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未验证 提交 a6d2fddb 编写于 作者: R ronnywang 提交者： GitHub
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refine structure for cuda and rocm (#37202) 

* refine structure for cuda and rocm

* update

* update

* update

* update
上级 9ccb6228
展开全部 隐藏空白更改
内联 并排
Showing with 3043 addition and 2151 deletion
paddle/fluid/framework/conv_search_cache.h
浏览文件 @ a6d2fddb
......@@ -17,11 +17,7 @@ limitations under the License. */
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator_kernel_configs.h"
#ifdef PADDLE_WITH_HIP
#include "paddle/fluid/platform/miopen_helper.h"
#else
#include "paddle/fluid/platform/cudnn_helper.h"
#endif
#include "paddle/fluid/platform/device/gpu/gpu_dnn.h"
namespace paddle {
namespace framework {
......
paddle/fluid/framework/details/all_reduce_op_handle.cc
浏览文件 @ a6d2fddb
......@@ -291,13 +291,9 @@ void AllReduceOpHandle::SyncNCCLAllReduce() {
nccl_ctxs_->GetRunEnvNCCLCtx(run_order_, use_hierarchical_allreduce_);
auto &nccl_ctx = nccl_ctxs->at(dev_id);
auto stream = nccl_ctx.stream();
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
PADDLE_ENFORCE_CUDA_SUCCESS(hipGetLastError());
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
PADDLE_ENFORCE_CUDA_SUCCESS(cudaGetLastError());
#endif
platform::GpuStreamSync(stream);
PADDLE_ENFORCE_GPU_SUCCESS(platform::GpuGetLastError());
}
}
}
......
paddle/fluid/framework/details/all_reduce_op_handle.h
浏览文件 @ a6d2fddb
......@@ -33,7 +33,7 @@ class NCCLCommunicator;
} // namespace paddle
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/framework/details/nccl_op_handle.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#elif defined(PADDLE_WITH_XPU_BKCL)
#include "paddle/fluid/framework/details/bkcl_op_handle.h"
#include "paddle/fluid/platform/device/xpu/bkcl_helper.h"
......
paddle/fluid/framework/details/broadcast_op_handle.cc
浏览文件 @ a6d2fddb
......@@ -111,7 +111,7 @@ void BroadcastOpHandle::BroadcastOneVar(
broadcast_calls.emplace_back(
[send_recv_buffer, numel, type, root_id, &nccl_ctx] {
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBcast(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclBcast(
send_recv_buffer, numel, static_cast<ncclDataType_t>(type),
root_id, nccl_ctx.comm_, nccl_ctx.stream()));
});
......
paddle/fluid/framework/details/broadcast_op_handle.h
浏览文件 @ a6d2fddb
......@@ -44,7 +44,7 @@ struct BKCLContextMap;
} // namespace paddle
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#elif defined(PADDLE_WITH_XPU_BKCL)
#include "paddle/fluid/platform/device/xpu/bkcl_helper.h"
#endif
......
paddle/fluid/framework/details/broadcast_op_handle_test.h
浏览文件 @ a6d2fddb
......@@ -95,7 +95,7 @@ struct TestBroadcastOpHandle {
#endif
} else if (use_device_ == p::kCUDA) {
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
int count = p::GetCUDADeviceCount();
int count = p::GetGPUDeviceCount();
if (count <= 1) {
LOG(WARNING) << "Cannot test multi-gpu Broadcast, because the CUDA "
"device count is "
......
paddle/fluid/framework/details/build_strategy.h
浏览文件 @ a6d2fddb
......@@ -40,7 +40,7 @@ class NCCLCommunicator;
} // namespace paddle
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#elif defined(PADDLE_WITH_XPU) && defined(PADDLE_WITH_XPU_BKCL)
#include "paddle/fluid/platform/device/xpu/bkcl_helper.h"
#endif
......
paddle/fluid/framework/details/eager_deletion_op_handle.cc
浏览文件 @ a6d2fddb
......@@ -49,10 +49,10 @@ EagerDeletionOpHandle::EagerDeletionOpHandle(
platform::CUDADeviceGuard guard(
BOOST_GET_CONST(platform::CUDAPlace, place).device);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipEventCreateWithFlags(&event_, hipEventDisableTiming));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventCreateWithFlags(&event_, cudaEventDisableTiming));
#endif
PADDLE_ENFORCE_NOT_NULL(event_, platform::errors::InvalidArgument(
......@@ -75,9 +75,9 @@ EagerDeletionOpHandle::~EagerDeletionOpHandle() {
auto gpu_place = BOOST_GET_CONST(platform::CUDAPlace, dev_ctx_->GetPlace());
platform::CUDADeviceGuard guard(gpu_place.device);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventDestroy(event_));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventDestroy(event_));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(event_));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventDestroy(event_));
#endif
}
#endif
......@@ -160,12 +160,12 @@ void EagerDeletionOpHandle::ClearGarbages(
reinterpret_cast<StreamGarbageCollector *>(gc_)->stream();
auto callback_func = [=]() {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventRecord(event_, compute_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(hipEventRecord(event_, compute_stream));
PADDLE_ENFORCE_GPU_SUCCESS(
hipStreamWaitEvent(callback_stream, event_, 0));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event_, compute_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventRecord(event_, compute_stream));
PADDLE_ENFORCE_GPU_SUCCESS(
cudaStreamWaitEvent(callback_stream, event_, 0));
#endif
};
......
paddle/fluid/framework/details/fused_all_reduce_op_handle.cc
浏览文件 @ a6d2fddb
......@@ -55,9 +55,9 @@ FusedAllReduceOpHandle::~FusedAllReduceOpHandle() {
auto destroy_event = [](gpuEvent_t event) {
if (event == nullptr) return;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventDestroy(event));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventDestroy(event));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(event));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventDestroy(event));
#endif
};
destroy_event(start_event_);
......@@ -87,10 +87,10 @@ void FusedAllReduceOpHandle::RunImpl() {
auto create_event = [](gpuEvent_t *event) {
if (*event) return;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipEventCreateWithFlags(event, hipEventDisableTiming));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventCreateWithFlags(event, cudaEventDisableTiming));
#endif
};
......@@ -109,12 +109,12 @@ void FusedAllReduceOpHandle::RunImpl() {
auto &nccl_ctx = flat_nccl_ctxs->at(gpu_place.device);
nccl_stream = nccl_ctx.stream();
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventRecord(start_event_, compute_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(hipEventRecord(start_event_, compute_stream));
PADDLE_ENFORCE_GPU_SUCCESS(
hipStreamWaitEvent(nccl_stream, start_event_, 0));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(start_event_, compute_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventRecord(start_event_, compute_stream));
PADDLE_ENFORCE_GPU_SUCCESS(
cudaStreamWaitEvent(nccl_stream, start_event_, 0));
#endif
} else {
......@@ -169,12 +169,12 @@ void FusedAllReduceOpHandle::RunImpl() {
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
if (FLAGS_allreduce_record_one_event) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventRecord(end_event_, nccl_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(hipEventRecord(end_event_, nccl_stream));
PADDLE_ENFORCE_GPU_SUCCESS(
hipStreamWaitEvent(compute_stream, end_event_, 0));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(end_event_, nccl_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventRecord(end_event_, nccl_stream));
PADDLE_ENFORCE_GPU_SUCCESS(
cudaStreamWaitEvent(compute_stream, end_event_, 0));
#endif
}
......
