,9 @@ Location DebugImporter::translateFuncLocation(llvm::Function *func) { return UnknownLoc::get(context); // Add a fused location to link the subprogram information. - StringAttr funcName = StringAttr::get(context, subprogram->getName()); StringAttr fileName = StringAttr::get(context, subprogram->getFilename()); return FusedLocWith<DISubprogramAttr>::get( - {NameLoc::get(funcName), - FileLineColLoc::get(fileName, subprogram->getLine(), /*column=*/0)}, + {FileLineColLoc::get(fileName, subprogram->getLine(), /*column=*/0)}, translate(subprogram), context); } diff --git a/mlir/lib/Target/Wasm/TranslateFromWasm.cpp b/mlir/lib/Target/Wasm/TranslateFromWasm.cpp index 132be4e..51c6077 100644 --- a/mlir/lib/Target/Wasm/TranslateFromWasm.cpp +++ b/mlir/lib/Target/Wasm/TranslateFromWasm.cpp @@ -956,7 +956,7 @@ inline parsed_inst_t ExpressionParser::buildNumericOp( << ", type = " << ty << " ***"; auto tysToPop = SmallVector<Type, numOperands>(); tysToPop.resize(numOperands); - std::fill(tysToPop.begin(), tysToPop.end(), ty); + llvm::fill(tysToPop, ty); auto operands = popOperands(tysToPop); if (failed(operands)) return failure(); diff --git a/mlir/lib/Tools/mlir-opt/MlirOptMain.cpp b/mlir/lib/Tools/mlir-opt/MlirOptMain.cpp index 30fd384..9ef405d 100644 --- a/mlir/lib/Tools/mlir-opt/MlirOptMain.cpp +++ b/mlir/lib/Tools/mlir-opt/MlirOptMain.cpp @@ -37,6 +37,7 @@ #include "llvm/ADT/StringRef.h" #include "llvm/Remarks/RemarkFormat.h" #include "llvm/Support/CommandLine.h" +#include "llvm/Support/Debug.h" #include "llvm/Support/InitLLVM.h" #include "llvm/Support/LogicalResult.h" #include "llvm/Support/ManagedStatic.h" @@ -226,6 +227,18 @@ struct MlirOptMainConfigCLOptions : public MlirOptMainConfig { "bitstream", "Print bitstream file")), llvm::cl::cat(remarkCategory)}; + static llvm::cl::opt<RemarkPolicy, /*ExternalStorage=*/true> remarkPolicy{ + "remark-policy", + llvm::cl::desc("Specify the policy for remark output."), + cl::location(remarkPolicyFlag), + llvm::cl::value_desc("format"), + llvm::cl::init(RemarkPolicy::REMARK_POLICY_ALL), + llvm::cl::values(clEnumValN(RemarkPolicy::REMARK_POLICY_ALL, "all", + "Print all remarks"), + clEnumValN(RemarkPolicy::REMARK_POLICY_FINAL, "final", + "Print final remarks")), + llvm::cl::cat(remarkCategory)}; + static cl::opt<std::string, /*ExternalStorage=*/true> remarksAll( "remarks-filter", cl::desc("Show all remarks: passed, missed, failed, analysis"), @@ -517,18 +530,28 @@ performActions(raw_ostream &os, return failure(); context->enableMultithreading(wasThreadingEnabled); - + // Set the remark categories and policy. remark::RemarkCategories cats{ config.getRemarksAllFilter(), config.getRemarksPassedFilter(), config.getRemarksMissedFilter(), config.getRemarksAnalyseFilter(), config.getRemarksFailedFilter()}; mlir::MLIRContext &ctx = *context; + // Helper to create the appropriate policy based on configuration + auto createPolicy = [&config]() + -> std::unique_ptr<mlir::remark::detail::RemarkEmittingPolicyBase> { + if (config.getRemarkPolicy() == RemarkPolicy::REMARK_POLICY_ALL) + return std::make_unique<mlir::remark::RemarkEmittingPolicyAll>(); + if (config.getRemarkPolicy() == RemarkPolicy::REMARK_POLICY_FINAL) + return std::make_unique<mlir::remark::RemarkEmittingPolicyFinal>(); + + llvm_unreachable("Invalid remark policy"); + }; switch (config.getRemarkFormat()) { case RemarkFormat::REMARK_FORMAT_STDOUT: if (failed(mlir::remark::enableOptimizationRemarks( - ctx, nullptr, cats, true /*printAsEmitRemarks*/))) + ctx, nullptr, createPolicy(), cats, true /*printAsEmitRemarks*/))) return failure(); break; @@ -537,7 +560,7 @@ performActions(raw_ostream &os, ? "mlir-remarks.yaml" : config.getRemarksOutputFile(); if (failed(mlir::remark::enableOptimizationRemarksWithLLVMStreamer( - ctx, file, llvm::remarks::Format::YAML, cats))) + ctx, file, llvm::remarks::Format::YAML, createPolicy(), cats))) return failure(); break; } @@ -547,7 +570,7 @@ performActions(raw_ostream &os, ? "mlir-remarks.bitstream" : config.getRemarksOutputFile(); if (failed(mlir::remark::enableOptimizationRemarksWithLLVMStreamer( - ctx, file, llvm::remarks::Format::Bitstream, cats))) + ctx, file, llvm::remarks::Format::Bitstream, createPolicy(), cats))) return failure(); break; } @@ -593,6 +616,12 @@ performActions(raw_ostream &os, AsmState asmState(op.get(), OpPrintingFlags(), /*locationMap=*/nullptr, &fallbackResourceMap); os << OpWithState(op.get(), asmState) << '\n'; + + // This is required if the remark policy is final. Otherwise, the remarks are + // not emitted. + if (remark::detail::RemarkEngine *engine = ctx.getRemarkEngine()) + engine->getRemarkEmittingPolicy()->finalize(); + return success(); } diff --git a/mlir/lib/Transforms/Utils/LoopInvariantCodeMotionUtils.cpp b/mlir/lib/Transforms/Utils/LoopInvariantCodeMotionUtils.cpp index 111f58e..5f3b04a 100644 --- a/mlir/lib/Transforms/Utils/LoopInvariantCodeMotionUtils.cpp +++ b/mlir/lib/Transforms/Utils/LoopInvariantCodeMotionUtils.cpp @@ -66,7 +66,9 @@ size_t mlir::moveLoopInvariantCode( size_t numMoved = 0; for (Region *region : regions) { - LDBG() << "Original loop:\n" << *region->getParentOp(); + LDBG() << "Original loop:\n" + << OpWithFlags(region->getParentOp(), + OpPrintingFlags().skipRegions()); std::queue<Operation *> worklist; // Add top-level operations in the loop body to the worklist. @@ -90,7 +92,8 @@ size_t mlir::moveLoopInvariantCode( !canBeHoisted(op, definedOutside)) continue; - LDBG() << "Moving loop-invariant op: " << *op; + LDBG() << "Moving loop-invariant op: " + << OpWithFlags(op, OpPrintingFlags().skipRegions()); moveOutOfRegion(op, region); ++numMoved; @@ -111,9 +114,7 @@ size_t mlir::moveLoopInvariantCode(LoopLikeOpInterface loopLike) { [&](Value value, Region *) { return loopLike.isDefinedOutsideOfLoop(value); }, - [&](Operation *op, Region *) { - return isMemoryEffectFree(op) && isSpeculatable(op); - }, + [&](Operation *op, Region *) { return isPure(op); }, [&](Operation *op, Region *) { loopLike.moveOutOfLoop(op); }); } diff --git a/mlir/test/Analysis/DataFlow/test-strided-metadata-range-analysis.mlir b/mlir/test/Analysis/DataFlow/test-strided-metadata-range-analysis.mlir new file mode 100644 index 0000000..808c1c2 --- /dev/null +++ b/mlir/test/Analysis/DataFlow/test-strided-metadata-range-analysis.mlir @@ -0,0 +1,67 @@ +// RUN: mlir-opt -test-strided-metadata-range-analysis %s 2>&1 | FileCheck %s + +func.func @memref_subview(%arg0: memref<8x16x4xf32, strided<[64, 4, 1]>>, %arg1: memref<1x128x1x32x1xf32, strided<[4096, 32, 32, 1, 1]>>, %arg2: memref<8x16x4xf32, strided<[1, 64, 8], offset: 16>>, %arg3: index, %arg4: index, %arg5: index) { + %c0 = arith.constant 0 : index + %c1 = arith.constant 1 : index + %c2 = arith.constant 2 : index + %0 = test.with_bounds {smax = 13 : index, smin = 11 : index, umax = 13 : index, umin = 11 : index} : index + %1 = test.with_bounds {smax = 7 : index, smin = 5 : index, umax = 7 : index, umin = 5 : index} : index + + // Test subview with unknown sizes, and constant offsets and strides. + // CHECK: Op: %[[SV0:.*]] = memref.subview + // CHECK-NEXT: result[0]: strided_metadata< + // CHECK-SAME: offset = [{unsigned : [1, 1] signed : [1, 1]}] + // CHECK-SAME: sizes = [{unsigned : [0, 18446744073709551615] signed : [-9223372036854775808, 9223372036854775807]}, {unsigned : [0, 18446744073709551615] signed : [-9223372036854775808, 9223372036854775807]}, {unsigned : [0, 18446744073709551615] signed : [-9223372036854775808, 9223372036854775807]}] + // CHECK-SAME: strides = [{unsigned : [64, 64] signed : [64, 64]}, {unsigned : [4, 4] signed : [4, 4]}, {unsigned : [1, 1] signed : [1, 1]}] + %subview = memref.subview %arg0[%c0, %c0, %c1] [%arg3, %arg4, %arg5] [%c1, %c1, %c1] : memref<8x16x4xf32, strided<[64, 4, 1]>> to memref<?x?x?xf32, strided<[?, ?, ?], offset: ?>> + + // Test a subview of a subview, with bounded dynamic offsets. + // CHECK: Op: %[[SV1:.*]] = memref.subview + // CHECK-NEXT: result[0]: strided_metadata< + // CHECK-SAME: offset = [{unsigned : [346, 484] signed : [346, 484]}] + // CHECK-SAME: sizes = [{unsigned : [2, 2] signed : [2, 2]}, {unsigned : [2, 2] signed : [2, 2]}, {unsigned : [2, 2] signed : [2, 2]}] + // CHECK-SAME: strides = [{unsigned : [704, 832] signed : [704, 832]}, {unsigned : [44, 52] signed : [44, 52]}, {unsigned : [11, 13] signed : [11, 13]}] + %subview_0 = memref.subview %subview[%1, %1, %1] [%c2, %c2, %c2] [%0, %0, %0] : memref<?x?x?xf32, strided<[?, ?, ?], offset: ?>> to memref<?x?x?xf32, strided<[?, ?, ?], offset: ?>> + + // Test a subview of a subview, with constant operands. + // CHECK: Op: %[[SV2:.*]] = memref.subview + // CHECK-NEXT: result[0]: strided_metadata< + // CHECK-SAME: offset = [{unsigned : [368, 510] signed : [368, 510]}] + // CHECK-SAME: sizes = [{unsigned : [2, 2] signed : [2, 2]}, {unsigned : [2, 2] signed : [2, 2]}, {unsigned : [2, 2] signed : [2, 2]}] + // CHECK-SAME: strides = [{unsigned : [704, 832] signed : [704, 832]}, {unsigned : [44, 52] signed : [44, 52]}, {unsigned : [11, 13] signed : [11, 13]}] + %subview_1 = memref.subview %subview_0[%c0, %c0, %c2] [%c2, %c2, %c2] [%c1, %c1, %c1] : memref<?x?x?xf32, strided<[?, ?, ?], offset: ?>> to memref<?x?x?xf32, strided<[?, ?, ?], offset: ?>> + + // Test a rank-reducing subview. + // CHECK: Op: %[[SV3:.*]] = memref.subview + // CHECK-NEXT: result[0]: strided_metadata< + // CHECK-SAME: offset = [{unsigned : [0, 18446744073709551615] signed : [-9223372036854775808, 9223372036854775807]}] + // CHECK-SAME: sizes = [{unsigned : [64, 64] signed : [64, 64]}, {unsigned : [16, 16] signed : [16, 16]}] + // CHECK-SAME: strides = [{unsigned : [0, 18446744073709551615] signed : [-9223372036854775808, 9223372036854775807]}, {unsigned : [0, 18446744073709551615] signed : [-9223372036854775808, 9223372036854775807]}] + %subview_2 = memref.subview %arg1[%arg4, %arg4, %arg4, %arg4, %arg4] [1, 64, 1, 16, 1] [%arg5, %arg5, %arg5, %arg5, %arg5] : memref<1x128x1x32x1xf32, strided<[4096, 32, 32, 1, 1]>> to memref<64x16xf32, strided<[?, ?], offset: ?>> + + // Test a subview of a rank-reducing subview + // CHECK: Op: %[[SV4:.