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未验证 提交 81d93514 编写于 作者: C chengduo 提交者: GitHub

Merge pull request #9522 from chengduoZH/feature/refine_parallel_exe

Refine parallel
......@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/framework/parallel_executor.h"
#include <string>
#include "ThreadPool.h"
......@@ -102,30 +103,43 @@ void ParallelExecutor::BCastParamsToGPUs(
auto *main_scope = member_->local_scopes_[0];
for (auto *var_desc : startup_program.Block(0).AllVars()) {
size_t idx = var_desc->Name().find("@GRAD");
if (idx != std::string::npos) continue;
if (var_desc->GetType() == proto::VarType::LOD_TENSOR) {
auto &main_tensor =
main_scope->FindVar(var_desc->Name())->Get<LoDTensor>();
ncclDataType_t data_type = platform::ToNCCLDataType(main_tensor.type());
auto &dims = main_tensor.dims();
size_t numel = main_tensor.numel();
platform::NCCLGroupGuard guard;
auto &dims = main_tensor.dims();
for (size_t i = 0; i < member_->places_.size(); ++i) {
auto place = member_->places_[i];
void *buffer;
if (i == 0) {
buffer = const_cast<void *>(main_tensor.data<void>());
} else {
if (paddle::platform::is_gpu_place(main_tensor.place())) {
size_t numel = main_tensor.numel();
ncclDataType_t data_type = platform::ToNCCLDataType(main_tensor.type());
platform::NCCLGroupGuard guard;
for (size_t i = 0; i < member_->places_.size(); ++i) {
auto place = member_->places_[i];
void *buffer;
if (i == 0) {
buffer = const_cast<void *>(main_tensor.data<void>());
} else {
auto local_scope = member_->local_scopes_[i];
auto *t =
local_scope->Var(var_desc->Name())->GetMutable<LoDTensor>();
t->Resize(dims);
buffer = t->mutable_data(place, main_tensor.type());
}
auto &nccl_ctx = member_->nccl_ctxs_->at(place);
platform::dynload::ncclBcast(buffer, numel, data_type, 0,
nccl_ctx.comm_, nccl_ctx.stream());
}
} else {
platform::CPUPlace cpu;
for (size_t i = 1; i < member_->places_.size(); ++i) {
auto local_scope = member_->local_scopes_[i];
auto *t = local_scope->Var(var_desc->Name())->GetMutable<LoDTensor>();
t->Resize(dims);
buffer = t->mutable_data(place, main_tensor.type());
t->mutable_data(cpu, main_tensor.type());
paddle::framework::TensorCopy(main_tensor, cpu, t);
}
auto &nccl_ctx = member_->nccl_ctxs_->at(place);
platform::dynload::ncclBcast(buffer, numel, data_type, 0,
nccl_ctx.comm_, nccl_ctx.stream());
}
}
member_->nccl_ctxs_->WaitAll();
......
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