paddle/fluid/framework/details/fused_all_reduce_op_handle.h
浏览文件 @ a6d2fddb
......@@ -35,7 +35,7 @@ class NCCLCommunicator;
} // namespace paddle
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/framework/details/nccl_op_handle.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#elif defined(PADDLE_WITH_XPU_BKCL)
#include "paddle/fluid/platform/device/xpu/bkcl_helper.h"
#endif
......
paddle/fluid/framework/details/fused_broadcast_op_handle.h
浏览文件 @ a6d2fddb
......@@ -37,7 +37,7 @@ struct NCCLContextMap;
} // namespace paddle
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
namespace paddle {
......
paddle/fluid/framework/details/gather_op_handle_test.cc
浏览文件 @ a6d2fddb
......@@ -48,7 +48,7 @@ struct TestGatherOpHandle {
void InitCtxOnGpu(bool use_gpu) {
if (use_gpu) {
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
int count = p::GetCUDADeviceCount();
int count = p::GetGPUDeviceCount();
if (count <= 1) {
LOG(WARNING) << "Cannot test multi-gpu Broadcast, because the CUDA "
"device count is "
......
paddle/fluid/framework/details/grad_merge_all_reduce_op_handle.h
浏览文件 @ a6d2fddb
......@@ -35,7 +35,7 @@ class NCCLCommunicator;
} // namespace paddle
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/framework/details/nccl_op_handle.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
namespace paddle {
......
paddle/fluid/framework/details/nan_inf_utils_detail.cu
浏览文件 @ a6d2fddb
......@@ -40,7 +40,7 @@ static std::vector<std::mutex>& multi_op_var2gpu_str_mutex() {
}
static void InitMultiGPUOpVarMap() {
int dev_count = platform::GetCUDADeviceCount();
int dev_count = platform::GetGPUDeviceCount();
PADDLE_ENFORCE_GT(dev_count, 0,
platform::errors::NotFound(
"cuda device must > 0, now dev_count=%d", dev_count));
......@@ -161,11 +161,11 @@ void TensorCheckerVisitor<platform::CUDADeviceContext>::apply(
op_var));
#ifdef __HIPCC__
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipMemcpyAsync(gpu_str_ptr, iter->first.c_str(), op_var.length() + 1,
hipMemcpyHostToDevice, dev_ctx->stream()));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaMemcpyAsync(gpu_str_ptr, iter->first.c_str(), op_var.length() + 1,
cudaMemcpyHostToDevice, dev_ctx->stream()));
#endif
......
paddle/fluid/framework/details/nccl_op_handle.h
浏览文件 @ a6d2fddb
......@@ -27,7 +27,7 @@
#ifdef PADDLE_WITH_HIP
#include "paddle/fluid/platform/dynload/rccl.h"
#endif
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
DECLARE_bool(sync_nccl_allreduce);
......@@ -52,16 +52,16 @@ class NCCLOpHandleBase : public OpHandleBase {
virtual ~NCCLOpHandleBase() {
for (auto& ev : inter_events_) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventDestroy(ev.second));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventDestroy(ev.second));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(ev.second));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventDestroy(ev.second));
#endif
}
for (auto& ev : exter_events_) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventDestroy(ev.second));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventDestroy(ev.second));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(ev.second));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventDestroy(ev.second));
#endif
}
}
......@@ -109,14 +109,14 @@ class NCCLOpHandleBase : public OpHandleBase {
platform::SetDeviceId(dev_id);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventCreateWithFlags(
PADDLE_ENFORCE_GPU_SUCCESS(hipEventCreateWithFlags(
&inter_events_[dev_id], hipEventDisableTiming));
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventCreateWithFlags(
PADDLE_ENFORCE_GPU_SUCCESS(hipEventCreateWithFlags(
&exter_events_[dev_id], hipEventDisableTiming));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventCreateWithFlags(
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventCreateWithFlags(
&inter_events_[dev_id], cudaEventDisableTiming));
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventCreateWithFlags(
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventCreateWithFlags(
&exter_events_[dev_id], cudaEventDisableTiming));
#endif
VLOG(10) << "Create events on dev_id:" << dev_id
......@@ -142,7 +142,7 @@ class NCCLOpHandleBase : public OpHandleBase {
<< ", dev_id:" << dev_id << ", dtype:" << datatype
<< ", place:" << place;
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllReduce(
sendbuff, recvbuff, count, datatype, op, comm, stream));
}
......@@ -192,7 +192,7 @@ class NCCLOpHandleBase : public OpHandleBase {
<< ", dtype:" << datatype << ", place:" << place
<< ", stream:" << stream;
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclReduce(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclReduce(
sendbuff, recvbuff, count, datatype, ncclSum, 0, comm, stream));
#ifdef PADDLE_WITH_HIP
......@@ -202,11 +202,7 @@ class NCCLOpHandleBase : public OpHandleBase {
#endif
if (FLAGS_sync_nccl_allreduce) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
#endif
platform::GpuStreamSync(stream);
}
}
......@@ -230,26 +226,21 @@ class NCCLOpHandleBase : public OpHandleBase {
#ifdef PADDLE_WITH_HIP
hipStreamWaitEvent(stream, inter_events_.at(dev_id), 0);
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllReduce(
sendbuff, recvbuff, count, datatype, op, comm, stream));
hipEventRecord(exter_events_.at(dev_id), stream);
if (FLAGS_sync_nccl_allreduce) {
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
}
#else
cudaStreamWaitEvent(stream, inter_events_.at(dev_id), 0);
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllReduce(
sendbuff, recvbuff, count, datatype, op, comm, stream));
cudaEventRecord(exter_events_.at(dev_id), stream);
#endif
if (FLAGS_sync_nccl_allreduce) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
platform::GpuStreamSync(stream);
}
#endif
}
void InterBroadCast(platform::Place place, void* sendbuff, size_t count,
......@@ -269,7 +260,7 @@ class NCCLOpHandleBase : public OpHandleBase {
#else
cudaStreamWaitEvent(stream, exter_events_.at(dev_id), 0);
#endif
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBcast(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclBcast(
sendbuff, count, datatype, 0, comm, stream));
}
......
