tensorflow/compiler/xla/service/gpu/gpu_transfer_manager.cc

/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include "tensorflow/compiler/xla/service/gpu/gpu_transfer_manager.h"

#include <string>
#include <utility>
#include <vector>

#include "absl/memory/memory.h"
#include "llvm/IR/DataLayout.h"
#include "tensorflow/compiler/xla/literal.h"
#include "tensorflow/compiler/xla/literal_util.h"
#include "tensorflow/compiler/xla/service/gpu/outfeed_manager.h"
#include "tensorflow/compiler/xla/service/gpu/target_constants.h"
#include "tensorflow/compiler/xla/shape_util.h"
#include "tensorflow/compiler/xla/status_macros.h"
#include "tensorflow/compiler/xla/statusor.h"
#include "tensorflow/compiler/xla/types.h"
#include "tensorflow/compiler/xla/util.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/gtl/cleanup.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/stream_executor_no_cuda.h"

namespace xla {
namespace gpu {

// TODO(b/30467474) Once GPU infeed implementation settles, consider
// folding back the cpu and gpu infeed implementations into a generic
// one if possible.
GpuTransferManager::GpuTransferManager(se::Platform::Id id,
                                       unsigned pointer_size)
    : GenericTransferManager(id, pointer_size) {}

Status GpuTransferManager::TransferLiteralToInfeed(
    se::StreamExecutor* executor, const LiteralSlice& literal) {
  return gpu::GetOrCreateInfeedManager(executor)->TransferLiteralToInfeed(
      executor, literal);
}

Status GpuTransferManager::TransferLiteralFromOutfeed(
    se::StreamExecutor* executor, MutableBorrowingLiteral literal) {
  return gpu::GetOrCreateOutfeedManager(executor)->TransferLiteralFromOutfeed(
      executor, literal);
}

}  // namespace gpu
}  // namespace xla

static std::unique_ptr<xla::TransferManager> CreateNVPTXTransferManager() {
  return absl::make_unique<xla::gpu::GpuTransferManager>(
      /*id=*/stream_executor::cuda::kCudaPlatformId,
      /*pointer_size=*/llvm::DataLayout(xla::gpu::nvptx::kDataLayout)
          .getPointerSize(0 /* default address space */));
}

static std::unique_ptr<xla::TransferManager> CreateAMDGPUTransferManager() {
  return absl::make_unique<xla::gpu::GpuTransferManager>(
      /*id=*/stream_executor::rocm::kROCmPlatformId,
      /*pointer_size=*/llvm::DataLayout(xla::gpu::amdgpu::kDataLayout)
          .getPointerSize(0 /* default address space */));
}

static bool InitModule() {
  xla::TransferManager::RegisterTransferManager(
      stream_executor::cuda::kCudaPlatformId, &CreateNVPTXTransferManager);
  xla::TransferManager::RegisterTransferManager(
      stream_executor::rocm::kROCmPlatformId, &CreateAMDGPUTransferManager);
  return true;
}
static bool module_initialized = InitModule();