*]] = memref.subview + // CHECK-NEXT: result[0]: strided_metadata< + // CHECK-SAME: offset = [{unsigned : [0, 18446744073709551615] signed : [-9223372036854775808, 9223372036854775807]}] + // CHECK-SAME: sizes = [{unsigned : [5, 7] signed : [5, 7]}] + // CHECK-SAME: strides = [{unsigned : [0, 18446744073709551615] signed : [-9223372036854775808, 9223372036854775807]}] + %subview_3 = memref.subview %subview_2[%c0, %0] [1, %1] [%c1, %c2] : memref<64x16xf32, strided<[?, ?], offset: ?>> to memref<?xf32, strided<[?], offset: ?>> + + // Test a subview with mixed bounded and unbound dynamic sizes. + // CHECK: Op: %[[SV5:.*]] = memref.subview + // CHECK-NEXT: result[0]: strided_metadata< + // CHECK-SAME: offset = [{unsigned : [32, 32] signed : [32, 32]}] + // CHECK-SAME: sizes = [{unsigned : [11, 13] signed : [11, 13]}, {unsigned : [5, 7] signed : [5, 7]}, {unsigned : [0, 18446744073709551615] signed : [-9223372036854775808, 9223372036854775807]}] + // CHECK-SAME: strides = [{unsigned : [1, 1] signed : [1, 1]}, {unsigned : [64, 64] signed : [64, 64]}, {unsigned : [8, 8] signed : [8, 8]}] + %subview_4 = memref.subview %arg2[%c0, %c0, %c2] [%0, %1, %arg5] [%c1, %c1, %c1] : memref<8x16x4xf32, strided<[1, 64, 8], offset: 16>> to memref<?x?x?xf32, strided<[?, ?, ?], offset: ?>> + return +} + +// CHECK: func.func @memref_subview +// CHECK: %[[A0:.*]]: memref<8x16x4xf32, strided<[64, 4, 1]>> +// CHECK: %[[SV0]] = memref.subview %[[A0]] +// CHECK-NEXT: %[[SV1]] = memref.subview +// CHECK-NEXT: %[[SV2]] = memref.subview +// CHECK-NEXT: %[[SV3]] = memref.subview +// CHECK-NEXT: %[[SV4]] = memref.subview +// CHECK-NEXT: %[[SV5]] = memref.subview diff --git a/mlir/test/Conversion/MathToXeVM/lit.local.cfg b/mlir/test/Conversion/MathToXeVM/lit.local.cfg new file mode 100644 index 0000000..cc1ce35 --- /dev/null +++ b/mlir/test/Conversion/MathToXeVM/lit.local.cfg @@ -0,0 +1,7 @@ +spirv_backend_tests = [ + 'native-spirv-builtins.mlir', +] + +# Exclude SPIRV backend tests if SPIRV target is disabled: +if(not config.run_xevm_tests): + config.excludes.update(spirv_backend_tests) diff --git a/mlir/test/Conversion/MathToXeVM/math-to-xevm.mlir b/mlir/test/Conversion/MathToXeVM/math-to-xevm.mlir new file mode 100644 index 0000000..d76627b --- /dev/null +++ b/mlir/test/Conversion/MathToXeVM/math-to-xevm.mlir @@ -0,0 +1,155 @@ +// RUN: mlir-opt %s -convert-math-to-xevm \ +// RUN: | FileCheck %s -check-prefixes='CHECK,CHECK-ARITH' +// RUN: mlir-opt %s -convert-math-to-xevm='convert-arith=false' \ +// RUN: | FileCheck %s -check-prefixes='CHECK,CHECK-NO-ARITH' + +module @test_module { + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expDh(f16) -> f16 + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expf(f32) -> f32 + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expd(f64) -> f64 + // + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expDv2_d(vector<2xf64>) -> vector<2xf64> + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expDv3_d(vector<3xf64>) -> vector<3xf64> + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expDv4_d(vector<4xf64>) -> vector<4xf64> + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expDv8_d(vector<8xf64>) -> vector<8xf64> + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expDv16_d(vector<16xf64>) -> vector<16xf64> + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expDv16_f(vector<16xf32>) -> vector<16xf32> + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_expDv4_Dh(vector<4xf16>) -> vector<4xf16> + // + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_cosDh(f16) -> f16 + // CHECK-DAG: llvm.func @_Z23__spirv_ocl_native_exp2f(f32) -> f32 + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_logDh(f16) -> f16 + // CHECK-DAG: llvm.func @_Z23__spirv_ocl_native_log2f(f32) -> f32 + // CHECK-DAG: llvm.func @_Z24__spirv_ocl_native_log10d(f64) -> f64 + // CHECK-DAG: llvm.func @_Z23__spirv_ocl_native_powrDhDh(f16, f16) -> f16 + // CHECK-DAG: llvm.func @_Z24__spirv_ocl_native_rsqrtd(f64) -> f64 + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_sinDh(f16) -> f16 + // CHECK-DAG: llvm.func @_Z23__spirv_ocl_native_sqrtf(f32) -> f32 + // CHECK-DAG: llvm.func @_Z22__spirv_ocl_native_tand(f64) -> f64 + // CHECK-ARITH-DAG: llvm.func @_Z25__spirv_ocl_native_divideff(f32, f32) -> f32 + + // CHECK-LABEL: func @math_ops + func.func @math_ops() { + + %c1_f16 = arith.constant 1. : f16 + %c1_f32 = arith.constant 1. : f32 + %c1_f64 = arith.constant 1. : f64 + + // CHECK: math.exp + %exp_normal_f16 = math.exp %c1_f16 : f16 + // CHECK: math.exp + %exp_normal_f32 = math.exp %c1_f32 : f32 + // CHECK: math.exp + %exp_normal_f64 = math.exp %c1_f64 : f64 + + // Check float operations are converted properly: + + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDh(%{{.*}}) {fastmathFlags = #llvm.fastmath<fast>} : (f16) -> f16 + %exp_fast_f16 = math.exp %c1_f16 fastmath<fast> : f16 + // CHECK: llvm.call @_Z22__spirv_ocl_native_expf(%{{.*}}) {fastmathFlags = #llvm.fastmath<fast>} : (f32) -> f32 + %exp_fast_f32 = math.exp %c1_f32 fastmath<fast> : f32 + // CHECK: llvm.call @_Z22__spirv_ocl_native_expd(%{{.*}}) {fastmathFlags = #llvm.fastmath<fast>} : (f64) -> f64 + %exp_fast_f64 = math.exp %c1_f64 fastmath<fast> : f64 + + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDh(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f16) -> f16 + %exp_afn_f16 = math.exp %c1_f16 fastmath<afn> : f16 + // CHECK: llvm.call @_Z22__spirv_ocl_native_expf(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f32) -> f32 + %exp_afn_f32 = math.exp %c1_f32 fastmath<afn> : f32 + // CHECK: llvm.call @_Z22__spirv_ocl_native_expd(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f64) -> f64 + %exp_afn_f64 = math.exp %c1_f64 fastmath<afn> : f64 + + // CHECK: math.exp + %exp_none_f16 = math.exp %c1_f16 fastmath<none> : f16 + // CHECK: math.exp + %exp_none_f32 = math.exp %c1_f32 fastmath<none> : f32 + // CHECK: math.exp + %exp_none_f64 = math.exp %c1_f64 fastmath<none> : f64 + + // Check vector operations: + + %v2_c1_f64 = arith.constant dense<1.> : vector<2xf64> + %v3_c1_f64 = arith.constant dense<1.> : vector<3xf64> + %v4_c1_f64 = arith.constant dense<1.> : vector<4xf64> + %v8_c1_f64 = arith.constant dense<1.> : vector<8xf64> + %v16_c1_f64 = arith.constant dense<1.> : vector<16xf64> + + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDv2_d(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (vector<2xf64>) -> vector<2xf64> + %exp_v2_f64 = math.exp %v2_c1_f64 fastmath<afn> : vector<2xf64> + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDv3_d(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (vector<3xf64>) -> vector<3xf64> + %exp_v3_f64 = math.exp %v3_c1_f64 fastmath<afn> : vector<3xf64> + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDv4_d(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (vector<4xf64>) -> vector<4xf64> + %exp_v4_f64 = math.exp %v4_c1_f64 fastmath<afn> : vector<4xf64> + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDv8_d(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (vector<8xf64>) -> vector<8xf64> + %exp_v8_f64 = math.exp %v8_c1_f64 fastmath<afn> : vector<8xf64> + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDv16_d(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (vector<16xf64>) -> vector<16xf64> + %exp_v16_f64 = math.exp %v16_c1_f64 fastmath<afn> : vector<16xf64> + + %v16_c1_f32 = arith.constant dense<1.> : vector<16xf32> + %v4_c1_f16 = arith.constant dense<1.> : vector<4xf16> + + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDv16_f(%{{.*}}) {fastmathFlags = #llvm.fastmath<fast>} : (vector<16xf32>) -> vector<16xf32> + %exp_v16_f32 = math.exp %v16_c1_f32 fastmath<fast> : vector<16xf32> + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDv4_Dh(%{{.*}}) {fastmathFlags = #llvm.fastmath<fast>} : (vector<4xf16>) -> vector<4xf16> + %exp_v4_f16 = math.exp %v4_c1_f16 fastmath<fast> : vector<4xf16> + + // Check unsupported vector sizes are not converted: + + %v5_c1_f64 = arith.constant dense<1.> : vector<5xf64> + %v32_c1_f64 = arith.constant dense<1.> : vector<32xf64> + + // CHECK: math.exp + %exp_v5_f64 = math.exp %v5_c1_f64 fastmath<afn> : vector<5xf64> + // CHECK: math.exp + %exp_v32_f64 = math.exp %v32_c1_f64 fastmath<afn> : vector<32xf64> + + // Check fastmath flags propagate properly: + + // CHECK: llvm.call @_Z22__spirv_ocl_native_expDh(%{{.*}}) {fastmathFlags = #llvm.fastmath<fast>} : (f16) -> f16 + %exp_fastmath_all_f16 = math.exp %c1_f16 fastmath<reassoc,nnan,ninf,nsz,arcp,contract,afn> : f16 + // CHECK: llvm.call @_Z22__spirv_ocl_native_expf(%{{.*}}) {fastmathFlags = #llvm.fastmath<nnan, ninf, nsz, arcp, contract, afn>} : (f32) -> f32 + %exp_fastmath_most_f32 = math.exp %c1_f32 fastmath<nnan,ninf,nsz,arcp,contract,afn> : f32 + // CHECK: llvm.call @_Z22__spirv_ocl_native_expf(%{{.*}}) {fastmathFlags = #llvm.fastmath<nnan, afn, reassoc>} : (f32) -> f32 + %exp_afn_reassoc_nnan_f32 = math.exp %c1_f32 fastmath<afn,reassoc,nnan> : f32 + + // Check all other math operations: + + // CHECK: llvm.call @_Z22__spirv_ocl_native_cosDh(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f16) -> f16 + %cos_afn_f16 = math.cos %c1_f16 fastmath<afn> : f16 + + // CHECK: llvm.call @_Z23__spirv_ocl_native_exp2f(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f32) -> f32 + %exp2_afn_f32 = math.exp2 %c1_f32 fastmath<afn> : f32 + + // CHECK: llvm.call @_Z22__spirv_ocl_native_logDh(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f16) -> f16 + %log_afn_f16 = math.log %c1_f16 fastmath<afn> : f16 + + // CHECK: llvm.call @_Z23__spirv_ocl_native_log2f(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f32) -> f32 + %log2_afn_f32 = math.log2 %c1_f32 fastmath<afn> : f32 + + // CHECK: llvm.call @_Z24__spirv_ocl_native_log10d(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f64) -> f64 + %log10_afn_f64 = math.log10 %c1_f64 fastmath<afn> : f64 + + // CHECK: llvm.call @_Z23__spirv_ocl_native_powrDhDh(%{{.