paddle/fluid/framework/details/op_handle_base.cc
浏览文件 @ a6d2fddb
......@@ -35,9 +35,9 @@ OpHandleBase::~OpHandleBase() PADDLE_MAY_THROW {
for (auto &ev : events_) {
if (ev.second) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventDestroy(ev.second));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventDestroy(ev.second));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(ev.second));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventDestroy(ev.second));
#endif
}
}
......@@ -50,10 +50,10 @@ void OpHandleBase::InitCUDA() {
int dev_id = BOOST_GET_CONST(platform::CUDAPlace, p.first).device;
platform::SetDeviceId(dev_id);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipEventCreateWithFlags(&events_[dev_id], hipEventDisableTiming));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventCreateWithFlags(&events_[dev_id], cudaEventDisableTiming));
#endif
}
......@@ -182,9 +182,9 @@ void OpHandleBase::RecordWaitEventOnCtx(platform::DeviceContext *waited_ctx) {
static_cast<platform::CUDADeviceContext *>(waited_ctx)->stream();
for (auto &ev : events_) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamWaitEvent(stream, ev.second, 0));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamWaitEvent(stream, ev.second, 0));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamWaitEvent(stream, ev.second, 0));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamWaitEvent(stream, ev.second, 0));
#endif
}
}
......@@ -221,10 +221,10 @@ void OpHandleBase::WaitInputVarGenerated(bool wait_for_feed) {
static_cast<platform::CUDADeviceContext *>(dev_ctxes_.at(place))
->stream();
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipStreamWaitEvent(stream, in_var_handle->GetEvent(), 0));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaStreamWaitEvent(stream, in_var_handle->GetEvent(), 0));
#endif
#else
......@@ -250,11 +250,7 @@ void OpHandleBase::WaitInputVarGenerated(bool wait_for_feed) {
auto stream =
static_cast<platform::CUDADeviceContext *>(pool.Get(place))
->stream();
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
#endif
platform::GpuStreamSync(stream);
#else
PADDLE_THROW(platform::errors::PreconditionNotMet(
"Not compiled with CUDA."));
......@@ -279,10 +275,10 @@ void OpHandleBase::WaitInputVarGenerated(const platform::Place &place) {
dev_ctxes_.at(in_var_handle->place()))
->stream();
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipStreamWaitEvent(stream, in_var_handle->GetEvent(), 0));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaStreamWaitEvent(stream, in_var_handle->GetEvent(), 0));
#endif
#else
......@@ -319,10 +315,10 @@ void OpHandleBase::RunAndRecordEvent(const std::function<void()> &callback) {
auto *cuda_dev_ctx = static_cast<platform::CUDADeviceContext *>(p.second);
VLOG(10) << "cudadevicecontext:" << cuda_dev_ctx << ", dev_id:" << dev_id;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipEventRecord(events_.at(dev_id), cuda_dev_ctx->stream()));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventRecord(events_.at(dev_id), cuda_dev_ctx->stream()));
#endif
}
......
paddle/fluid/framework/details/reduce_op_handle.cc
浏览文件 @ a6d2fddb
......@@ -193,7 +193,7 @@ void ReduceOpHandle::RunImpl() {
size_t numel = static_cast<size_t>(lod_tensor.numel());
all_reduce_calls.emplace_back(
[buffer, recvbuffer, type, numel, root_id, &nccl_ctx] {
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclReduce(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclReduce(
buffer, recvbuffer, numel, static_cast<ncclDataType_t>(type),
ncclSum, root_id, nccl_ctx.comm_, nccl_ctx.stream()));
});
......
paddle/fluid/framework/details/reduce_op_handle.h
浏览文件 @ a6d2fddb
......@@ -41,7 +41,7 @@ struct NCCLContextMap;
} // namespace platform
} // namespace paddle
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#elif defined(PADDLE_WITH_XPU_BKCL)
#include "paddle/fluid/platform/device/xpu/bkcl_helper.h"
#endif
......
paddle/fluid/framework/details/reduce_op_handle_test.cc
浏览文件 @ a6d2fddb
......@@ -59,7 +59,7 @@ struct TestReduceOpHandle {
use_gpu_ = use_gpu;
if (use_gpu) {
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
int count = p::GetCUDADeviceCount();
int count = p::GetGPUDeviceCount();
if (count <= 1) {
LOG(WARNING) << "Cannot test multi-gpu Broadcast, because the CUDA "
"device count is "
......
paddle/fluid/framework/details/sparse_all_reduce_op_handle.cc
浏览文件 @ a6d2fddb
......@@ -23,7 +23,7 @@
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/memory/malloc.h"
#include "paddle/fluid/platform/cuda_device_guard.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/profiler.h"
DECLARE_bool(sync_nccl_allreduce);
......@@ -182,7 +182,7 @@ void SparseAllReduceOpHandle::RunImplEncoded() {
<< ", k:" << k << ", place:" << place << ", dtype:" << dtype;
all_gather_calls.emplace_back([=] {
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
in_tensor_buf, gather_buff, 2 * k, static_cast<ncclDataType_t>(dtype),
comm, stream));
});
......
paddle/fluid/framework/details/sparse_all_reduce_op_handle.h
浏览文件 @ a6d2fddb
......@@ -21,7 +21,7 @@
#include "paddle/fluid/framework/details/dgc_const_values.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
namespace paddle {
namespace framework {
......
paddle/fluid/framework/device_worker.h
浏览文件 @ a6d2fddb
......@@ -54,7 +54,7 @@ class DeviceContext;
} // namespace paddle
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
namespace paddle {
......
paddle/fluid/framework/dlpack_tensor_test.cc
浏览文件 @ a6d2fddb
......@@ -115,7 +115,7 @@ void TestMainLoop() {
std::vector<platform::Place> places{platform::CPUPlace(),
platform::CUDAPlace(0),
platform::CUDAPinnedPlace()};
if (platform::GetCUDADeviceCount() > 1) {
if (platform::GetGPUDeviceCount() > 1) {
places.emplace_back(platform::CUDAPlace(1));
}
#else
......
paddle/fluid/framework/fleet/ascend_wrapper.h
浏览文件 @ a6d2fddb
......@@ -24,7 +24,7 @@ limitations under the License. */
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/platform/timer.h"
......
paddle/fluid/framework/fleet/box_wrapper.cc
浏览文件 @ a6d2fddb
......@@ -19,7 +19,7 @@
#include <memory>
#include <numeric>
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
namespace paddle {
namespace framework {
......
paddle/fluid/framework/fleet/box_wrapper.cu
浏览文件 @ a6d2fddb
......@@ -19,7 +19,7 @@
#include <numeric>
#include "paddle/fluid/framework/fleet/box_wrapper.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
namespace paddle {
namespace framework {
......
paddle/fluid/framework/fleet/box_wrapper.h
浏览文件 @ a6d2fddb
......@@ -40,7 +40,7 @@ limitations under the License. */
#include "paddle/fluid/framework/data_set.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/platform/timer.h"
#include "paddle/fluid/string/string_helper.h"
......@@ -397,7 +397,7 @@ class BoxWrapper {
if (nullptr != s_instance_) {
VLOG(3) << "Begin InitializeGPU";
std::vector<gpuStream_t*> stream_list;
for (int i = 0; i < platform::GetCUDADeviceCount(); ++i) {
for (int i = 0; i < platform::GetGPUDeviceCount(); ++i) {
VLOG(3) << "before get context i[" << i << "]";
platform::CUDADeviceContext* context =
dynamic_cast<platform::CUDADeviceContext*>(
......@@ -416,7 +416,7 @@ class BoxWrapper {
slot_name_omited_in_feedpass_.insert(slot_name);
}
slot_vector_ = slot_vector;
keys_tensor.resize(platform::GetCUDADeviceCount());
keys_tensor.resize(platform::GetGPUDeviceCount());
}
}
......
paddle/fluid/framework/fleet/fleet_wrapper.cc
浏览文件 @ a6d2fddb
......@@ -740,10 +740,10 @@ void FleetWrapper::PushDenseVarsAsync(
BOOST_GET_CONST(platform::CUDAPlace, place), g_data,
sizeof(float) * count, stream);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventRecord(event, stream));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventRecord(event, stream));
hipEventSynchronize(event);
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event, stream));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventRecord(event, stream));
cudaEventSynchronize(event);
#endif
......
