clang-p2996/mlir/lib/Conversion/GPUToCUDA/ConvertKernelFuncToCubin.cpp

//===- ConvertKernelFuncToCubin.cpp - MLIR GPU lowering passes ------------===//
//
// 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 implements a pass to convert gpu kernel functions into a
// corresponding binary blob that can be executed on a CUDA GPU. Currently
// only translates the function itself but no dependencies.
//
//===----------------------------------------------------------------------===//

#include "mlir/Conversion/GPUToCUDA/GPUToCUDAPass.h"

#include "mlir/Dialect/GPU/GPUDialect.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/Function.h"
#include "mlir/IR/Module.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Pass/PassRegistry.h"
#include "mlir/Support/LogicalResult.h"
#include "mlir/Target/NVVMIR.h"

#include "llvm/ADT/Optional.h"
#include "llvm/ADT/Twine.h"
#include "llvm/IR/Constants.h"
#include "llvm/IR/LegacyPassManager.h"
#include "llvm/IR/Module.h"
#include "llvm/Support/Error.h"
#include "llvm/Support/TargetRegistry.h"
#include "llvm/Support/TargetSelect.h"
#include "llvm/Target/TargetMachine.h"

using namespace mlir;

namespace {
// TODO(herhut): Move to shared location.
static constexpr const char *kCubinAnnotation = "nvvm.cubin";

/// A pass converting tagged kernel modules to cubin blobs.
///
/// If tagged as a kernel module, each contained function is translated to NVVM
/// IR and further to PTX. A user provided CubinGenerator compiles the PTX to
/// GPU binary code, which is then attached as an attribute to the function. The
/// function body is erased.
class GpuKernelToCubinPass
    : public OperationPass<GpuKernelToCubinPass, gpu::GPUModuleOp> {
public:
  GpuKernelToCubinPass(
      CubinGenerator cubinGenerator = compilePtxToCubinForTesting)
      : cubinGenerator(cubinGenerator) {}

  void runOnOperation() override {
    gpu::GPUModuleOp module = getOperation();

    // Make sure the NVPTX target is initialized.
    LLVMInitializeNVPTXTarget();
    LLVMInitializeNVPTXTargetInfo();
    LLVMInitializeNVPTXTargetMC();
    LLVMInitializeNVPTXAsmPrinter();

    auto llvmModule = translateModuleToNVVMIR(module);
    if (!llvmModule)
      return signalPassFailure();

    // Translate the module to CUBIN and attach the result as attribute to the
    // module.
    if (auto cubinAttr = translateGPUModuleToCubinAnnotation(
            *llvmModule, module.getLoc(), module.getName()))
      module.setAttr(kCubinAnnotation, cubinAttr);
    else
      signalPassFailure();
  }

private:
  static OwnedCubin compilePtxToCubinForTesting(const std::string &ptx,
                                                Location, StringRef);

  std::string translateModuleToPtx(llvm::Module &module,
                                   llvm::TargetMachine &target_machine);

  /// Converts llvmModule to cubin using the user-provided generator. Location
  /// is used for error reporting and name is forwarded to the CUBIN generator
  /// to use in its logging mechanisms.
  OwnedCubin convertModuleToCubin(llvm::Module &llvmModule, Location loc,
                                  StringRef name);

  /// Translates llvmModule to cubin and returns the result as attribute.
  StringAttr translateGPUModuleToCubinAnnotation(llvm::Module &llvmModule,
                                                 Location loc, StringRef name);

  CubinGenerator cubinGenerator;
};

} // anonymous namespace

std::string GpuKernelToCubinPass::translateModuleToPtx(
    llvm::Module &module, llvm::TargetMachine &target_machine) {
  std::string ptx;
  {
    llvm::raw_string_ostream stream(ptx);
    llvm::buffer_ostream pstream(stream);
    llvm::legacy::PassManager codegen_passes;
    target_machine.addPassesToEmitFile(codegen_passes, pstream, nullptr,
                                       llvm::CGFT_AssemblyFile);
    codegen_passes.run(module);
  }

  return ptx;
}

OwnedCubin
GpuKernelToCubinPass::compilePtxToCubinForTesting(const std::string &ptx,
                                                  Location, StringRef) {
  const char data[] = "CUBIN";
  return std::make_unique<std::vector<char>>(data, data + sizeof(data) - 1);
}

OwnedCubin GpuKernelToCubinPass::convertModuleToCubin(llvm::Module &llvmModule,
                                                      Location loc,
                                                      StringRef name) {
  std::unique_ptr<llvm::TargetMachine> targetMachine;
  {
    std::string error;
    // TODO(herhut): Make triple configurable.
    constexpr const char *cudaTriple = "nvptx64-nvidia-cuda";
    llvm::Triple triple(cudaTriple);
    const llvm::Target *target =
        llvm::TargetRegistry::lookupTarget("", triple, error);
    if (target == nullptr) {
      emitError(loc, "cannot initialize target triple");
      return {};
    }
    targetMachine.reset(
        target->createTargetMachine(triple.str(), "sm_35", "+ptx60", {}, {}));
  }

  // Set the data layout of the llvm module to match what the ptx target needs.
  llvmModule.setDataLayout(targetMachine->createDataLayout());

  auto ptx = translateModuleToPtx(llvmModule, *targetMachine);

  return cubinGenerator(ptx, loc, name);
}

StringAttr GpuKernelToCubinPass::translateGPUModuleToCubinAnnotation(
    llvm::Module &llvmModule, Location loc, StringRef name) {
  auto cubin = convertModuleToCubin(llvmModule, loc, name);
  if (!cubin)
    return {};
  return StringAttr::get({cubin->data(), cubin->size()}, loc->getContext());
}

std::unique_ptr<OpPassBase<gpu::GPUModuleOp>>
mlir::createConvertGPUKernelToCubinPass(CubinGenerator cubinGenerator) {
  return std::make_unique<GpuKernelToCubinPass>(cubinGenerator);
}

static PassRegistration<GpuKernelToCubinPass>
    pass("test-kernel-to-cubin",
         "Convert all kernel functions to CUDA cubin blobs");