未验证 提交 7b54f168 编写于 作者: C chengduo 提交者: GitHub

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上级 b0378963
...@@ -73,18 +73,12 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place, ...@@ -73,18 +73,12 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
memory::Copy(dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size, memory::Copy(dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size,
stream); stream);
} else { } else {
// NOTE(zcd): Because TensorCopy is an async operation, when the src_place
// and dst_place are two different GPU, to ensure that the operation can
// be carried out correctly, we should make ctx wait.
// If ctx_place and src_place are the same, we should add ctx.Wait()
// after memory::Copy; if ctx_place and dst_place are the same, we should
// add ctx.Wait() before memory::Copy.
if (platform::is_same_place(ctx_place, src_place)) { if (platform::is_same_place(ctx_place, src_place)) {
memory::Copy(dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size, memory::Copy(dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size,
stream); stream);
ctx.Wait(); platform::DeviceContextPool::Instance().Get(src.place())->Wait();
} else if (platform::is_same_place(ctx_place, dst_place)) { } else if (platform::is_same_place(ctx_place, dst_place)) {
ctx.Wait(); platform::DeviceContextPool::Instance().Get(src.place())->Wait();
memory::Copy(dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size, memory::Copy(dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size,
stream); stream);
} else { } else {
...@@ -97,13 +91,6 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place, ...@@ -97,13 +91,6 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
void TensorCopy(const Tensor& src, const platform::Place& dst_place, void TensorCopy(const Tensor& src, const platform::Place& dst_place,
Tensor* dst) { Tensor* dst) {
// NOTE(zcd): If the src.place() and dst_place are two different GPU,
// the copy operation is carried out on the dst_place's stream. This is
// very important, because TensorCopy is an async operator, and in most
// case, once this copy operator returns, dst is to be used in dst_place's
// stream, if this copy operation is carried out on the src_place's stream,
// when dst is used in dst_place's stream the copy operation may be
// not completed.
platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance(); platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
const platform::DeviceContext* dev_ctx; const platform::DeviceContext* dev_ctx;
if (platform::is_gpu_place(dst_place)) { if (platform::is_gpu_place(dst_place)) {
......
...@@ -23,10 +23,25 @@ limitations under the License. */ ...@@ -23,10 +23,25 @@ limitations under the License. */
namespace paddle { namespace paddle {
namespace framework { namespace framework {
// NOTE(zcd): Because TensorCopy is an async operation, when the src_place
// and dst_place are two different GPU, to ensure that the operation can
// be carried out correctly, there is a src_ctx wait operation in TensorCopy.
// If ctx_place and src_place are the same, src_ctx.Wait() is added
// after memory::Copy; if ctx_place and dst_place are the same,
// src_ctx.Wait() is added before memory::Copy.
void TensorCopy(const Tensor& src, const platform::Place& dst_place, void TensorCopy(const Tensor& src, const platform::Place& dst_place,
const platform::DeviceContext& ctx, Tensor* dst); const platform::DeviceContext& ctx, Tensor* dst);
// NOTE(zcd): If the src.place() and dst_place are two different GPU,
// the copy operation is carried out on the dst_place's stream. This is
// very important, because TensorCopy is an async operator, and in most
// case, once this copy operator returns, dst is to be used in dst_place's
// stream, if this copy operation is carried out on the src_place's stream,
// when dst is used in dst_place's stream the copy operation may be
// not completed.
void TensorCopy(const Tensor& src, const platform::Place& dst_place, void TensorCopy(const Tensor& src, const platform::Place& dst_place,
Tensor* dst); Tensor* dst);
void TensorCopySync(const Tensor& src, const platform::Place& dst_place, void TensorCopySync(const Tensor& src, const platform::Place& dst_place,
Tensor* dst); Tensor* dst);
......
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