paddle/fluid/framework/fleet/fleet_wrapper.h
浏览文件 @ a6d2fddb
......@@ -35,7 +35,7 @@ limitations under the License. */
#include "paddle/fluid/framework/variable_helper.h"
#include "paddle/fluid/platform/macros.h" // for DISABLE_COPY_AND_ASSIGN
#ifdef PADDLE_WITH_HETERPS
#include "paddle/fluid/platform/type_defs.h"
#include "paddle/fluid/platform/device/gpu/gpu_types.h"
#endif
namespace paddle {
......
paddle/fluid/framework/fleet/heter_ps/hashtable.h
浏览文件 @ a6d2fddb
......@@ -28,7 +28,7 @@ limitations under the License. */
// #include "cudf/concurrent_unordered_map.cuh.h"
#include "paddle/fluid/framework/fleet/heter_ps/cudf/concurrent_unordered_map.cuh.h"
#ifdef PADDLE_WITH_HETERPS
#include "paddle/fluid/platform/type_defs.h"
#include "paddle/fluid/platform/device/gpu/gpu_types.h"
namespace paddle {
namespace framework {
......
paddle/fluid/framework/fleet/heter_ps/heter_comm_inl.h
浏览文件 @ a6d2fddb
......@@ -347,7 +347,7 @@ void HeterComm<KeyType, ValType, GradType>::build_ps(int num, KeyType* h_keys,
gpuStream_t streams[stream_num];
for (int i = 0; i < stream_num; ++i) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&(streams[i])));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamCreate(&(streams[i])));
auto d_k_buf = memory::AllocShared(place, chunk_size * sizeof(KeyType));
auto d_v_buf = memory::AllocShared(place, chunk_size * sizeof(ValType));
d_key_bufs.push_back(d_k_buf);
......@@ -360,11 +360,11 @@ void HeterComm<KeyType, ValType, GradType>::build_ps(int num, KeyType* h_keys,
while (cur_len < len) {
cur_stream = cur_stream % stream_num;
int tmp_len = cur_len + chunk_size > len ? len - cur_len : chunk_size;
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaMemcpyAsync(d_key_bufs[cur_stream]->ptr(), h_keys + cur_len,
sizeof(KeyType) * tmp_len, cudaMemcpyHostToDevice,
streams[cur_stream]));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaMemcpyAsync(d_val_bufs[cur_stream]->ptr(), h_vals + cur_len,
sizeof(ValType) * tmp_len, cudaMemcpyHostToDevice,
streams[cur_stream]));
......@@ -378,7 +378,7 @@ void HeterComm<KeyType, ValType, GradType>::build_ps(int num, KeyType* h_keys,
for (int i = 0; i < stream_num; ++i) {
cudaStreamSynchronize(streams[i]);
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamDestroy(streams[i]));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamDestroy(streams[i]));
}
}
......@@ -402,14 +402,14 @@ void HeterComm<KeyType, ValType, GradType>::merge_grad(int gpu_num,
GradType* d_merge_grads_ptr =
reinterpret_cast<GradType*>(d_merge_grads->ptr());
PADDLE_ENFORCE_CUDA_SUCCESS(cub::DeviceRadixSort::SortPairs(
PADDLE_ENFORCE_GPU_SUCCESS(cub::DeviceRadixSort::SortPairs(
NULL, temp_storage_bytes, d_keys, d_merge_keys_ptr, d_grads,
d_merge_grads_ptr, len, 0, 8 * sizeof(KeyType), stream, false));
void* d_buff = NULL;
auto d_temp_storage = memory::AllocShared(place, temp_storage_bytes);
PADDLE_ENFORCE_CUDA_SUCCESS(cub::DeviceRadixSort::SortPairs(
PADDLE_ENFORCE_GPU_SUCCESS(cub::DeviceRadixSort::SortPairs(
d_temp_storage->ptr(), temp_storage_bytes, d_keys, d_merge_keys_ptr,
d_grads, d_merge_grads_ptr, len, 0, 8 * sizeof(KeyType), stream, false));
temp_storage_bytes = 0;
......@@ -417,7 +417,7 @@ void HeterComm<KeyType, ValType, GradType>::merge_grad(int gpu_num,
auto d_num_runs_out_mem = memory::AllocShared(place, sizeof(int));
int* d_num_runs_out = reinterpret_cast<int*>(d_num_runs_out_mem->ptr());
PADDLE_ENFORCE_CUDA_SUCCESS(cub::DeviceReduce::ReduceByKey(
PADDLE_ENFORCE_GPU_SUCCESS(cub::DeviceReduce::ReduceByKey(
NULL, temp_storage_bytes, d_merge_keys_ptr, d_keys, d_merge_grads_ptr,
d_grads, d_num_runs_out, merger_, len, stream, false));
......@@ -426,13 +426,13 @@ void HeterComm<KeyType, ValType, GradType>::merge_grad(int gpu_num,
d_temp_storage = memory::AllocShared(place, temp_storage_bytes);
}
PADDLE_ENFORCE_CUDA_SUCCESS(cub::DeviceReduce::ReduceByKey(
PADDLE_ENFORCE_GPU_SUCCESS(cub::DeviceReduce::ReduceByKey(
d_temp_storage->ptr(), temp_storage_bytes, d_merge_keys_ptr, d_keys,
d_merge_grads_ptr, d_grads, d_num_runs_out, merger_, len, stream, false));
cudaMemcpyAsync(&uniq_len, d_num_runs_out, sizeof(int),
cudaMemcpyDeviceToHost, stream);
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamSynchronize(stream));
}
template <typename KeyType, typename ValType, typename GradType>
......@@ -461,12 +461,12 @@ void HeterComm<KeyType, ValType, GradType>::split_input_to_shard(
size_t temp_storage_bytes;
const int num_bits = 1 + log2i(total_gpu);
PADDLE_ENFORCE_CUDA_SUCCESS(cub::DeviceRadixSort::SortPairs(
PADDLE_ENFORCE_GPU_SUCCESS(cub::DeviceRadixSort::SortPairs(
NULL, temp_storage_bytes, d_shard_index_tmp_ptr, d_shard_index_ptr,
d_idx_tmp_ptr, d_idx_ptr, len, 0, num_bits, stream));
auto d_temp_storage = memory::AllocShared(place, temp_storage_bytes);
PADDLE_ENFORCE_CUDA_SUCCESS(cub::DeviceRadixSort::SortPairs(
PADDLE_ENFORCE_GPU_SUCCESS(cub::DeviceRadixSort::SortPairs(
d_temp_storage->ptr(), temp_storage_bytes, d_shard_index_tmp_ptr,
d_shard_index_ptr, d_idx_tmp_ptr, d_idx_ptr, len, 0, num_bits, stream));
calc_shard_offset<<<grid_size, block_size_, 0, stream>>>(d_shard_index_ptr,
......@@ -720,12 +720,12 @@ int HeterComm<KeyType, ValType, GradType>::gather_one_node_grad(
cudaMemcpyHostToDevice);
// allgather grad len
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupStart());
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupStart());
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
(const void*)(d_node_len + gpu_num), (void*)d_node_len, 1, ncclInt,
nccl_inner_comm, stream));
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupEnd());
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupEnd());
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamSynchronize(stream));
cudaMemcpy(h_node_len, d_node_len, sizeof(int) * total_gpu,
cudaMemcpyDeviceToHost);
......@@ -737,15 +737,15 @@ int HeterComm<KeyType, ValType, GradType>::gather_one_node_grad(
storage.alloc(max_size * total_gpu);
// allgather keys and grads
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupStart());
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupStart());
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
d_keys, storage.all_keys, max_size, ncclUint64, nccl_inner_comm, stream));
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
d_grads, storage.all_grads, max_size * sizeof(GradType), ncclUint8,
nccl_inner_comm, stream));
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupEnd());
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupEnd());
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamSynchronize(stream));
int h_left[total_gpu];
int h_right[total_gpu];
......@@ -802,11 +802,11 @@ int HeterComm<KeyType, ValType, GradType>::gather_multi_node_grad(
cudaMemcpy(d_node_len, h_node_len, sizeof(int), cudaMemcpyHostToDevice);
// allgather grad len
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupStart());
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupStart());
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
d_node_len, d_node_len, 1, ncclInt, nccl_inter_comm, stream));
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupEnd());
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupEnd());
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamSynchronize(stream));
cudaMemcpy(h_node_len, d_node_len, sizeof(int) * node_size_,
cudaMemcpyDeviceToHost);
......@@ -818,15 +818,15 @@ int HeterComm<KeyType, ValType, GradType>::gather_multi_node_grad(
storage.alloc(max_size * node_size_);
// allgather keys and grads
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupStart());
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupStart());
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
d_keys, storage.all_keys, max_size, ncclUint64, nccl_inter_comm, stream));
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
d_grads, storage.all_grads, max_size * sizeof(GradType), ncclUint8,
nccl_inter_comm, stream));
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupEnd());
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupEnd());
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamSynchronize(stream));
int merge_num = 0;
for (int i = 0; i < node_size_; ++i) {
......