*}}, %{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f16, f16) -> f16 + %powr_afn_f16 = math.powf %c1_f16, %c1_f16 fastmath<afn> : f16 + + // CHECK: llvm.call @_Z24__spirv_ocl_native_rsqrtd(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f64) -> f64 + %rsqrt_afn_f64 = math.rsqrt %c1_f64 fastmath<afn> : f64 + + // CHECK: llvm.call @_Z22__spirv_ocl_native_sinDh(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f16) -> f16 + %sin_afn_f16 = math.sin %c1_f16 fastmath<afn> : f16 + + // CHECK: llvm.call @_Z23__spirv_ocl_native_sqrtf(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f32) -> f32 + %sqrt_afn_f32 = math.sqrt %c1_f32 fastmath<afn> : f32 + + // CHECK: llvm.call @_Z22__spirv_ocl_native_tand(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f64) -> f64 + %tan_afn_f64 = math.tan %c1_f64 fastmath<afn> : f64 + + %c6_9_f32 = arith.constant 6.9 : f32 + %c7_f32 = arith.constant 7. : f32 + + // CHECK-ARITH: llvm.call @_Z25__spirv_ocl_native_divideff(%{{.*}}) {fastmathFlags = #llvm.fastmath<afn>} : (f32, f32) -> f32 + // CHECK-NO-ARITH: arith.divf + %divf_afn_f32 = arith.divf %c6_9_f32, %c7_f32 fastmath<afn> : f32 + + return + } +} diff --git a/mlir/test/Conversion/MathToXeVM/native-spirv-builtins.mlir b/mlir/test/Conversion/MathToXeVM/native-spirv-builtins.mlir new file mode 100644 index 0000000..82426c4 --- /dev/null +++ b/mlir/test/Conversion/MathToXeVM/native-spirv-builtins.mlir @@ -0,0 +1,119 @@ +// RUN: mlir-opt %s -gpu-module-to-binary="format=isa" \ +// RUN: -debug-only=serialize-to-isa 2> %t +// RUN: FileCheck --input-file=%t %s +// REQUIRES: asserts +// +// MathToXeVM pass generates OpenCL intrinsics function calls when converting +// Math ops with `fastmath` attr to native function calls. It is assumed that +// the SPIRV backend would correctly convert these intrinsics calls to OpenCL +// ExtInst instructions in SPIRV (See llvm/lib/Target/SPIRV/SPIRVBuiltins.cpp). +// +// To ensure this assumption holds, this test verifies that the SPIRV backend +// behaves as expected. + +module @test_ocl_intrinsics attributes {gpu.container_module} { + gpu.module @kernel [#xevm.target] { + llvm.func spir_kernelcc @native_fcns() attributes {gpu.kernel} { + // CHECK-DAG: %[[F16T:.+]] = OpTypeFloat 16 + // CHECK-DAG: %[[ZERO_F16:.+]] = OpConstantNull %[[F16T]] + %c0_f16 = llvm.mlir.constant(0. : f16) : f16 + // CHECK-DAG: %[[F32T:.+]] = OpTypeFloat 32 + // CHECK-DAG: %[[ZERO_F32:.+]] = OpConstantNull %[[F32T]] + %c0_f32 = llvm.mlir.constant(0. : f32) : f32 + // CHECK-DAG: %[[F64T:.+]] = OpTypeFloat 64 + // CHECK-DAG: %[[ZERO_F64:.+]] = OpConstantNull %[[F64T]] + %c0_f64 = llvm.mlir.constant(0. : f64) : f64 + + // CHECK-DAG: %[[V2F64T:.+]] = OpTypeVector %[[F64T]] 2 + // CHECK-DAG: %[[V2_ZERO_F64:.+]] = OpConstantNull %[[V2F64T]] + %v2_c0_f64 = llvm.mlir.constant(dense<0.> : vector<2xf64>) : vector<2xf64> + // CHECK-DAG: %[[V3F32T:.+]] = OpTypeVector %[[F32T]] 3 + // CHECK-DAG: %[[V3_ZERO_F32:.+]] = OpConstantNull %[[V3F32T]] + %v3_c0_f32 = llvm.mlir.constant(dense<0.> : vector<3xf32>) : vector<3xf32> + // CHECK-DAG: %[[V4F64T:.+]] = OpTypeVector %[[F64T]] 4 + // CHECK-DAG: %[[V4_ZERO_F64:.+]] = OpConstantNull %[[V4F64T]] + %v4_c0_f64 = llvm.mlir.constant(dense<0.> : vector<4xf64>) : vector<4xf64> + // CHECK-DAG: %[[V8F64T:.+]] = OpTypeVector %[[F64T]] 8 + // CHECK-DAG: %[[V8_ZERO_F64:.+]] = OpConstantNull %[[V8F64T]] + %v8_c0_f64 = llvm.mlir.constant(dense<0.> : vector<8xf64>) : vector<8xf64> + // CHECK-DAG: %[[V16F16T:.+]] = OpTypeVector %[[F16T]] 16 + // CHECK-DAG: %[[V16_ZERO_F16:.+]] = OpConstantNull %[[V16F16T]] + %v16_c0_f16 = llvm.mlir.constant(dense<0.> : vector<16xf16>) : vector<16xf16> + + // CHECK: OpExtInst %[[F16T]] %{{.+}} native_exp %[[ZERO_F16]] + %exp_f16 = llvm.call @_Z22__spirv_ocl_native_expDh(%c0_f16) : (f16) -> f16 + // CHECK: OpExtInst %[[F32T]] %{{.+}} native_exp %[[ZERO_F32]] + %exp_f32 = llvm.call @_Z22__spirv_ocl_native_expf(%c0_f32) : (f32) -> f32 + // CHECK: OpExtInst %[[F64T]] %{{.+}} native_exp %[[ZERO_F64]] + %exp_f64 = llvm.call @_Z22__spirv_ocl_native_expd(%c0_f64) : (f64) -> f64 + + // CHECK: OpExtInst %[[V2F64T]] %{{.+}} native_exp %[[V2_ZERO_F64]] + %exp_v2_f64 = llvm.call @_Z22__spirv_ocl_native_expDv2_f64(%v2_c0_f64) : (vector<2xf64>) -> vector<2xf64> + // CHECK: OpExtInst %[[V3F32T]] %{{.+}} native_exp %[[V3_ZERO_F32]] + %exp_v3_f32 = llvm.call @_Z22__spirv_ocl_native_expDv3_f32(%v3_c0_f32) : (vector<3xf32>) -> vector<3xf32> + // CHECK: OpExtInst %[[V4F64T]] %{{.+}} native_exp %[[V4_ZERO_F64]] + %exp_v4_f64 = llvm.call @_Z22__spirv_ocl_native_expDv4_f64(%v4_c0_f64) : (vector<4xf64>) -> vector<4xf64> + // CHECK: OpExtInst %[[V8F64T]] %{{.+}} native_exp %[[V8_ZERO_F64]] + %exp_v8_f64 = llvm.call @_Z22__spirv_ocl_native_expDv8_f64(%v8_c0_f64) : (vector<8xf64>) -> vector<8xf64> + // CHECK: OpExtInst %[[V16F16T]] %{{.+}} native_exp %[[V16_ZERO_F16]] + %exp_v16_f16 = llvm.call @_Z22__spirv_ocl_native_expDv16_f16(%v16_c0_f16) : (vector<16xf16>) -> vector<16xf16> + + // SPIRV backend does not currently handle fastmath flags: The SPIRV + // backend would need to generate OpDecorate calls to decorate math ops + // with FPFastMathMode/FPFastMathModeINTEL decorations. + // + // FIXME: When support for fastmath flags in the SPIRV backend is added, + // add tests here to ensure fastmath flags are converted to the correct + // OpDecorate calls. + // + // See: + // - https://registry.khronos.org/SPIR-V/specs/unified1/OpenCL.ExtendedInstructionSet.100.html#_math_extended_instructions + // - https://registry.khronos.org/SPIR-V/specs/unified1/SPIRV.html#OpDecorate + + // CHECK: OpExtInst %[[F16T]] %{{.+}} native_cos %[[ZERO_F16]] + %cos_afn_f16 = llvm.call @_Z22__spirv_ocl_native_cosDh(%c0_f16) {fastmathFlags = #llvm.fastmath<afn>} : (f16) -> f16 + // CHECK: OpExtInst %[[F32T]] %{{.+}} native_exp2 %[[ZERO_F32]] + %exp2_afn_f32 = llvm.call @_Z23__spirv_ocl_native_exp2f(%c0_f32) {fastmathFlags = #llvm.fastmath<afn>} : (f32) -> f32 + // CHECK: OpExtInst %[[F16T]] %{{.+}} native_log %[[ZERO_F16]] + %log_afn_f16 = llvm.call @_Z22__spirv_ocl_native_logDh(%c0_f16) {fastmathFlags = #llvm.fastmath<afn>} : (f16) -> f16 + // CHECK: OpExtInst %[[F32T]] %{{.+}} native_log2 %[[ZERO_F32]] + %log2_afn_f32 = llvm.call @_Z23__spirv_ocl_native_log2f(%c0_f32) {fastmathFlags = #llvm.fastmath<afn>} : (f32) -> f32 + // CHECK: OpExtInst %[[V8F64T]] %{{.+}} native_log10 %[[V8_ZERO_F64]] + %log10_afn_f64 = llvm.call @_Z24__spirv_ocl_native_log10Dv8_d(%v8_c0_f64) {fastmathFlags = #llvm.fastmath<afn>} : (vector<8xf64>) -> vector<8xf64> + // CHECK: OpExtInst %[[V16F16T]] %{{.+}} native_powr %[[V16_ZERO_F16]] %[[V16_ZERO_F16]] + %powr_afn_f16 = llvm.call @_Z23__spirv_ocl_native_powrDv16_DhS_(%v16_c0_f16, %v16_c0_f16) {fastmathFlags = #llvm.fastmath<afn>} : (vector<16xf16>, vector<16xf16>) -> vector<16xf16> + // CHECK: OpExtInst %[[F64T]] %{{.+}} native_rsqrt %[[ZERO_F64]] + %rsqrt_afn_f64 = llvm.call @_Z24__spirv_ocl_native_rsqrtd(%c0_f64) {fastmathFlags = #llvm.fastmath<afn>} : (f64) -> f64 + // CHECK: OpExtInst %[[F16T]] %{{.+}} native_sin %[[ZERO_F16]] + %sin_afn_f16 = llvm.call @_Z22__spirv_ocl_native_sinDh(%c0_f16) {fastmathFlags = #llvm.fastmath<afn>} : (f16) -> f16 + // CHECK: OpExtInst %[[F32T]] %{{.+}} native_sqrt %[[ZERO_F32]] + %sqrt_afn_f32 = llvm.call @_Z23__spirv_ocl_native_sqrtf(%c0_f32) {fastmathFlags = #llvm.fastmath<afn>} : (f32) -> f32 + // CHECK: OpExtInst %[[F64T]] %{{.+}} native_tan %[[ZERO_F64]] + %tan_afn_f64 = llvm.call @_Z22__spirv_ocl_native_tand(%c0_f64) {fastmathFlags = #llvm.fastmath<afn>} : (f64) -> f64 + // CHECK: OpExtInst %[[F32T]] %{{.+}} native_divide %[[ZERO_F32]] %[[ZERO_F32]] + %divide_afn_f32 = llvm.call @_Z25__spirv_ocl_native_divideff(%c0_f32, %c0_f32) {fastmathFlags = #llvm.fastmath<afn>} : (f32, f32) -> f32 + + llvm.return + } + + llvm.func @_Z22__spirv_ocl_native_expDh(f16) -> f16 + llvm.func @_Z22__spirv_ocl_native_expf(f32) -> f32 + llvm.func @_Z22__spirv_ocl_native_expd(f64) -> f64 + llvm.func @_Z22__spirv_ocl_native_expDv2_f64(vector<2xf64>) -> vector<2xf64> + llvm.func @_Z22__spirv_ocl_native_expDv3_f32(vector<3xf32>) -> vector<3xf32> + llvm.func @_Z22__spirv_ocl_native_expDv4_f64(vector<4xf64>) -> vector<4xf64> + llvm.func @_Z22__spirv_ocl_native_expDv8_f64(vector<8xf64>) -> vector<8xf64> + llvm.func @_Z22__spirv_ocl_native_expDv16_f16(vector<16xf16>) -> vector<16xf16> + llvm.func @_Z22__spirv_ocl_native_cosDh(f16) -> f16 + llvm.func @_Z23__spirv_ocl_native_exp2f(f32) -> f32 + llvm.func @_Z22__spirv_ocl_native_logDh(f16) -> f16 + llvm.func @_Z23__spirv_ocl_native_log2f(f32) -> f32 + llvm.func @_Z24__spirv_ocl_native_log10Dv8_d(vector<8xf64>) -> vector<8xf64> + llvm.func @_Z23__spirv_ocl_native_powrDv16_DhS_(vector<16xf16>, vector<16xf16>) -> vector<16xf16> + llvm.func @_Z24__spirv_ocl_native_rsqrtd(f64) -> f64 + llvm.func @_Z22__spirv_ocl_native_sinDh(f16) -> f16 + llvm.func @_Z23__spirv_ocl_native_sqrtf(f32) -> f32 + llvm.func @_Z22__spirv_ocl_native_tand(f64) -> f64 + llvm.func @_Z25__spirv_ocl_native_divideff(f32, f32) -> f32 + } +} diff --git a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir index a7a73ae..780c25a 100644 --- a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir +++ b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir @@ -1538,6 +1538,92 @@ func.func @unsupportedRescaleInexactRound(%arg0 : tensor<2xi8>) -> (tensor<2xi8> // ----- +// CHECK: #[[$MAP0:.+]] = affine_map<(d0) -> (d0)> +// CHECK: #[[$MAP1:.+]] = affine_map<(d0) -> ()> +// CHECK-LABEL: @rescale_no_const +// CHECK-SAME: ([[ARG0:%[0-9a-zA-Z_]*]] +func.func @rescale_no_const(%arg0 : tensor<2xi8>, %multiplier : tensor<1xi32>, %shift : tensor<1xi8>, %input_zp : tensor<1xi8>, %output_zp : tensor<1xi8>) -> (tensor<2xi8>) { + // CHECK: [[MULTIPLIER:%.+]] = tensor.collapse_shape %arg1 [] : tensor<1xi32> into tensor<i32> + // CHECK: [[SHIFT:%.+]] = tensor.collapse_shape %arg2 [] : tensor<1xi8> into tensor<i8> + // CHECK: [[INPUT_ZP:%.+]] = tensor.collapse_shape %arg3 [] : tensor<1xi8> into tensor<i8> + // CHECK: [[OUTPUT_ZP:%.+]] = tensor.collapse_shape %arg4 [] : tensor<1xi8> into tensor<i8> + // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<2xi8> + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]], #[[$MAP1]], #[[$MAP1]], #[[$MAP0]]], iterator_types = ["parallel"]} ins([[ARG0]], [[MULTIPLIER]], [[SHIFT]], [[INPUT_ZP]], [[OUTPUT_ZP]] : tensor<2xi8>, tensor<i32>, tensor<i8>, tensor<i8>, tensor<i8>) outs([[INIT]] : tensor<2xi8>) { + // CHECK: ^bb0([[ARG0:%.