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Rebase onto llvm-project f69328049e9e with local changes

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This commit rebases the compiler onto commit f69328049e9e from
llvm-project.

Changes:

* Use of the one-shot bufferizer for improved memory management

* A new pass `OneShotBufferizeDPSWrapper` that converts functions
  returning tensors to destination-passing-style as required by the
  one-shot bufferizer

* A new pass `LinalgGenericOpWithTensorsToLoopsPass` that converts
  `linalg.generic` operations with value semantics to loop nests

* Rebase onto a fork of llvm-project at f69328049e9e with local
  modifications to enable bufferization of `linalg.generic` operations
  with value semantics

* Workaround for the absence of type propagation after type conversion
  via extra patterns in all dialect conversion passes

* Printer, parser and verifier definitions moved from inline
  declarations in ODS to the respective source files as required by
  upstream changes

* New tests for functions with a large number of inputs

* Increase the number of allowed task inputs as required by new tests

* Use upstream function `mlir_configure_python_dev_packages()` to
  locate Python development files for compatibility with various CMake
  versions

Co-authored-by: Quentin Bourgerie <quentin.bourgerie@zama.ai>
Co-authored-by: Ayoub Benaissa <ayoub.benaissa@zama.ai>
Co-authored-by: Antoniu Pop <antoniu.pop@zama.ai>
This commit is contained in:
Andi Drebes
2022-06-14 14:35:25 +02:00
parent 670af02112
commit 45577fb79e
141 changed files with 4029 additions and 2029 deletions
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17
compiler/lib/Conversion/MLIRLowerableDialectsToLLVM/MLIRLowerableDialectsToLLVM.cpp
View File

@@ -4,22 +4,25 @@
// for license information.
#include <iostream>
#include <mlir/Conversion/BufferizationToMemRef/BufferizationToMemRef.h>
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/DialectConversion.h"
#include "mlir/Conversion/ArithmeticToLLVM/ArithmeticToLLVM.h"
#include "mlir/Conversion/ControlFlowToLLVM/ControlFlowToLLVM.h"
#include "mlir/Conversion/FuncToLLVM/ConvertFuncToLLVM.h"
#include "mlir/Conversion/FuncToLLVM/ConvertFuncToLLVMPass.h"
#include "mlir/Conversion/LLVMCommon/ConversionTarget.h"
#include "mlir/Conversion/LLVMCommon/TypeConverter.h"
#include "mlir/Conversion/MemRefToLLVM/MemRefToLLVM.h"
#include "mlir/Conversion/OpenMPToLLVM/ConvertOpenMPToLLVM.h"
#include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h"
#include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h"
#include "mlir/Conversion/SCFToControlFlow/SCFToControlFlow.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/OpenMP/OpenMPDialect.h"
#include "mlir/Dialect/SCF/SCF.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/DialectConversion.h"
#include "llvm/ADT/Sequence.h"
@@ -88,7 +91,7 @@ struct Memref1DCopyOpPattern
copyOp.getLoc(), opType, copyOp.source());
auto targetOp = rewriter.create<mlir::memref::CastOp>(
copyOp.getLoc(), opType, copyOp.target());
rewriter.replaceOpWithNewOp<mlir::CallOp>(
rewriter.replaceOpWithNewOp<mlir::func::CallOp>(
copyOp, "memref_copy_one_rank", mlir::TypeRange{},
mlir::ValueRange{sourceOp, targetOp});
return mlir::success();
@@ -122,10 +125,14 @@ void MLIRLowerableDialectsToLLVMPass::runOnOperation() {
patterns.add<Memref1DCopyOpPattern>(&getContext(), 100);
mlir::concretelang::populateRTToLLVMConversionPatterns(typeConverter,
patterns);
mlir::populateStdToLLVMConversionPatterns(typeConverter, patterns);
mlir::populateFuncToLLVMConversionPatterns(typeConverter, patterns);
mlir::arith::populateArithmeticToLLVMConversionPatterns(typeConverter,
patterns);
mlir::populateMemRefToLLVMConversionPatterns(typeConverter, patterns);
mlir::populateSCFToControlFlowConversionPatterns(patterns);
mlir::cf::populateControlFlowToLLVMConversionPatterns(typeConverter,
patterns);
target.addLegalOp<mlir::scf::YieldOp>();
mlir::populateOpenMPToLLVMConversionPatterns(typeConverter, patterns);
target.addDynamicallyLegalOp<mlir::omp::MasterOp, mlir::omp::ParallelOp,