paddle/fluid/framework/fleet/heter_ps/heter_resource.cc
浏览文件 @ a6d2fddb
......@@ -30,11 +30,11 @@ GPUResource::GPUResource(std::vector<int>& dev_ids, int index) {
remote_streams_.resize(dev_ids_.size());
for (size_t i = 0; i < dev_ids_.size(); ++i) {
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaStreamCreateWithFlags(&local_streams_[i], cudaStreamNonBlocking));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaStreamCreateWithFlags(&comm_streams_[i], cudaStreamNonBlocking));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaStreamCreateWithFlags(&remote_streams_[i], cudaStreamNonBlocking));
}
}
......@@ -42,13 +42,13 @@ GPUResource::GPUResource(std::vector<int>& dev_ids, int index) {
GPUResource::~GPUResource() {
platform::CUDADeviceGuard guard(dev_id_);
for (size_t i = 0; i < local_streams_.size(); ++i) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamDestroy(local_streams_[i]));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamDestroy(local_streams_[i]));
}
for (size_t i = 0; i < comm_streams_.size(); ++i) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamDestroy(comm_streams_[i]));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamDestroy(comm_streams_[i]));
}
for (size_t i = 0; i < remote_streams_.size(); ++i) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamDestroy(remote_streams_[i]));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamDestroy(remote_streams_[i]));
}
}
......@@ -58,7 +58,7 @@ void HeterPsResource::enable_p2p() {
for (size_t j = 0; j < dev_ids_.size(); ++j) {
if (i != j) {
int p2p_flag;
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaDeviceCanAccessPeer(&p2p_flag, dev_ids_[i], dev_ids_[j]));
if (p2p_flag == 1) {
cudaError_t ret = cudaDeviceEnablePeerAccess(dev_ids_[j], 0);
......
paddle/fluid/framework/fleet/nccl_wrapper.cc
浏览文件 @ a6d2fddb
......@@ -22,7 +22,7 @@ bool NCCLWrapper::is_initialized_ = false;
void NCCLWrapper::InitNCCL() {
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclCommInitRank(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclCommInitRank(
&(nccl_info_.comm_), nccl_info_.global_ranks_, nccl_info_.nccl_id_,
nccl_info_.my_global_rank_));
#endif
......@@ -38,7 +38,7 @@ void NCCLWrapper::SetNCCLId(const NCCLInfo& nccl_info) {
NCCLInfo NCCLWrapper::GetNCCLId() {
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::ncclGetUniqueId(&(nccl_info_.nccl_id_)));
#endif
return nccl_info_;
......@@ -52,9 +52,9 @@ void NCCLWrapper::SetRankInfo(const int local_rank, const int global_rank,
nccl_info_.global_ranks_ = ranks;
platform::SetDeviceId(local_rank);
#ifdef PADDLE_WITH_RCCL
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamCreate(&(nccl_info_.stream_)));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamCreate(&(nccl_info_.stream_)));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&(nccl_info_.stream_)));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamCreate(&(nccl_info_.stream_)));
#endif
#endif
return;
......@@ -67,7 +67,7 @@ void NCCLWrapper::SyncVar(const int root_rank, const Scope& scope,
auto var = scope.FindVar(name);
LoDTensor* tensor = var->GetMutable<LoDTensor>();
int32_t total_size = tensor->numel();
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBcast(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclBcast(
reinterpret_cast<void*>(tensor->data<float>()), total_size, ncclFloat,
root_rank, nccl_info_.comm_, nccl_info_.stream_));
#ifdef PADDLE_WITH_RCCL
......
paddle/fluid/framework/fleet/ps_gpu_wrapper.cu
浏览文件 @ a6d2fddb
......@@ -20,7 +20,7 @@ limitations under the License. */
#include "paddle/fluid/framework/fleet/heter_ps/optimizer_conf.h"
#include "paddle/fluid/framework/fleet/ps_gpu_wrapper.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
namespace paddle {
namespace framework {
......
paddle/fluid/framework/fleet/ps_gpu_wrapper.h
浏览文件 @ a6d2fddb
......@@ -37,8 +37,8 @@ limitations under the License. */
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/framework/variable_helper.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/dynload/nccl.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/macros.h" // for DISABLE_COPY_AND_ASSIGN
#include "paddle/fluid/platform/place.h"
#ifdef PADDLE_WITH_PSCORE
......@@ -230,7 +230,7 @@ class PSGPUWrapper {
? 1.0
: config["mf_max_bound"];
for (size_t i = 0; i < heter_devices_.size(); i++) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaSetDevice(heter_devices_[i]));
PADDLE_ENFORCE_GPU_SUCCESS(cudaSetDevice(heter_devices_[i]));
this->SetSparseSGD(nonclk_coeff, clk_coeff, min_bound, max_bound,
learning_rate, initial_g2sum, initial_range);
this->SetEmbedxSGD(mf_create_thresholds, mf_learning_rate,
......
paddle/fluid/framework/garbage_collector.cc
浏览文件 @ a6d2fddb
......@@ -83,9 +83,9 @@ StreamGarbageCollector::StreamGarbageCollector(const platform::CUDAPlace &place,
: GarbageCollector(place, max_memory_size) {
platform::CUDADeviceGuard guard(place.device);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamCreate(&stream_));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamCreate(&stream_));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&stream_));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamCreate(&stream_));
callback_manager_.reset(
new platform::StreamCallbackManager<gpuStream_t>(stream_));
#endif
......@@ -94,13 +94,8 @@ StreamGarbageCollector::StreamGarbageCollector(const platform::CUDAPlace &place,
StreamGarbageCollector::~StreamGarbageCollector() {
auto place = BOOST_GET_CONST(platform::CUDAPlace, this->dev_ctx_->GetPlace());
platform::CUDADeviceGuard guard(place.device);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream_));
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamDestroy(stream_));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream_));
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamDestroy(stream_));
#endif
platform::GpuStreamSync(stream_);
platform::GpuDestroyStream(stream_);
}
gpuStream_t StreamGarbageCollector::stream() const { return stream_; }
......