*]]: i8, [[ARG1:%.*]]: i32, [[ARG2:%.*]]: i8, [[ARG3:%.*]]: i8, [[ARG4:%.*]]: i8, [[OUT:%.*]]: i8): + // CHECK: [[INPUT_ZP_I32:%.+]] = arith.extsi [[ARG3]] : i8 to i32 + // CHECK: [[OUTPUT_ZP_I32:%.+]] = arith.extsi [[ARG4]] : i8 to i32 + // CHECK: [[ARG0_I32:%.+]] = arith.extsi [[ARG0]] : i8 to i32 + // CHECK: [[TMP1:%.+]] = arith.subi [[ARG0_I32]], [[INPUT_ZP_I32]] : i32 + // CHECK: [[TMP2:%.+]] = tosa.apply_scale [[TMP1]], [[ARG1]], [[ARG2]] {rounding_mode = DOUBLE_ROUND} : (i32, i32, i8) -> i32 + // CHECK: [[TMP3:%.+]] = arith.addi [[TMP2]], [[OUTPUT_ZP_I32]] : i32 + // CHECK: %c-128_i32 = arith.constant -128 : i32 + // CHECK: %c127_i32 = arith.constant 127 : i32 + // CHECK: [[MAX:%.+]] = arith.maxsi %c-128_i32, [[TMP3]] : i32 + // CHECK: [[MIN:%.+]] = arith.minsi %c127_i32, [[MAX]] : i32 + %0 = tosa.rescale %arg0, %multiplier, %shift, %input_zp, %output_zp {scale32 = true, rounding_mode = DOUBLE_ROUND, per_channel = false, input_unsigned = false, output_unsigned = false} : (tensor<2xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<2xi8> + return %0 : tensor<2xi8> +} + +// ----- + +// CHECK: #[[$MAP0:.+]] = affine_map<(d0) -> (d0)> +// CHECK: #[[$MAP1:.+]] = affine_map<(d0) -> ()> +// CHECK-LABEL: @rescale_no_const_per_channel +// CHECK-SAME: ([[ARG0:%[0-9a-zA-Z_]*]] +// CHECK-SAME: [[ARG1:%[0-9a-zA-Z_]*]] +// CHECK-SAME: [[ARG2:%[0-9a-zA-Z_]*]] +func.func @rescale_no_const_per_channel(%arg0 : tensor<2xi8>, %arg1 : tensor<2xi32>, %arg2 : tensor<2xi8>, %input_zp : tensor<1xi8>, %output_zp : tensor<1xi8>) -> (tensor<2xi8>) { + // CHECK: [[INPUT_ZP:%.+]] = tensor.collapse_shape %arg3 [] : tensor<1xi8> into tensor<i8> + // CHECK: [[OUTPUT_ZP:%.+]] = tensor.collapse_shape %arg4 [] : tensor<1xi8> into tensor<i8> + // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<2xi8> + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]], #[[$MAP0]], #[[$MAP1]], #[[$MAP1]], #[[$MAP0]]], iterator_types = ["parallel"]} ins([[ARG0]], [[ARG1]], [[ARG2]], [[INPUT_ZP]], [[OUTPUT_ZP]] : tensor<2xi8>, tensor<2xi32>, tensor<2xi8>, tensor<i8>, tensor<i8>) outs([[INIT]] : tensor<2xi8>) { + // CHECK: ^bb0([[ARG0:%.*]]: i8, [[ARG1:%.*]]: i32, [[ARG2:%.*]]: i8, [[ARG3:%.*]]: i8, [[ARG4:%.*]]: i8, [[OUT:%.*]]: i8): + // CHECK: [[INPUT_ZP_I32:%.+]] = arith.extsi [[ARG3]] : i8 to i32 + // CHECK: [[OUTPUT_ZP_I32:%.+]] = arith.extsi [[ARG4]] : i8 to i32 + // CHECK: [[ARG0_I32:%.+]] = arith.extsi [[ARG0]] : i8 to i32 + // CHECK: [[TMP1:%.+]] = arith.subi [[ARG0_I32]], [[INPUT_ZP_I32]] : i32 + // CHECK: [[TMP2:%.+]] = tosa.apply_scale [[TMP1]], [[ARG1]], [[ARG2]] {rounding_mode = DOUBLE_ROUND} : (i32, i32, i8) -> i32 + // CHECK: [[TMP3:%.+]] = arith.addi [[TMP2]], [[OUTPUT_ZP_I32]] : i32 + // CHECK: %c-128_i32 = arith.constant -128 : i32 + // CHECK: %c127_i32 = arith.constant 127 : i32 + // CHECK: [[MAX:%.+]] = arith.maxsi %c-128_i32, [[TMP3]] : i32 + // CHECK: [[MIN:%.+]] = arith.minsi %c127_i32, [[MAX]] : i32 + %0 = tosa.rescale %arg0, %arg1, %arg2, %input_zp, %output_zp {scale32 = true, rounding_mode = DOUBLE_ROUND, per_channel = true, input_unsigned = false, output_unsigned = false} : (tensor<2xi8>, tensor<2xi32>, tensor<2xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<2xi8> + return %0 : tensor<2xi8> +} + +// ----- + +// CHECK: #[[$MAP0:.+]] = affine_map<(d0) -> (d0)> +// CHECK: #[[$MAP1:.+]] = affine_map<(d0) -> ()> +// CHECK-LABEL: @rescale_no_const_per_channel_input_output_zp_ui8 +// CHECK-SAME: ([[ARG0:%[0-9a-zA-Z_]*]] +// CHECK-SAME: [[ARG1:%[0-9a-zA-Z_]*]] +// CHECK-SAME: [[ARG2:%[0-9a-zA-Z_]*]] +func.func @rescale_no_const_per_channel_input_output_zp_ui8(%arg0 : tensor<2xi8>, %arg1 : tensor<2xi32>, %arg2 : tensor<2xi8>, %input_zp : tensor<1xui8>, %output_zp : tensor<1xui8>) -> (tensor<2xui8>) { + // CHECK: [[INPUT_ZP:%.+]] = tensor.collapse_shape %arg3 [] : tensor<1xui8> into tensor<ui8> + // CHECK: [[OUTPUT_ZP:%.+]] = tensor.collapse_shape %arg4 [] : tensor<1xui8> into tensor<ui8> + // CHECK: [[INIT:%.+]] = tensor.empty() : tensor<2xui8> + // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]], #[[$MAP0]], #[[$MAP1]], #[[$MAP1]], #[[$MAP0]]], iterator_types = ["parallel"]} ins([[ARG0]], [[ARG1]], [[ARG2]], [[INPUT_ZP]], [[OUTPUT_ZP]] : tensor<2xi8>, tensor<2xi32>, tensor<2xi8>, tensor<ui8>, tensor<ui8>) outs([[INIT]] : tensor<2xui8>) { + // CHECK: ^bb0([[ARG0:%.*]]: i8, [[ARG1:%.*]]: i32, [[ARG2:%.*]]: i8, [[ARG3:%.*]]: ui8, [[ARG4:%.*]]: ui8, [[OUT:%.*]]: ui8): + // CHECK: [[INPUT_ZP_I8:%.+]] = builtin.unrealized_conversion_cast [[ARG3]] : ui8 to i8 + // CHECK: [[INPUT_ZP_I32:%.+]] = arith.extui [[INPUT_ZP_I8]] : i8 to i32 + // CHECK: [[OUTPUT_ZP_I8:%.+]] = builtin.unrealized_conversion_cast [[ARG4]] : ui8 to i8 + // CHECK: [[OUTPUT_ZP_I32:%.+]] = arith.extui [[OUTPUT_ZP_I8]] : i8 to i32 + // CHECK: [[ARG0_I32:%.+]] = arith.extsi [[ARG0]] : i8 to i32 + // CHECK: [[TMP1:%.+]] = arith.subi [[ARG0_I32]], [[INPUT_ZP_I32]] : i32 + // CHECK: [[TMP2:%.+]] = tosa.apply_scale [[TMP1]], [[ARG1]], [[ARG2]] {rounding_mode = DOUBLE_ROUND} : (i32, i32, i8) -> i32 + // CHECK: [[TMP3:%.+]] = arith.addi [[TMP2]], [[OUTPUT_ZP_I32]] : i32 + // CHECK: %c0_i32 = arith.constant 0 : i32 + // CHECK: %c255_i32 = arith.constant 255 : i32 + // CHECK: [[MAX:%.+]] = arith.maxsi %c0_i32, [[TMP3]] : i32 + // CHECK: [[MIN:%.+]] = arith.minsi %c255_i32, [[MAX]] : i32 + %0 = tosa.rescale %arg0, %arg1, %arg2, %input_zp, %output_zp {scale32 = true, rounding_mode = DOUBLE_ROUND, per_channel = true, input_unsigned = false, output_unsigned = true} : (tensor<2xi8>, tensor<2xi32>, tensor<2xi8>, tensor<1xui8>, tensor<1xui8>) -> tensor<2xui8> + return %0 : tensor<2xui8> +} + +// ----- + // CHECK: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d0, d1)> // CHECK-LABEL: @reverse diff --git a/mlir/test/Dialect/Bufferization/Transforms/one-shot-module-bufferize-allow-return-allocs.mlir b/mlir/test/Dialect/Bufferization/Transforms/one-shot-module-bufferize-allow-return-allocs.mlir index c58b153..21b508e 100644 --- a/mlir/test/Dialect/Bufferization/Transforms/one-shot-module-bufferize-allow-return-allocs.mlir +++ b/mlir/test/Dialect/Bufferization/Transforms/one-shot-module-bufferize-allow-return-allocs.mlir @@ -65,13 +65,13 @@ func.func @main(%t: tensor<?xf32>, %sz: index, %idx: index) -> (f32, f32) { // ----- -func.func @return_arg(%A: tensor<?xf32>) -> tensor<?xf32> { +func.func private @return_arg(%A: tensor<?xf32>) -> tensor<?xf32> { func.return %A : tensor<?xf32> } -// CHECK-LABEL: func @return_arg +// CHECK-LABEL: func private @return_arg // CHECK-SAME: %[[A:.*]]: memref<?xf32 // CHECK-NOT: return %[[A]] -// NO-DROP-LABEL: func @return_arg +// NO-DROP-LABEL: func private @return_arg // NO-DROP-SAME: %[[A:.*]]: memref<?xf32 // NO-DROP: return %[[A]] diff --git a/mlir/test/Dialect/Bufferization/Transforms/one-shot-module-bufferize.mlir b/mlir/test/Dialect/Bufferization/Transforms/one-shot-module-bufferize.mlir index 6054a61..d5f834b 100644 --- a/mlir/test/Dialect/Bufferization/Transforms/one-shot-module-bufferize.mlir +++ b/mlir/test/Dialect/Bufferization/Transforms/one-shot-module-bufferize.mlir @@ -171,9 +171,9 @@ func.func @func_without_tensor_args(%v : vector<10xf32>) -> () { // Bufferization of a function that is reading and writing. %t0 is writable, so // no copy should be inserted. -// CHECK-LABEL: func @inner_func( +// CHECK-LABEL: func private @inner_func( // CHECK-SAME: %[[arg0:.*]]: memref<?xf32 -func.func @inner_func(%t: tensor<?xf32>) -> (tensor<?xf32>, f32) { +func.func private @inner_func(%t: tensor<?xf32>) -> (tensor<?xf32>, f32) { // CHECK-NOT: copy %f = arith.constant 1.0 : f32 %c0 = arith.constant 0 : index @@ -186,9 +186,9 @@ func.func @inner_func(%t: tensor<?xf32>) -> (tensor<?xf32>, f32) { return %0, %1 : tensor<?xf32>, f32 } -// CHECK-LABEL: func @call_func_with_non_tensor_return( +// CHECK-LABEL: func private @call_func_with_non_tensor_return( // CHECK-SAME: %[[arg0:.*]]: memref<?xf32 -func.func @call_func_with_non_tensor_return( +func.func private @call_func_with_non_tensor_return( %t0: tensor<?xf32> {bufferization.writable = true}) -> (f32, tensor<?xf32>) { // CHECK-NOT: alloc // CHECK-NOT: copy @@ -203,9 +203,9 @@ func.func @call_func_with_non_tensor_return( // Bufferization of a function that is reading and writing. %t0 is not writable, // so a copy is needed. -// CHECK-LABEL: func @inner_func( +// CHECK-LABEL: func private @inner_func( // CHECK-SAME: %[[arg0:.*]]: memref<?xf32 -func.func @inner_func(%t: tensor<?xf32>) -> (tensor<?xf32>, f32) { +func.func private @inner_func(%t: tensor<?xf32>) -> (tensor<?xf32>, f32) { // CHECK-NOT: copy %f = arith.constant 1.0 : f32 %c0 = arith.constant 0 : index @@ -276,10 +276,10 @@ func.func @main(%t: tensor<?xf32> {bufferization.writable = false}) -> (f32) { // This function does not read, just write. We need an alloc, but no copy. -// CHECK-LABEL: func @does_not_read( +// CHECK-LABEL: func private @does_not_read( // CHECK-NOT: alloc // CHECK-NOT: copy -func.func @does_not_read(%t: tensor<?xf32>) -> tensor<?xf32> { +func.func private @does_not_read(%t: tensor<?xf32>) -> tensor<?xf32> { %f0 = arith.constant 0.0 : f32 %r = linalg.fill ins(%f0 : f32) outs(%t : tensor<?xf32>) -> tensor<?xf32> return %r : tensor<?xf32> @@ -354,9 +354,9 @@ func.func @main() { // A write inside an scf.execute_region. An equivalent tensor is yielded. -// CHECK-LABEL: func @execute_region_test( +// CHECK-LABEL: func private @execute_region_test( // CHECK-SAME: %[[m1:.*]]: memref<?xf32 -func.func @execute_region_test(%t1 : tensor<?xf32>) +func.func private @execute_region_test(%t1 : tensor<?xf32>) -> (f32, tensor<?xf32>, f32) { %f1 = arith.constant 0.0 : f32 @@ -397,11 +397,11 @@ func.func @no_inline_execute_region_not_canonicalized() { // CHECK: func private @some_external_func(memref<?xf32, strided<[?], offset: ?>>) func.func private @some_external_func(tensor<?xf32>) -// CHECK: func @scf_for_with_tensor_insert_slice( +// CHECK: func private @scf_for_with_tensor_insert_slice( // CHECK-SAME: %[[A:[a-zA-Z0-9]*]]: memref<?xf32, strided<[?], offset: ?>> // CHECK-SAME: %[[B:[a-zA-Z0-9]*]]: memref<?xf32, strided<[?], offset: ?