paddle/fluid/framework/generator.cc
浏览文件 @ a6d2fddb
......@@ -18,8 +18,8 @@ limitations under the License. */
#include <memory>
#include <utility>
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/gpu_info.h"
namespace paddle {
namespace framework {
......@@ -33,7 +33,7 @@ const std::shared_ptr<Generator>& GetDefaultCUDAGenerator(int64_t device_id) {
static std::vector<std::shared_ptr<Generator>> default_cuda_generators;
std::call_once(num_devices_init_flag, []() {
num_cuda_devices = paddle::platform::GetCUDADeviceCount();
num_cuda_devices = paddle::platform::GetGPUDeviceCount();
cuda_device_flags.resize(num_cuda_devices);
default_cuda_generators.resize(num_cuda_devices);
});
......
paddle/fluid/framework/heterxpu_trainer.cc
浏览文件 @ a6d2fddb
......@@ -51,11 +51,11 @@ void HeterXpuTrainer::Initialize(const TrainerDesc& trainer_desc,
platform::CUDAPlace place = platform::CUDAPlace(num);
platform::CUDADeviceGuard guard(place.device);
cudaStream_t stream;
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&stream));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamCreate(&stream));
copy_streams_.push_back(stream);
places_.push_back(place);
cudaEvent_t event;
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventCreateWithFlags(&event, cudaEventDisableTiming));
events_.push_back(event);
#endif
......@@ -104,7 +104,7 @@ void HeterXpuTrainer::Initialize(const TrainerDesc& trainer_desc,
// platform::CUDAPlace place = platform::CUDAPlace(num);
// platform::CUDADeviceGuard guard(place.device);
// cudaStream_t stream;
// PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&stream));
// PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamCreate(&stream));
// copy_streams_.push_back(stream);
// places_.push_back(place);
// }
......@@ -157,7 +157,7 @@ void HeterXpuTrainer::CreateThreadParam(const ProgramDesc& program, int num) {
}
}
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event, stream));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventRecord(event, stream));
cudaEventSynchronize(event);
#endif
}
......@@ -287,7 +287,7 @@ void HeterXpuTrainer::InitOtherEnv(const ProgramDesc& main_program) {
#ifdef PADDLE_WITH_CUDA
auto dev_id = BOOST_GET_CONST(platform::CUDAPlace, place).device;
platform::CUDADeviceGuard guard(dev_id);
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventCreateWithFlags(&context->event_, cudaEventDisableTiming));
#endif
object_pool_.Push(context);
......@@ -441,7 +441,7 @@ int HeterXpuTrainer::RunTask(const HeterRequest* request,
#ifdef PADDLE_WITH_CUDA
auto dev_id = BOOST_GET_CONST(platform::CUDAPlace, place).device;
platform::CUDADeviceGuard guard(dev_id);
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventCreateWithFlags(&context->event_, cudaEventDisableTiming));
#endif
}
......@@ -461,7 +461,7 @@ int HeterXpuTrainer::RunTask(const HeterRequest* request,
#endif
}
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventRecord(context->event_, copy_streams_[context->place_num_]));
while (cudaEventQuery(context->event_) != cudaSuccess) {
VLOG(3) << "wait for kernel";
......@@ -481,7 +481,7 @@ int HeterXpuTrainer::RunTask(const HeterRequest* request,
#ifdef PADDLE_WITH_CUDA
auto* dev_ctx = static_cast<platform::CUDADeviceContext*>(
platform::DeviceContextPool::Instance().Get(place));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventRecord(context->event_, dev_ctx->stream()));
// cudaEventSynchronize(context->event_);
{
......
paddle/fluid/framework/ir/fuse_bn_act_pass.cc
浏览文件 @ a6d2fddb
......@@ -24,12 +24,8 @@ class Node;
} // namespace ir
} // namespace framework
} // namespace paddle
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/cudnn_helper.h"
#endif
#ifdef PADDLE_WITH_HIP
#include "paddle/fluid/platform/miopen_helper.h"
#endif
#include "paddle/fluid/platform/device/gpu/gpu_dnn.h"
namespace paddle {
namespace framework {
......
paddle/fluid/framework/ir/fuse_bn_add_act_pass.cc
浏览文件 @ a6d2fddb
......@@ -15,13 +15,8 @@
#include "paddle/fluid/framework/ir/fuse_bn_add_act_pass.h"
#include <string>
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/platform/device/gpu/gpu_dnn.h"
#include "paddle/fluid/platform/enforce.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/cudnn_helper.h"
#endif
#ifdef PADDLE_WITH_HIP
#include "paddle/fluid/platform/miopen_helper.h"
#endif
namespace paddle {
namespace framework {
......
paddle/fluid/framework/mixed_vector_test.cu
浏览文件 @ a6d2fddb
......@@ -24,7 +24,7 @@
#include "glog/logging.h"
#include "gtest/gtest.h"
#include "paddle/fluid/framework/mixed_vector.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
template <typename T>
using vec = paddle::framework::Vector<T>;
......@@ -63,7 +63,7 @@ TEST(mixed_vector, GPU_VECTOR) {
}
TEST(mixed_vector, MultiGPU) {
if (paddle::platform::GetCUDADeviceCount() < 2) {
if (paddle::platform::GetGPUDeviceCount() < 2) {
LOG(WARNING) << "Skip mixed_vector.MultiGPU since there are not multiple "
"GPUs in your machine.";
return;
......
paddle/fluid/framework/new_executor/interpretercore.cc
浏览文件 @ a6d2fddb
......@@ -398,13 +398,8 @@ void InterpreterCore::RunInstruction(const Instruction& instr_node) {
/*For profiling/benchmark only*/
if (FLAGS_benchmark) {
instr_node.DeviceContext().Wait();
#if defined(PADDLE_WITH_CUDA)
PADDLE_ENFORCE_CUDA_SUCCESS(cudaGetLastError());
VLOG(4) << "Operator(" << op->Type()
<< "): context wait and get last error";
#endif
#if defined(PADDLE_WITH_HIP)
PADDLE_ENFORCE_CUDA_SUCCESS(hipGetLastError());
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
PADDLE_ENFORCE_GPU_SUCCESS(platform::GpuGetLastError());
VLOG(4) << "Operator(" << op->Type()
<< "): context wait and get last error";
#endif
......
paddle/fluid/framework/new_executor/profiler.h
浏览文件 @ a6d2fddb
......@@ -15,7 +15,7 @@
#pragma once
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/framework/variable.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/timer.h"
namespace paddle {
......@@ -45,7 +45,7 @@ class ProfilerGuard {
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
auto cuda_place = BOOST_GET_CONST(platform::CUDAPlace, place);
cost_info_->device_memory_bytes =
platform::RecordedCudaMallocSize(cuda_place.device);
platform::RecordedGpuMallocSize(cuda_place.device);
#endif
}
}
......