>> // CHECK-SAME: %[[C:[a-zA-Z0-9]*]]: memref<4xf32, strided<[?], offset: ?>> -func.func @scf_for_with_tensor_insert_slice( +func.func private @scf_for_with_tensor_insert_slice( %A : tensor<?xf32>, %B : tensor<?xf32>, %C : tensor<4xf32>, %lb : index, %ub : index, %step : index) -> (tensor<?xf32>, tensor<?xf32>) @@ -456,11 +456,11 @@ func.func @bar( // ----- -// CHECK: func @init_and_dot( +// CHECK: func private @init_and_dot( // CHECK-SAME: %[[A:[a-zA-Z0-9]*]]: memref<64xf32, strided<[?], offset: ?>> // CHECK-SAME: %[[B:[a-zA-Z0-9]*]]: memref<64xf32, strided<[?], offset: ?>> // CHECK-SAME: %[[C:[a-zA-Z0-9]*]]: memref<f32, strided<[], offset: ?>> -func.func @init_and_dot(%a: tensor<64xf32>, %b: tensor<64xf32>, %c: tensor<f32>) -> tensor<f32> { +func.func private @init_and_dot(%a: tensor<64xf32>, %b: tensor<64xf32>, %c: tensor<f32>) -> tensor<f32> { // CHECK-NEXT: %[[C0:.*]] = arith.constant 0{{.*}} : f32 %v0 = arith.constant 0.0 : f32 @@ -574,9 +574,9 @@ func.func @entry(%A : tensor<?xf32> {bufferization.buffer_layout = affine_map<(i // No alloc or copy inside of the loop. -// CHECK-LABEL: func @inner_func( +// CHECK-LABEL: func private @inner_func( // CHECK-SAME: %[[arg0:.*]]: memref<?xf32 -func.func @inner_func(%t: tensor<?xf32>) -> tensor<?xf32> { +func.func private @inner_func(%t: tensor<?xf32>) -> tensor<?xf32> { %f = arith.constant 1.0 : f32 %c0 = arith.constant 0 : index // CHECK: memref.store %{{.*}}, %[[arg0]] diff --git a/mlir/test/Dialect/Linalg/match-ops-interpreter.mlir b/mlir/test/Dialect/Linalg/match-ops-interpreter.mlir index 618ba34..66cae5c 100644 --- a/mlir/test/Dialect/Linalg/match-ops-interpreter.mlir +++ b/mlir/test/Dialect/Linalg/match-ops-interpreter.mlir @@ -1011,6 +1011,20 @@ module attributes { transform.target_tag = "start_here" } { } -> tensor<1x1x4xf32> return } + + func.func @generic_none(%arg0: tensor<128x128xi32>, %arg1: tensor<128x128xi32>, %arg2: tensor<128x128xi32>) { + %0 = linalg.generic { + indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>, + affine_map<(d0, d1, d2) -> (d2, d1)>, + affine_map<(d0, d1, d2) -> (d0, d1)>], + iterator_types = ["parallel", "parallel", "reduction"]} + ins(%arg0, %arg1 : tensor<128x128xi32>, tensor<128x128xi32>) + outs(%arg2 : tensor<128x128xi32>) { + ^bb0(%in: i32, %in_0: i32, %out: i32): + linalg.yield %out : i32 + } -> tensor<128x128xi32> + return + } } // ----- diff --git a/mlir/test/Dialect/Linalg/one-shot-bufferize.mlir b/mlir/test/Dialect/Linalg/one-shot-bufferize.mlir index 9616a3e..1df15e8 100644 --- a/mlir/test/Dialect/Linalg/one-shot-bufferize.mlir +++ b/mlir/test/Dialect/Linalg/one-shot-bufferize.mlir @@ -10,10 +10,10 @@ // TODO: Some test cases from this file should be moved to other dialects. -// CHECK-LABEL: func @fill_inplace( +// CHECK-LABEL: func private @fill_inplace( // CHECK-SAME: %[[A:[a-zA-Z0-9]*]]: memref<?xf32, strided<[?], offset: ?>> -// CHECK-NO-LAYOUT-MAP-LABEL: func @fill_inplace(%{{.*}}: memref<?xf32>) { -func.func @fill_inplace( +// CHECK-NO-LAYOUT-MAP-LABEL: func private @fill_inplace(%{{.*}}: memref<?xf32>) { +func.func private @fill_inplace( %A : tensor<?xf32> {bufferization.writable = true}) -> tensor<?xf32> { @@ -56,10 +56,10 @@ func.func @not_inplace( // ----- -// CHECK-LABEL: func @not_inplace +// CHECK-LABEL: func private @not_inplace // CHECK-SAME: %[[A:[a-zA-Z0-9]*]]: memref<?x?xf32, strided<[?, ?], offset: ?>>) { -// CHECK-NO-LAYOUT-MAP-LABEL: func @not_inplace(%{{.*}}: memref<?x?xf32>) { -func.func @not_inplace( +// CHECK-NO-LAYOUT-MAP-LABEL: func private @not_inplace(%{{.*}}: memref<?x?xf32>) { +func.func private @not_inplace( %A : tensor<?x?xf32> {bufferization.writable = true}) -> tensor<?x?xf32> { @@ -235,7 +235,7 @@ func.func @dominance_violation_bug_1( // ----- -func.func @gather_like( +func.func private @gather_like( %arg0 : tensor<?x?xf32> {bufferization.writable = false}, %arg1 : tensor<?xi32> {bufferization.writable = false}, %arg2 : tensor<?x?xf32> {bufferization.writable = true}) @@ -254,7 +254,7 @@ func.func @gather_like( } -> tensor<?x?xf32> return %0 : tensor<?x?xf32> } -// CHECK-LABEL: func @gather_like( +// CHECK-LABEL: func private @gather_like( // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: memref<?x?xf32, // CHECK-SAME: %[[ARG1:.+]]: memref<?xi32 // CHECK-SAME: %[[ARG2:.+]]: memref<?x?xf32 diff --git a/mlir/test/Dialect/OpenACC/recipe-populate-firstprivate.mlir b/mlir/test/Dialect/OpenACC/recipe-populate-firstprivate.mlir new file mode 100644 index 0000000..35355c6 --- /dev/null +++ b/mlir/test/Dialect/OpenACC/recipe-populate-firstprivate.mlir @@ -0,0 +1,102 @@ +// RUN: mlir-opt %s --split-input-file --pass-pipeline="builtin.module(test-acc-recipe-populate{recipe-type=firstprivate})" | FileCheck %s + +// CHECK: acc.firstprivate.recipe @firstprivate_scalar : memref<f32> init { +// CHECK: ^bb0(%{{.*}}: memref<f32>): +// CHECK: %[[ALLOC:.*]] = memref.alloca() : memref<f32> +// CHECK: acc.yield %[[ALLOC]] : memref<f32> +// CHECK: } copy { +// CHECK: ^bb0(%[[SRC:.*]]: memref<f32>, %[[DST:.*]]: memref<f32>): +// CHECK: memref.copy %[[SRC]], %[[DST]] : memref<f32> to memref<f32> +// CHECK: acc.terminator +// CHECK: } +// CHECK-NOT: destroy + +func.func @test_scalar() { + %0 = memref.alloca() {test.var = "scalar"} : memref<f32> + return +} + +// ----- + +// CHECK: acc.firstprivate.recipe @firstprivate_static_2d : memref<10x20xf32> init { +// CHECK: ^bb0(%{{.*}}: memref<10x20xf32>): +// CHECK: %[[ALLOC:.*]] = memref.alloca() : memref<10x20xf32> +// CHECK: acc.yield %[[ALLOC]] : memref<10x20xf32> +// CHECK: } copy { +// CHECK: ^bb0(%[[SRC:.*]]: memref<10x20xf32>, %[[DST:.*]]: memref<10x20xf32>): +// CHECK: memref.copy %[[SRC]], %[[DST]] : memref<10x20xf32> to memref<10x20xf32> +// CHECK: acc.terminator +// CHECK: } +// CHECK-NOT: destroy + +func.func @test_static_2d() { + %0 = memref.alloca() {test.var = "static_2d"} : memref<10x20xf32> + return +} + +// ----- + +// CHECK: acc.firstprivate.recipe @firstprivate_dynamic_2d : memref<?x?xf32> init { +// CHECK: ^bb0(%[[ARG:.*]]: memref<?x?xf32>): +// CHECK: %[[C0:.*]] = arith.constant 0 : index +// CHECK: %[[DIM0:.*]] = memref.dim %[[ARG]], %[[C0]] : memref<?x?xf32> +// CHECK: %[[C1:.*]] = arith.constant 1 : index +// CHECK: %[[DIM1:.*]] = memref.dim %[[ARG]], %[[C1]] : memref<?x?xf32> +// CHECK: %[[ALLOC:.*]] = memref.alloc(%[[DIM0]], %[[DIM1]]) : memref<?x?xf32> +// CHECK: acc.yield %[[ALLOC]] : memref<?x?xf32> +// CHECK: } copy { +// CHECK: ^bb0(%[[SRC:.*]]: memref<?x?xf32>, %[[DST:.*]]: memref<?x?xf32>): +// CHECK: memref.copy %[[SRC]], %[[DST]] : memref<?x?xf32> to memref<?x?xf32> +// CHECK: acc.terminator +// CHECK: } destroy { +// CHECK: ^bb0(%{{.*}}: memref<?x?xf32>, %[[VAL:.*]]: memref<?x?xf32>): +// CHECK: memref.dealloc %[[VAL]] : memref<?x?xf32> +// CHECK: acc.terminator +// CHECK: } + +func.func @test_dynamic_2d(%arg0: index, %arg1: index) { + %0 = memref.alloc(%arg0, %arg1) {test.var = "dynamic_2d"} : memref<?x?xf32> + return +} + +// ----- + +// CHECK: acc.firstprivate.recipe @firstprivate_mixed_dims : memref<10x?xf32> init { +// CHECK: ^bb0(%[[ARG:.*]]: memref<10x?xf32>): +// CHECK: %[[C1:.*]] = arith.constant 1 : index +// CHECK: %[[DIM1:.*]] = memref.dim %[[ARG]], %[[C1]] : memref<10x?xf32> +// CHECK: %[[ALLOC:.*]] = memref.alloc(%[[DIM1]]) : memref<10x?xf32> +// CHECK: acc.yield %[[ALLOC]] : memref<10x?xf32> +// CHECK: } copy { +// CHECK: ^bb0(%[[SRC:.*]]: memref<10x?xf32>, %[[DST:.*]]: memref<10x?xf32>): +// CHECK: memref.copy %[[SRC]], %[[DST]] : memref<10x?xf32> to memref<10x?xf32> +// CHECK: acc.terminator +// CHECK: } destroy { +// CHECK: ^bb0(%{{.*}}: memref<10x?xf32>, %[[VAL:.*]]: memref<10x?xf32>): +// CHECK: memref.dealloc %[[VAL]] : memref<10x?xf32> +// CHECK: acc.terminator +// CHECK: } + +func.func @test_mixed_dims(%arg0: index) { + %0 = memref.alloc(%arg0) {test.var = "mixed_dims"} : memref<10x?xf32> + return +} + +// ----- + +// CHECK: acc.firstprivate.recipe @firstprivate_scalar_int : memref<i32> init { +// CHECK: ^bb0(%{{.*}}: memref<i32>): +// CHECK: %[[ALLOC:.*]] = memref.alloca() : memref<i32> +// CHECK: acc.yield %[[ALLOC]] : memref<i32> +// CHECK: } copy { +// CHECK: ^bb0(%[[SRC:.*]]: memref<i32>, %[[DST:.*]]: memref<i32>): +// CHECK: memref.copy %[[SRC]], %[[DST]] : memref<i32> to memref<i32> +// CHECK: acc.terminator +// CHECK: } +// CHECK-NOT: destroy + +func.func @test_scalar_int() { + %0 = memref.alloca() {test.var = "scalar_int"} : memref<i32> + return +} + diff --git a/mlir/test/Dialect/OpenACC/recipe-populate-private.mlir b/mlir/test/Dialect/OpenACC/recipe-populate-private.mlir new file mode 100644 index 0000000..8403ee8 --- /dev/null +++ b/mlir/test/Dialect/OpenACC/recipe-populate-private.mlir @@ -0,0 +1,82 @@ +// RUN: mlir-opt %s --split-input-file --pass-pipeline="builtin.module(test-acc-recipe-populate{recipe-type=private})" | FileCheck %s + +// CHECK: acc.private.recipe @private_scalar : memref<f32> init { +// CHECK: ^bb0(%{{.*}}: memref<f32>): +// CHECK: %[[ALLOC:.*]] = memref.alloca() : memref<f32> +// CHECK: acc.yield %[[ALLOC]] : memref<f32> +// CHECK: } +// CHECK-NOT: destroy + +func.func @test_scalar() { + %0 = memref.alloca() {test.var = "scalar"} : memref<f32> + return +} + +// ----- + +// CHECK: acc.private.recipe @private_static_2d : memref<10x20xf32> init { +// CHECK: ^bb0(%{{.*}}: memref<10x20xf32>): +// CHECK: %[[ALLOC:.*]] = memref.alloca() : memref<10x20xf32> +// CHECK: acc.yield %[[ALLOC]] : memref<10x20xf32> +// CHECK: } +// CHECK-NOT: destroy + +func.func @test_static_2d() { + %0 = memref.alloca() {test.var = "static_2d"} : memref<10x20xf32> + return +} + +// ----- + +// CHECK: acc.private.recipe @private_dynamic_2d : memref<?x?xf32> init { +// CHECK: ^bb0(%[[ARG:.*]]: memref<?x?xf32>): +// CHECK: %[[C0:.*]] = arith.constant 0 : index +// CHECK: %[[DIM0:.*]] = memref.dim %[[ARG]], %[[C0]] : memref<?x?xf32> +// CHECK: %[[C1:.*]] = arith.constant 1 : index +// CHECK: %[[DIM1:.*]] = memref.dim %[[ARG]], %[[C1]] : memref<?x?xf32> +// CHECK: %[[ALLOC:.*]] = memref.alloc(%[[DIM0]], %[[DIM1]]) : memref<?x?xf32> +// CHECK: acc.yield %[[ALLOC]] : memref<?x?xf32> +// CHECK: } destroy { +// CHECK: ^bb0(%{{.*}}: memref<?x?xf32>, %[[VAL:.*]]: memref<?x?xf32>): +// CHECK: memref.dealloc %[[VAL]] : memref<?x?xf32> +// CHECK: acc.terminator +// CHECK: } + +func.func @test_dynamic_2d(%arg0: index, %arg1: index) { + %0 = memref.alloc(%arg0, %arg1) {test.var = "dynamic_2d"} : memref<?x?xf32> + return +} + +// ----- + +// CHECK: acc.private.recipe @private_mixed_dims : memref<10x?xf32> init { +// CHECK: ^bb0(%[[ARG:.*]]: memref<10x?xf32>): +// CHECK: %[[C1:.*]] = arith.constant 1 : index +// CHECK: %[[DIM1:.*]] = memref.dim %[[ARG]], %[[C1]] : memref<10x?xf32> +// CHECK: %[[ALLOC:.*]] = memref.alloc(%[[DIM1]]) : memref<10x?xf32> +// CHECK: acc.yield %[[ALLOC]] : memref<10x?xf32> +// CHECK: } destroy { +// CHECK: ^bb0(%{{.*}}: memref<10x?xf32>, %[[VAL:.*]]: memref<10x?xf32>): +// CHECK: memref.dealloc %[[VAL]] : memref<10x?xf32> +// CHECK: acc.terminator +// CHECK: } + +func.func @test_mixed_dims(%arg0: index) { + %0 = memref.alloc(%arg0) {test.var = "mixed_dims"} : memref<10x?xf32> + return +} + +// ----- + +// CHECK: acc.private.recipe @private_scalar_int : memref<i32> init { +// CHECK: ^bb0(%{{.*}}: memref<i32>): +// CHECK: %[[ALLOC:.*]] = memref.alloca() : memref<i32> +// CHECK: acc.yield %[[ALLOC]] : memref<i32> +// CHECK: } +// CHECK-NOT: destroy + +func.func @test_scalar_int() { + %0 = memref.alloca() {test.var = "scalar_int"} : memref<i32> + return +} + diff --git a/mlir/test/Dialect/SCF/one-shot-bufferize.mlir b/mlir/test/Dialect/SCF/one-shot-bufferize.mlir index a1067ec..af09dc8 100644 --- a/mlir/test/Dialect/SCF/one-shot-bufferize.mlir +++ b/mlir/test/Dialect/SCF/one-shot-bufferize.mlir @@ -8,11 +8,11 @@ // Test bufferization using memref types that have no layout map. // RUN: mlir-opt %s -allow-unregistered-dialect -one-shot-bufferize="allow-return-allocs-from-loops unknown-type-conversion=identity-layout-map function-boundary-type-conversion=identity-layout-map bufferize-function-boundaries" -split-input-file -o /dev/null -// CHECK-LABEL: func @scf_for_yield_only( +// CHECK-LABEL: func private @scf_for_yield_only( // CHECK-SAME: %[[A:[a-zA-Z0-9]*]]: memref<?xf32, strided<[?], offset: ?>>, // CHECK-SAME: %[[t:[a-zA-Z0-9]*]]: memref<?xf32, strided<[?], offset: ?>> // CHECK-SAME: ) -> memref<?xf32> { -func.func @scf_for_yield_only( +func.func private @scf_for_yield_only( %A : tensor<?xf32> {bufferization.writable = false}, %B : tensor<?xf32> {bufferization.writable = true}, %lb : index, %ub : index, %step : index) @@ -85,11 +85,11 @@ func.func @nested_scf_for(%A : tensor<?xf32> {bufferization.writable = true}, // ----- -// CHECK-LABEL: func @scf_for_with_tensor.insert_slice +// CHECK-LABEL: func private @scf_for_with_tensor.insert_slice // CHECK-SAME: %[[A:[a-zA-Z0-9]*]]: memref<?xf32, strided<[?], offset: ?>> // CHECK-SAME: %[[B:[a-zA-Z0-9]*]]: memref<?xf32, strided<[?], offset: ?>> // CHECK-SAME: %[[C:[a-zA-Z0-9]*]]: memref<4xf32, strided<[?], offset: ?>> -func.func @scf_for_with_tensor.insert_slice( +func.func private @scf_for_with_tensor.insert_slice( %A : tensor<?xf32> {bufferization.writable = false}, %B : tensor<?xf32> {bufferization.writable = true}, %C : tensor<4xf32> {bufferization.writable = false}, @@ -471,11 +471,11 @@ func.func @scf_while_iter_arg_result_mismatch(%arg0: tensor<5xi1>, // ----- -// CHECK-LABEL: func.func @parallel_insert_slice_no_conflict( +// CHECK-LABEL: func private @parallel_insert_slice_no_conflict( // CHECK-SAME: %[[idx:.*]]: index, %[[idx2:.*]]: index, // CHECK-SAME: %[[arg1:.*]]: memref<?xf32, strided{{.*}}>, // CHECK-SAME: %[[arg2:.*]]: memref<?xf32, strided{{.*}}> -func.func @parallel_insert_slice_no_conflict( +func.func private @parallel_insert_slice_no_conflict( %idx: index, %idx2: index, %arg1: tensor<?xf32> {bufferization.writable = true}, diff --git a/mlir/test/Dialect/Tensor/one-shot-bufferize.mlir b/mlir/test/Dialect/Tensor/one-shot-bufferize.mlir index 5f95da2..b6c72be 100644 --- a/mlir/test/Dialect/Tensor/one-shot-bufferize.mlir +++ b/mlir/test/Dialect/Tensor/one-shot-bufferize.mlir @@ -8,12 +8,12 @@ // Test bufferization using memref types that have no layout map. // RUN: mlir-opt %s -one-shot-bufferize="unknown-type-conversion=identity-layout-map bufferize-function-boundaries" -split-input-file -o /dev/null -// CHECK-LABEL: func @insert_slice_fun +// CHECK-LABEL: func private @insert_slice_fun // CHECK-SAME: %[[A0:[a-zA-Z0-9]*]]: memref<?xf32, strided<[?], offset: ?>>, // CHECK-SAME: %[[A1:[a-zA-Z0-9]*]]: memref<?xf32, strided<[?], offset: ?>>, // CHECK-SAME: %[[t0:[a-zA-Z0-9]*]]: memref<4xf32, strided<[?], offset: ?>>, // CHECK-SAME: %[[t1:[a-zA-Z0-9]*]]: memref<4xf32, strided<[?], offset: ?>> -func.func @insert_slice_fun( +func.func private @insert_slice_fun( %A0 : tensor<?xf32> {bufferization.writable = false}, %A1 : tensor<?xf32> {bufferization.writable = true}, %t0 : tensor<4xf32> {bufferization.writable = false}, @@ -331,12 +331,12 @@ func.func @dim_not_reading(%t: tensor<?xf32>, %f: f32, %pos: index) // ----- // CHECK: #[[$map:.*]] = affine_map<(d0) -> (d0 + 5)> -// CHECK-LABEL: func.func @cast_retains_buffer_layout( +// CHECK-LABEL: func.func private @cast_retains_buffer_layout( // CHECK-SAME: %[[t:.*]]: memref<?xf32, #[[$map]]>, %[[sz:.*]]: index) -> memref<?xf32, strided<[1], offset: 7>> { // CHECK: %[[casted:.*]] = memref.cast %[[t]] : memref<?xf32, #[[$map]]> to memref<10xf32, #[[$map]]> // CHECK: %[[slice:.*]] = memref.subview %[[casted]][2] [%[[sz]]] [1] : memref<10xf32, #[[$map]]> to memref<?xf32, strided<[1], offset: 7>> // CHECK: return %[[slice]] -func.func @cast_retains_buffer_layout( +func.func private @cast_retains_buffer_layout( %t: tensor<?xf32> {bufferization.buffer_layout = affine_map<(d0) -> (d0 + 5)>}, %sz: index) @@ -353,12 +353,12 @@ func.func @cast_retains_buffer_layout( // ----- -// CHECK-LABEL: func.func @cast_retains_buffer_layout_strided( +// CHECK-LABEL: func private @cast_retains_buffer_layout_strided( // CHECK-SAME: %[[t:.*]]: memref<?xf32, strided<[1], offset: 5>>, %[[sz:.*]]: index) -> memref<?xf32, strided<[1], offset: 7>> { // CHECK: %[[casted:.*]] = memref.cast %[[t]] : memref<?xf32, strided<[1], offset: 5>> to memref<10xf32, strided<[1], offset: 5>> // CHECK: %[[slice:.*]] = memref.subview %[[casted]][2] [%[[sz]]] [1] : memref<10xf32, strided<[1], offset: 5>> to memref<?xf32, strided<[1], offset: 7>> // CHECK: return %[[slice]] -func.func @cast_retains_buffer_layout_strided( +func.func private @cast_retains_buffer_layout_strided( %t: tensor<?xf32> {bufferization.buffer_layout = strided<[1], offset: 5>}, %sz: index) diff --git a/mlir/test/Integration/GPU/SPIRV/simple_add.mlir b/mlir/test/Integration/GPU/SPIRV/simple_add.mlir index cb16c37..b3154d4 100644 --- a/mlir/test/Integration/GPU/SPIRV/simple_add.mlir +++ b/mlir/test/Integration/GPU/SPIRV/simple_add.mlir @@ -3,7 +3,16 @@ // RUN: | FileCheck %s // CHECK: data = -// CHECK-RAW: [[[7.7, 0, 0], [7.7, 0, 0], [7.7, 0, 0]], [[0, 7.7, 0], [0, 7.7, 0], [0, 7.7, 0]], [[0, 0, 7.7], [0, 0, 7.7], [0, 0, 7.7]]] +// CHECK{LITERAL}: [[[7.7, 0, 0], +// CHECK{LITERAL}: [7.7, 0, 0], +// CHECK{LITERAL}: [7.7, 0, 0]], +// CHECK{LITERAL}: [[0, 7.7, 0], +// CHECK{LITERAL}: [0, 7.7, 0], +// CHECK{LITERAL}: [0, 7.7, 0]], +// CHECK{LITERAL}: [[0, 0, 7.7], +// CHECK{LITERAL}: [0, 0, 7.7], +// CHECK{LITERAL}: [0, 0, 7.7]]] + module attributes { gpu.container_module, spirv.target_env = #spirv.target_env< diff --git a/mlir/test/Pass/remark-final.mlir b/mlir/test/Pass/remark-final.mlir new file mode 100644 index 0000000..325271e --- /dev/null +++ b/mlir/test/Pass/remark-final.mlir @@ -0,0 +1,17 @@ +// RUN: mlir-opt %s --test-remark --remarks-filter="category.*" --remark-policy=final 2>&1 | FileCheck %s +// RUN: mlir-opt %s --test-remark --remarks-filter="category.*" --remark-policy=final --remark-format=yaml --remarks-output-file=%t.yaml +// RUN: FileCheck --check-prefix=CHECK-YAML %s < %t.yaml +module @foo { + "test.op"() : () -> () + +} + +// CHECK-YAML-NOT: This is a test passed remark (should be dropped) +// CHECK-YAML-DAG: !Analysis +// CHECK-YAML-DAG: !Failure +// CHECK-YAML-DAG: !Passed + +// CHECK-NOT: This is a test passed remark (should be dropped) +// CHECK-DAG: remark: [Analysis] test-remark +// CHECK-DAG: remark: [Failure] test-remark | Category:category-2-failed +// CHECK-DAG: remark: [Passed] test-remark | Category:category-1-passed diff --git a/mlir/test/Target/LLVMIR/Import/debug-info.ll b/mlir/test/Target/LLVMIR/Import/debug-info.ll index e056e43..61376b8 100644 --- a/mlir/test/Target/LLVMIR/Import/debug-info.ll +++ b/mlir/test/Target/LLVMIR/Import/debug-info.ll @@ -240,11 +240,10 @@ define void @subprogram() !dbg !3 { define void @func_loc() !dbg !3 { ret void } -; CHECK-DAG: #[[NAME_LOC:.+]] = loc("func_loc") ; CHECK-DAG: #[[FILE_LOC:.+]] = loc("debug-info.ll":42:0) ; CHECK-DAG: #[[SP:.+]] = #llvm.di_subprogram<id = distinct[{{.*}}]<>, compileUnit = #{{.*}}, scope = #{{.*}}, name = "func_loc", file = #{{.*}}, line = 42, subprogramFlags = Definition> -; CHECK: loc(fused<#[[SP]]>[#[[NAME_LOC]], #[[FILE_LOC]]] +; CHECK: loc(fused<#[[SP]]>[#[[FILE_LOC]]] !llvm.dbg.cu = !{!1} !llvm.module.flags = !{!0} diff --git a/mlir/test/Target/LLVMIR/nvvm/convert_fp4x2.mlir b/mlir/test/Target/LLVMIR/nvvm/convert_fp4x2.mlir new file mode 100644 index 0000000..04e2ddf --- /dev/null +++ b/mlir/test/Target/LLVMIR/nvvm/convert_fp4x2.mlir @@ -0,0 +1,12 @@ +// RUN: mlir-translate -mlir-to-llvmir %s | FileCheck %s + +// CHECK-LABEL: @convert_f32x2_to_f4x2_e2m1 +llvm.func @convert_f32x2_to_f4x2_e2m1(%srcA : f32, %srcB : f32) { + // CHECK: %[[res1:.*]] = call i16 @llvm.nvvm.ff.to.e2m1x2.rn.satfinite(float %{{.*}}, float %{{.*}}) + // CHECK-NEXT: %{{.*}} = trunc i16 %[[res1]] to i8 + %res1 = nvvm.convert.f32x2.to.f4x2 %srcA, %srcB : i8 (f4E2M1FN) + // CHECK: %[[res2:.*]] = call i16 @llvm.nvvm.ff.to.e2m1x2.rn.relu.satfinite(float %{{.*}}, float %{{.*}}) + // CHECK-NEXT: %{{.*}} = trunc i16 %[[res2]] to i8 + %res2 = nvvm.convert.f32x2.to.f4x2 %srcA, %srcB {relu = true} : i8 (f4E2M1FN) + llvm.return +} diff --git a/mlir/test/Target/LLVMIR/nvvmir-invalid.mlir b/mlir/test/Target/LLVMIR/nvvmir-invalid.mlir index 0b36154..78e1e659 100644 --- a/mlir/test/Target/LLVMIR/nvvmir-invalid.mlir +++ b/mlir/test/Target/LLVMIR/nvvmir-invalid.mlir @@ -254,6 +254,14 @@ llvm.func @nvvm_cvt_f32x2_to_f6x2_invalid_type(%a : f32, %b : f32) { // ----- +llvm.func @nvvm_cvt_f32x2_to_f4x2_invalid_type(%a : f32, %b : f32) { + // expected-error @below {{Only 'f4E2M1FN' type is supported for conversions from f32x2 to f4x2.