paddle/fluid/framework/operator.cc
浏览文件 @ a6d2fddb
......@@ -1212,14 +1212,10 @@ void OperatorWithKernel::RunImpl(const Scope& scope,
/*For profiling/benchmark only*/
if (FLAGS_benchmark) {
dev_ctx->Wait();
#if defined(PADDLE_WITH_CUDA)
PADDLE_ENFORCE_CUDA_SUCCESS(cudaGetLastError());
VLOG(4) << "Operator(" << Type() << "): context wait and get last error";
#if defined(PADDLE_WITH_CUDA) || defined(PADLDE_WITH_ROCM)
PADDLE_ENFORCE_GPU_SUCCESS(platform::GpuGetLastError());
#endif
#if defined(PADDLE_WITH_HIP)
PADDLE_ENFORCE_CUDA_SUCCESS(hipGetLastError());
VLOG(4) << "Operator(" << Type() << "): context wait and get last error";
#endif
}
if (FLAGS_check_nan_inf) {
......
paddle/fluid/framework/parallel_executor.h
浏览文件 @ a6d2fddb
......@@ -34,7 +34,7 @@ limitations under the License. */
#include "paddle/fluid/platform/device_context.h"
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
namespace paddle {
......
paddle/fluid/framework/var_type_traits.cc
浏览文件 @ a6d2fddb
......@@ -22,7 +22,7 @@
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_NCCL)
#include "paddle/fluid/operators/nccl/nccl_gpu_common.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
#include <cudnn.h>
#include "paddle/fluid/operators/conv_cudnn_op_cache.h"
......@@ -30,8 +30,8 @@
#endif
#ifdef PADDLE_WITH_HIP
#if defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/operators/nccl/nccl_gpu_common.h" // NOLINT
#include "paddle/fluid/platform/nccl_helper.h" // NOLINT
#include "paddle/fluid/operators/nccl/nccl_gpu_common.h" // NOLINT
#include "paddle/fluid/platform/device/gpu/nccl_helper.h" // NOLINT
#endif
#include "paddle/fluid/operators/conv_cudnn_op_cache.h" // NOLINT
#include "paddle/fluid/operators/miopen_rnn_cache.h"
......
paddle/fluid/framework/var_type_traits_test.cc
浏览文件 @ a6d2fddb
......@@ -23,15 +23,15 @@
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_NCCL)
#include "paddle/fluid/operators/nccl/nccl_gpu_common.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
#include "paddle/fluid/operators/conv_cudnn_op_cache.h"
#include "paddle/fluid/operators/cudnn_rnn_cache.h"
#endif
#ifdef PADDLE_WITH_HIP
#if defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/operators/nccl/nccl_gpu_common.h" // NOLINT
#include "paddle/fluid/platform/nccl_helper.h" // NOLINT
#include "paddle/fluid/operators/nccl/nccl_gpu_common.h" // NOLINT
#include "paddle/fluid/platform/device/gpu/nccl_helper.h" // NOLINT
#endif
#include "paddle/fluid/operators/conv_cudnn_op_cache.h" // NOLINT
#include "paddle/fluid/operators/miopen_rnn_cache.h"
......
paddle/fluid/imperative/all_reduce.cc
浏览文件 @ a6d2fddb
......@@ -28,8 +28,8 @@
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/framework/variable.h"
#include "paddle/fluid/imperative/parallel_context.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/string/string_helper.h"
namespace paddle {
......@@ -64,7 +64,7 @@ static void AllReduce(const framework::Tensor &src, framework::Tensor *dst,
dst->Resize(src.dims());
auto *dst_ptr = dst->mutable_data(src.place(), src.type());
auto nccl_dtype = platform::ToNCCLDataType(src.type());
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllReduce(
src_ptr, dst_ptr, src.numel(), nccl_dtype, ncclSum, comm->comm(),
stream));
}
......@@ -100,16 +100,12 @@ static void AllReduce(const framework::SelectedRows &src,
if (!use_calc_stream) {
dev_ctx->Wait();
}
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
gpu_rows_num_ptr + strategy.local_rank_, gpu_rows_num_ptr, 1, ncclInt64,
comm->comm(), stream));
if (!use_calc_stream) {
#ifdef PADDLE_WITH_RCCL
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
#endif
platform::GpuStreamSync(stream);
}
const auto *cpu_rows_num_ptr = rows_num_vector.data();
......@@ -146,11 +142,11 @@ static void AllReduce(const framework::SelectedRows &src,
// allgather is used to speed up the allreduce by replacing broadcast.
auto row_sendcount = cpu_rows_num_ptr[0];
VLOG(3) << "allgather replaces broadcast to speed up in sparse allreduce";
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
src_rows_ptr, dst_rows_ptr, row_sendcount, ncclInt64, comm->comm(),
stream));
auto value_sendcount = cpu_rows_num_ptr[0] * feature_size;
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllGather(
src_tensor_ptr, dst_tensor_ptr, value_sendcount, nccl_dtype,
comm->comm(), stream));
return;
......@@ -158,13 +154,13 @@ static void AllReduce(const framework::SelectedRows &src,
for (int i = 0; i < strategy.nranks_; ++i) {
if (cpu_rows_num_ptr[i] > 0) {
// 2. Broadcast the rows of SelectedRows
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBroadcast(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclBroadcast(
src_rows_ptr, dst_rows_ptr + row_offset, cpu_rows_num_ptr[i],
ncclInt64, i, comm->comm(), stream));
// 3. Broadcast the tensor data of SelectedRows
auto *dst_tensor_ptr_i = reinterpret_cast<uint8_t *>(dst_tensor_ptr) +
row_offset * feature_size * sizeof_dtype;
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBroadcast(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclBroadcast(
src_tensor_ptr, dst_tensor_ptr_i, cpu_rows_num_ptr[i] * feature_size,
nccl_dtype, i, comm->comm(), stream));
row_offset += cpu_rows_num_ptr[i];
......@@ -209,12 +205,8 @@ void AllReduce(const framework::Variable &src, framework::Variable *dst,
AllReduce(src.Get<framework::SelectedRows>(),
tmp_dst.GetMutable<framework::SelectedRows>(), strategy, stream,
comm);
// stream must synchronize to ensure accuracy of the move operation
#ifdef PADDLE_WITH_RCCL
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
#endif
// stream must synchronize to ensure accuracy of the move operation
platform::GpuStreamSync(stream);
*dst = std::move(tmp_dst);
}
#endif
......
paddle/fluid/imperative/nccl_context.cc
浏览文件 @ a6d2fddb
......@@ -153,11 +153,11 @@ void NCCLParallelContext::WaitCompute(int ring_id) {
// compute_stream-->event-->comm_stream
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventRecord(event, compute_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamWaitEvent(comm_stream, event, 0));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventRecord(event, compute_stream));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamWaitEvent(comm_stream, event, 0));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event, compute_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamWaitEvent(comm_stream, event, 0));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventRecord(event, compute_stream));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamWaitEvent(comm_stream, event, 0));
#endif
}
......@@ -179,11 +179,11 @@ void NCCLParallelContext::WaitComm(int ring_id) {
// comm_stream-->event-->compute_stream
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventRecord(event, comm_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamWaitEvent(compute_stream, event, 0));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventRecord(event, comm_stream));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamWaitEvent(compute_stream, event, 0));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event, comm_stream));
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamWaitEvent(compute_stream, event, 0));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventRecord(event, comm_stream));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamWaitEvent(compute_stream, event, 0));
#endif
}
......