}} + %res = nvvm.convert.f32x2.to.f4x2 %a, %b : i8 (f8E4M3FN) + llvm.return +} + +// ----- + llvm.func @nvvm_prefetch_L1_with_evict_priority(%global_ptr: !llvm.ptr<1>) { // expected-error @below {{cache eviction priority supported only for cache level L2}} nvvm.prefetch level = L1, evict_priority = evict_last, %global_ptr : !llvm.ptr<1> diff --git a/mlir/test/lib/Analysis/CMakeLists.txt b/mlir/test/lib/Analysis/CMakeLists.txt index 9187998..c37671a 100644 --- a/mlir/test/lib/Analysis/CMakeLists.txt +++ b/mlir/test/lib/Analysis/CMakeLists.txt @@ -17,6 +17,7 @@ add_mlir_library(MLIRTestAnalysis DataFlow/TestDenseForwardDataFlowAnalysis.cpp DataFlow/TestLivenessAnalysis.cpp DataFlow/TestSparseBackwardDataFlowAnalysis.cpp + DataFlow/TestStridedMetadataRangeAnalysis.cpp EXCLUDE_FROM_LIBMLIR diff --git a/mlir/test/lib/Analysis/DataFlow/TestStridedMetadataRangeAnalysis.cpp b/mlir/test/lib/Analysis/DataFlow/TestStridedMetadataRangeAnalysis.cpp new file mode 100644 index 0000000..6ac09fd --- /dev/null +++ b/mlir/test/lib/Analysis/DataFlow/TestStridedMetadataRangeAnalysis.cpp @@ -0,0 +1,86 @@ +//===- TestStridedMetadataRangeAnalysis.cpp - Test strided md analysis ----===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// + +#include "mlir/Analysis/DataFlow/ConstantPropagationAnalysis.h" +#include "mlir/Analysis/DataFlow/DeadCodeAnalysis.h" +#include "mlir/Analysis/DataFlow/IntegerRangeAnalysis.h" +#include "mlir/Analysis/DataFlow/StridedMetadataRangeAnalysis.h" +#include "mlir/Analysis/DataFlowFramework.h" +#include "mlir/IR/BuiltinAttributes.h" +#include "mlir/IR/Operation.h" +#include "mlir/Pass/Pass.h" +#include "mlir/Pass/PassRegistry.h" +#include "llvm/ADT/STLExtras.h" +#include "llvm/Support/raw_ostream.h" + +using namespace mlir; +using namespace mlir::dataflow; + +static void printAnalysisResults(DataFlowSolver &solver, Operation *op, + raw_ostream &os) { + // Collect the strided metadata of the op results. + SmallVector<std::pair<unsigned, const StridedMetadataRangeLattice *>> results; + for (OpResult result : op->getResults()) { + const auto *state = solver.lookupState<StridedMetadataRangeLattice>(result); + // Skip the result if it's uninitialized. + if (!state || state->getValue().isUninitialized()) + continue; + + // Skip the result if the range is empty. + const mlir::StridedMetadataRange &md = state->getValue(); + if (md.getOffsets().empty() && md.getSizes().empty() && + md.getStrides().empty()) + continue; + results.push_back({result.getResultNumber(), state}); + } + + // Early exit if there's no metadata to print. + if (results.empty()) + return; + + // Print the metadata. + os << "Op: " << OpWithFlags(op, OpPrintingFlags().skipRegions()) << "\n"; + for (auto [idx, state] : results) + os << " result[" << idx << "]: " << state->getValue() << "\n"; + os << "\n"; +} + +namespace { +struct TestStridedMetadataRangeAnalysisPass + : public PassWrapper<TestStridedMetadataRangeAnalysisPass, + OperationPass<>> { + MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID( + TestStridedMetadataRangeAnalysisPass) + + StringRef getArgument() const override { + return "test-strided-metadata-range-analysis"; + } + void runOnOperation() override { + Operation *op = getOperation(); + + DataFlowSolver solver; + solver.load<DeadCodeAnalysis>(); + solver.load<SparseConstantPropagation>(); + solver.load<IntegerRangeAnalysis>(); + solver.load<StridedMetadataRangeAnalysis>(); + if (failed(solver.initializeAndRun(op))) + return signalPassFailure(); + + op->walk( + [&](Operation *op) { printAnalysisResults(solver, op, llvm::errs()); }); + } +}; +} // end anonymous namespace + +namespace mlir { +namespace test { +void registerTestStridedMetadataRangeAnalysisPass() { + PassRegistration<TestStridedMetadataRangeAnalysisPass>(); +} +} // end namespace test +} // end namespace mlir diff --git a/mlir/test/lib/Dialect/OpenACC/CMakeLists.txt b/mlir/test/lib/Dialect/OpenACC/CMakeLists.txt index f84055d..1e59338 100644 --- a/mlir/test/lib/Dialect/OpenACC/CMakeLists.txt +++ b/mlir/test/lib/Dialect/OpenACC/CMakeLists.txt @@ -1,6 +1,7 @@ add_mlir_library(MLIROpenACCTestPasses TestOpenACC.cpp TestPointerLikeTypeInterface.cpp + TestRecipePopulate.cpp EXCLUDE_FROM_LIBMLIR ) diff --git a/mlir/test/lib/Dialect/OpenACC/TestOpenACC.cpp b/mlir/test/lib/Dialect/OpenACC/TestOpenACC.cpp index 9886240..bea21b9 100644 --- a/mlir/test/lib/Dialect/OpenACC/TestOpenACC.cpp +++ b/mlir/test/lib/Dialect/OpenACC/TestOpenACC.cpp @@ -15,9 +15,13 @@ namespace test { // Forward declarations of individual test pass registration functions void registerTestPointerLikeTypeInterfacePass(); +void registerTestRecipePopulatePass(); // Unified registration function for all OpenACC tests -void registerTestOpenACC() { registerTestPointerLikeTypeInterfacePass(); } +void registerTestOpenACC() { + registerTestPointerLikeTypeInterfacePass(); + registerTestRecipePopulatePass(); +} } // namespace test } // namespace mlir diff --git a/mlir/test/lib/Dialect/OpenACC/TestPointerLikeTypeInterface.cpp b/mlir/test/lib/Dialect/OpenACC/TestPointerLikeTypeInterface.cpp index 85f9283..027b0a1 100644 --- a/mlir/test/lib/Dialect/OpenACC/TestPointerLikeTypeInterface.cpp +++ b/mlir/test/lib/Dialect/OpenACC/TestPointerLikeTypeInterface.cpp @@ -196,13 +196,15 @@ void TestPointerLikeTypeInterfacePass::testGenAllocate( newBuilder.setInsertionPointAfter(op); // Call the genAllocate API + bool needsFree = false; Value allocRes = pointerType.genAllocate(newBuilder, loc, "test_alloc", - result.getType(), result); + result.getType(), result, needsFree); if (allocRes) { llvm::errs() << "Successfully generated alloc for operation: "; op->print(llvm::errs()); llvm::errs() << "\n"; + llvm::errs() << "\tneeds free: " << (needsFree ? "true" : "false") << "\n"; // Print all operations that were inserted for (Operation *insertedOp : tracker.insertedOps) { @@ -230,8 +232,8 @@ void TestPointerLikeTypeInterfacePass::testGenFree(Operation *op, Value result, // Call the genFree API auto typedResult = cast<TypedValue<PointerLikeType>>(result); - bool success = - pointerType.genFree(newBuilder, loc, typedResult, result.getType()); + bool success = pointerType.genFree(newBuilder, loc, typedResult, result, + result.getType()); if (success) { llvm::errs() << "Successfully generated free for operation: "; diff --git a/mlir/test/lib/Dialect/OpenACC/TestRecipePopulate.cpp b/mlir/test/lib/Dialect/OpenACC/TestRecipePopulate.cpp new file mode 100644 index 0000000..35f092c --- /dev/null +++ b/mlir/test/lib/Dialect/OpenACC/TestRecipePopulate.cpp @@ -0,0 +1,110 @@ +//===- TestRecipePopulate.cpp - Test Recipe Population -------------------===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// +// +// This file contains test passes for testing the createAndPopulate methods +// of the recipe operations. +// +//===----------------------------------------------------------------------===// + +#include "mlir/Dialect/Arith/IR/Arith.h" +#include "mlir/Dialect/Func/IR/FuncOps.h" +#include "mlir/Dialect/MemRef/IR/MemRef.h" +#include "mlir/Dialect/OpenACC/OpenACC.h" +#include "mlir/IR/Builders.h" +#include "mlir/Pass/Pass.h" +#include "llvm/Support/CommandLine.h" + +using namespace mlir; +using namespace mlir::acc; + +namespace { + +struct TestRecipePopulatePass + : public PassWrapper<TestRecipePopulatePass, OperationPass<ModuleOp>> { + MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestRecipePopulatePass) + + TestRecipePopulatePass() = default; + TestRecipePopulatePass(const TestRecipePopulatePass &pass) + : PassWrapper(pass) { + recipeType = pass.recipeType; + } + + Pass::Option<std::string> recipeType{ + *this, "recipe-type", + llvm::cl::desc("Recipe type: private or firstprivate"), + llvm::cl::init("private")}; + + StringRef getArgument() const override { return "test-acc-recipe-populate"; } + + StringRef getDescription() const override { + return "Test OpenACC recipe population"; + } + + void runOnOperation() override; + + void getDependentDialects(DialectRegistry ®istry) const override { + registry.insert<acc::OpenACCDialect>(); + registry.insert<arith::ArithDialect>(); + registry.insert<memref::MemRefDialect>(); + } +}; + +void TestRecipePopulatePass::runOnOperation() { + auto module = getOperation(); + OpBuilder builder(&getContext()); + + // Collect all test variables + SmallVector<std::tuple<Operation *, Value, std::string>> testVars; + + module.walk([&](Operation *op) { + if (auto varName = op->getAttrOfType<StringAttr>("test.var")) { + for (auto result : op->getResults()) { + testVars.push_back({op, result, varName.str()}); + } + } + }); + + // Generate recipes at module level + builder.setInsertionPoint(&module.getBodyRegion().front(), + module.getBodyRegion().front().begin()); + + for (auto [op, var, varName] : testVars) { + Location loc = op->getLoc(); + + std::string recipeName = recipeType.getValue() + "_" + varName; + ValueRange bounds; // No bounds for memref tests + + if (recipeType == "private") { + auto recipe = PrivateRecipeOp::createAndPopulate( + builder, loc, recipeName, var.getType(), varName, bounds); + + if (!recipe) { + op->emitError("Failed to create private recipe for ") << varName; + } + } else if (recipeType == "firstprivate") { + auto recipe = FirstprivateRecipeOp::createAndPopulate( + builder, loc, recipeName, var.getType(), varName, bounds); + + if (!recipe) { + op->emitError("Failed to create firstprivate recipe for ") << varName; + } + } + } +} + +} // namespace + +namespace mlir { +namespace test { + +void registerTestRecipePopulatePass() { + PassRegistration<TestRecipePopulatePass>(); +} + +} // namespace test +} // namespace mlir diff --git a/mlir/test/lib/Pass/TestRemarksPass.cpp b/mlir/test/lib/Pass/TestRemarksPass.cpp index 3b25686..5ca2d1a 100644 --- a/mlir/test/lib/Pass/TestRemarksPass.cpp +++ b/mlir/test/lib/Pass/TestRemarksPass.cpp @@ -43,7 +43,12 @@ public: << remark::add("This is a test missed remark") << remark::reason("because we are testing the remark pipeline") << remark::suggest("try using the remark pipeline feature"); - + mlir::remark::passed( + loc, + remark::RemarkOpts::name("test-remark").category("category-1-passed")) + << remark::add("This is a test passed remark (should be dropped)") + << remark::reason("because we are testing the remark pipeline") + << remark::suggest("try using the remark pipeline feature"); mlir::remark::passed( loc, remark::RemarkOpts::name("test-remark").category("category-1-passed")) diff --git a/mlir/tools/mlir-opt/mlir-opt.cpp b/mlir/tools/mlir-opt/mlir-opt.cpp index 6432fae..8842180 100644 --- a/mlir/tools/mlir-opt/mlir-opt.cpp +++ b/mlir/tools/mlir-opt/mlir-opt.cpp @@ -151,6 +151,7 @@ void registerTestSliceAnalysisPass(); void registerTestSPIRVCPURunnerPipeline(); void registerTestSPIRVFuncSignatureConversion(); void registerTestSPIRVVectorUnrolling(); +void registerTestStridedMetadataRangeAnalysisPass(); void registerTestTensorCopyInsertionPass(); void registerTestTensorLikeAndBufferLikePass(); void registerTestTensorTransforms(); @@ -299,6 +300,7 @@ void registerTestPasses() { mlir::test::registerTestSPIRVCPURunnerPipeline(); mlir::test::registerTestSPIRVFuncSignatureConversion(); mlir::test::registerTestSPIRVVectorUnrolling(); + mlir::test::registerTestStridedMetadataRangeAnalysisPass(); mlir::test::registerTestTensorCopyInsertionPass(); mlir::test::registerTestTensorLikeAndBufferLikePass(); mlir::test::registerTestTensorTransforms(); diff --git a/mlir/unittests/IR/RemarkTest.cpp b/mlir/unittests/IR/RemarkTest.cpp index bcbda90..09c576c 100644 --- a/mlir/unittests/IR/RemarkTest.cpp +++ b/mlir/unittests/IR/RemarkTest.cpp @@ -53,10 +53,12 @@ TEST(Remark, TestOutputOptimizationRemark) { /*missed=*/categoryUnroll, /*analysis=*/categoryRegister, /*failed=*/categoryInliner}; - + std::unique_ptr<remark::RemarkEmittingPolicyAll> policy = + std::make_unique<remark::RemarkEmittingPolicyAll>(); LogicalResult isEnabled = mlir::remark::enableOptimizationRemarksWithLLVMStreamer( - context, yamlFile, llvm::remarks::Format::YAML, cats); + context, yamlFile, llvm::remarks::Format::YAML, std::move(policy), + cats); ASSERT_TRUE(succeeded(isEnabled)) << "Failed to enable remark engine"; // PASS: something succeeded @@ -202,9 +204,10 @@ TEST(Remark, TestOutputOptimizationRemarkDiagnostic) { /*missed=*/categoryUnroll, /*analysis=*/categoryRegister, /*failed=*/categoryUnroll}; - - LogicalResult isEnabled = - remark::enableOptimizationRemarks(context, nullptr, cats, true); + std::unique_ptr<remark::RemarkEmittingPolicyAll> policy = + std::make_unique<remark::RemarkEmittingPolicyAll>(); + LogicalResult isEnabled = remark::enableOptimizationRemarks( + context, nullptr, std::move(policy), cats, true); ASSERT_TRUE(succeeded(isEnabled)) << "Failed to enable remark engine"; @@ -282,8 +285,11 @@ TEST(Remark, TestCustomOptimizationRemarkDiagnostic) { /*analysis=*/std::nullopt, /*failed=*/categoryLoopunroll}; + std::unique_ptr<remark::RemarkEmittingPolicyAll> policy = + std::make_unique<remark::RemarkEmittingPolicyAll>(); LogicalResult isEnabled = remark::enableOptimizationRemarks( - context, std::make_unique<MyCustomStreamer>(), cats, true); + context, std::make_unique<MyCustomStreamer>(), std::move(policy), cats, + true); ASSERT_TRUE(succeeded(isEnabled)) << "Failed to enable remark engine"; // Remark 1: pass, category LoopUnroll @@ -311,4 +317,66 @@ TEST(Remark, TestCustomOptimizationRemarkDiagnostic) { EXPECT_NE(errOut.find(pass2Msg), std::string::npos); // printed EXPECT_EQ(errOut.find(pass3Msg), std::string::npos); // filtered out } + +TEST(Remark, TestRemarkFinal) { + testing::internal::CaptureStderr(); + const auto *pass1Msg = "I failed"; + const auto *pass2Msg = "I failed too"; + const auto *pass3Msg = "I succeeded"; + const auto *pass4Msg = "I succeeded too"; + + std::string categoryLoopunroll("LoopUnroll"); + + std::string seenMsg = ""; + + { + MLIRContext context; + Location loc = FileLineColLoc::get(&context, "test.cpp", 1, 5); + Location locOther = FileLineColLoc::get(&context, "test.cpp", 55, 5); + + // Setup the remark engine + mlir::remark::RemarkCategories cats{/*all=*/"", + /*passed=*/categoryLoopunroll, + /*missed=*/categoryLoopunroll, + /*analysis=*/categoryLoopunroll, + /*failed=*/categoryLoopunroll}; + + std::unique_ptr<remark::RemarkEmittingPolicyFinal> policy = + std::make_unique<remark::RemarkEmittingPolicyFinal>(); + LogicalResult isEnabled = remark::enableOptimizationRemarks( + context, std::make_unique<MyCustomStreamer>(), std::move(policy), cats, + true); + ASSERT_TRUE(succeeded(isEnabled)) << "Failed to enable remark engine"; + + // Remark 1: failure + remark::failed( + loc, remark::RemarkOpts::name("Unroller").category(categoryLoopunroll)) + << pass1Msg; + + // Remark 2: failure + remark::missed( + loc, remark::RemarkOpts::name("Unroller").category(categoryLoopunroll)) + << remark::reason(pass2Msg); + + // Remark 3: pass + remark::passed( + loc, remark::RemarkOpts::name("Unroller").category(categoryLoopunroll)) + << pass3Msg; + + // Remark 4: pass + remark::passed( + locOther, + remark::RemarkOpts::name("Unroller").category(categoryLoopunroll)) + << pass4Msg; + } + + llvm::errs().flush(); + std::string errOut = ::testing::internal::GetCapturedStderr(); + + // Containment checks for messages. + EXPECT_EQ(errOut.find(pass1Msg), std::string::npos); // dropped + EXPECT_EQ(errOut.find(pass2Msg), std::string::npos); // dropped + EXPECT_NE(errOut.find(pass3Msg), std::string::npos); // shown + EXPECT_NE(errOut.find(pass4Msg), std::string::npos); // shown +} } // namespace diff --git a/mlir/utils/generate-test-checks.py b/mlir/utils/generate-test-checks.py index f80a181..3712a6b 100755 --- a/mlir/utils/generate-test-checks.py +++ b/mlir/utils/generate-test-checks.py @@ -31,13 +31,16 @@ import argparse import os # Used to advertise this file's name ("autogenerated_note"). import re import sys +from collections import Counter ADVERT_BEGIN = "// NOTE: Assertions have been autogenerated by " ADVERT_END = """ -// The script is designed to make adding checks to -// a test case fast, it is *not* designed to be authoritative -// about what constitutes a good test! The CHECK should be -// minimized and named to reflect the test intent. +// This script is intended to make adding checks to a test case quick and easy. +// It is *not* authoritative about what constitutes a good test. After using the +// script, be sure to review and refine the generated checks. For example, +// CHECK lines should be minimized and named to reflect the test’s intent. +// For comprehensive guidelines, see: +// * https://mlir.llvm.org/getting_started/TestingGuide/ """ @@ -45,6 +48,9 @@ ADVERT_END = """ SSA_RE_STR = "[0-9]+|[a-zA-Z$._-][a-zA-Z0-9$._-]*" SSA_RE = re.compile(SSA_RE_STR) +# Regex matching `dialect.op_name` (e.g. `vector.transfer_read`). +SSA_OP_NAME_RE = re.compile(r"\b(?:\s=\s[a-z_]+)[.]([a-z_]+)\b") + # Regex matching the left-hand side of an assignment SSA_RESULTS_STR = r'\s*(%' + SSA_RE_STR + r')(\s*,\s*(%' + SSA_RE_STR + r'))*\s*=' SSA_RESULTS_RE = re.compile(SSA_RESULTS_STR) @@ -63,7 +69,12 @@ ATTR_DEF_RE = re.compile(ATTR_DEF_RE_STR) class VariableNamer: def __init__(self, variable_names): self.scopes = [] + # Counter for generic FileCHeck names, e.g. VAL_#N self.name_counter = 0 + # Counters for FileCheck names derived from Op names, e.g. + # TRANSFER_READ_#N (based on `vector.transfer_read`). Note, there's a + # dedicated counter for every Op type present in the input. + self.op_name_counter = Counter() # Number of variable names to still generate in parent scope self.generate_in_parent_scope_left = 0 @@ -77,17 +88,29 @@ class VariableNamer: self.generate_in_parent_scope_left = n # Generate a substitution name for the given ssa value name. - def generate_name(self, source_variable_name, use_ssa_name): + def generate_name(self, source_variable_name, use_ssa_name, op_name=""): # Compute variable name - variable_name = self.variable_names.pop(0) if len(self.variable_names) > 0 else '' - if variable_name == '': + variable_name = ( + self.variable_names.pop(0) if len(self.variable_names) > 0 else "" + ) + if variable_name == "": # If `use_ssa_name` is set, use the MLIR SSA value name to generate # a FileCHeck substation string. As FileCheck requires these # strings to start with a character, skip MLIR variables starting # with a digit (e.g. `%0`). + # + # The next fallback option is to use the op name, if the + # corresponding match succeeds. + # + # If neither worked, use a generic name: `VAL_#N`. if use_ssa_name and source_variable_name[0].isalpha(): variable_name = source_variable_name.upper() + elif op_name != "": + variable_name = ( + op_name.upper() + "_" + str(self.op_name_counter[op_name]) + ) + self.op_name_counter[op_name] += 1 else: variable_name = "VAL_" + str(self.name_counter) self.name_counter += 1 @@ -123,6 +146,7 @@ class VariableNamer: def clear_names(self): self.name_counter = 0 self.used_variable_names = set() + self.op_name_counter.clear() class AttributeNamer: @@ -170,8 +194,12 @@ def process_line(line_chunks, variable_namer, use_ssa_name=False, strict_name_re # Process the rest that contained an SSA value name. for chunk in line_chunks: - m = SSA_RE.match(chunk) - ssa_name = m.group(0) if m is not None else '' + ssa = SSA_RE.match(chunk) + op_name_with_dialect = SSA_OP_NAME_RE.search(chunk) + ssa_name = ssa.group(0) if ssa is not None else "" + op_name = ( + op_name_with_dialect.group(1) if op_name_with_dialect is not None else "" + ) # Check if an existing variable exists for this name. variable = None @@ -185,7 +213,7 @@ def process_line(line_chunks, variable_namer, use_ssa_name=False, strict_name_re output_line += "%[[" + variable + "]]" else: # Otherwise, generate a new variable. - variable = variable_namer.generate_name(ssa_name, use_ssa_name) + variable = variable_namer.generate_name(ssa_name, use_ssa_name, op_name) if strict_name_re: # Use stricter regexp for the variable name, if requested. # Greedy matching may cause issues with the generic '.*' |