paddle/fluid/imperative/nccl_context.h
浏览文件 @ a6d2fddb
......@@ -18,7 +18,7 @@
#include <vector>
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/cuda_resource_pool.h"
#include "paddle/fluid/platform/device/gpu/gpu_resource_pool.h"
#endif
#ifdef PADDLE_WITH_NCCL
......
paddle/fluid/imperative/prepared_operator.cc
浏览文件 @ a6d2fddb
......@@ -24,6 +24,8 @@
#ifdef PADDLE_WITH_XPU
#include "paddle/fluid/platform/device/xpu/xpu_op_list.h"
#endif
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
DECLARE_bool(check_nan_inf);
DECLARE_bool(run_pten_kernel);
DECLARE_bool(benchmark);
......@@ -523,12 +525,8 @@ static void PreparedOpRunPtImpl(
if (FLAGS_benchmark) {
dev_ctx->Wait();
#if defined(PADDLE_WITH_CUDA)
PADDLE_ENFORCE_CUDA_SUCCESS(cudaGetLastError());
VLOG(4) << "Operator(" << op.Type() << "): context wait and get last error";
#endif
#if defined(PADDLE_WITH_HIP)
PADDLE_ENFORCE_CUDA_SUCCESS(hipGetLastError());
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
PADDLE_ENFORCE_GPU_SUCCESS(platform::GpuGetLastError());
VLOG(4) << "Operator(" << op.Type() << "): context wait and get last error";
#endif
}
......
paddle/fluid/inference/api/analysis_config.cc
浏览文件 @ a6d2fddb
......@@ -19,8 +19,8 @@
#include "paddle/fluid/inference/api/paddle_pass_builder.h"
#include "paddle/fluid/inference/utils/table_printer.h"
#include "paddle/fluid/platform/cpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/gpu_info.h"
#ifdef PADDLE_WITH_TENSORRT
#include "paddle/fluid/inference/tensorrt/helper.h"
......
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @ a6d2fddb
......@@ -41,8 +41,8 @@
#include "paddle/fluid/inference/utils/singleton.h"
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/platform/cpu_helper.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/platform/profiler.h"
#include "paddle/pten/api/ext/op_meta_info.h"
......
paddle/fluid/inference/api/paddle_infer_contrib.cc
浏览文件 @ a6d2fddb
......@@ -27,7 +27,7 @@ using paddle::PaddleDType;
void* TensorUtils::CudaMallocPinnedMemory(size_t size) {
#if defined(PADDLE_WITH_CUDA)
void* ptr = nullptr;
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMallocHost(&ptr, size));
PADDLE_ENFORCE_GPU_SUCCESS(cudaMallocHost(&ptr, size));
return ptr;
#else
return nullptr;
......@@ -36,7 +36,7 @@ void* TensorUtils::CudaMallocPinnedMemory(size_t size) {
void TensorUtils::CudaFreePinnedMemory(void* ptr) {
#if defined(PADDLE_WITH_CUDA)
PADDLE_ENFORCE_CUDA_SUCCESS(cudaFreeHost(ptr));
PADDLE_ENFORCE_GPU_SUCCESS(cudaFreeHost(ptr));
#endif
}
......
paddle/fluid/inference/tensorrt/convert/io_converter.cc
浏览文件 @ a6d2fddb
......@@ -45,7 +45,7 @@ class DefaultIOConverter : public EngineIOConverter {
"the input max_size. But in's memory_size = %u, max_size = %u.",
size, max_size));
if (is_cpu_place(place)) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemcpyAsync(
PADDLE_ENFORCE_GPU_SUCCESS(cudaMemcpyAsync(
out, in.data<float>(), size, cudaMemcpyHostToDevice, *stream_));
} else if (is_gpu_place(place)) {
PADDLE_ENFORCE_EQ(
......
paddle/fluid/inference/tensorrt/engine.cc
浏览文件 @ a6d2fddb
......@@ -20,8 +20,8 @@ limitations under the License. */
#include "cuda_runtime_api.h" // NOLINT
#include "paddle/fluid/inference/tensorrt/helper.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/gpu_info.h"
namespace paddle {
namespace inference {
......
paddle/fluid/inference/tensorrt/plugin/deformable_conv_op_plugin.cu
浏览文件 @ a6d2fddb
......@@ -43,16 +43,16 @@ nvinfer1::Weights DeformableConvPlugin::copyToDevice(const void* hostData,
size_t count) {
int num_bytes = (data_type_ == nvinfer1::DataType::kFLOAT ? 4 : 2);
void* deviceData;
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMalloc(&deviceData, count * num_bytes));
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemcpy(
deviceData, hostData, count * num_bytes, cudaMemcpyHostToDevice));
PADDLE_ENFORCE_GPU_SUCCESS(cudaMalloc(&deviceData, count * num_bytes));
PADDLE_ENFORCE_GPU_SUCCESS(cudaMemcpy(deviceData, hostData, count * num_bytes,
cudaMemcpyHostToDevice));
return nvinfer1::Weights{data_type_, deviceData, int64_t(count)};
}
void DeformableConvPlugin::serializeFromDevice(
void** hostBuffer, const nvinfer1::Weights& deviceWeights) const {
int num_bytes = (data_type_ == nvinfer1::DataType::kFLOAT ? 4 : 2);
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaMemcpy(static_cast<char*>(*hostBuffer), deviceWeights.values,
deviceWeights.count * num_bytes, cudaMemcpyDeviceToHost));
hostBuffer += deviceWeights.count * num_bytes;
......
paddle/fluid/inference/tensorrt/plugin/instance_norm_op_plugin.cu
浏览文件 @ a6d2fddb
......@@ -17,7 +17,7 @@
#include <vector>
#include "glog/logging.h"
#include "paddle/fluid/inference/tensorrt/plugin/instance_norm_op_plugin.h"
#include "paddle/fluid/platform/cudnn_helper.h"
#include "paddle/fluid/platform/device/gpu/gpu_dnn.h"
namespace paddle {
namespace inference {
......
paddle/fluid/inference/tensorrt/plugin/split_op_plugin.cu
浏览文件 @ a6d2fddb
......@@ -136,7 +136,7 @@ int SplitPlugin::enqueue(int batchSize, const void* const* inputs,
float const* input_ptr = reinterpret_cast<float const*>(inputs[0]);
float* const* h_odatas = reinterpret_cast<float* const*>(outputs);
float** output_ptrs = thrust::raw_pointer_cast(&d_output_ptrs_[0]);
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemcpyAsync(
PADDLE_ENFORCE_GPU_SUCCESS(cudaMemcpyAsync(
output_ptrs, h_odatas, d_output_ptrs_.size() * sizeof(float*),
cudaMemcpyHostToDevice, stream));
......@@ -263,7 +263,7 @@ int SplitPluginDynamic::enqueue(const nvinfer1::PluginTensorDesc* input_desc,
float* const* h_odatas = reinterpret_cast<float* const*>(outputs);
float** output_ptrs = thrust::raw_pointer_cast(&d_output_ptrs[0]);
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemcpyAsync(
PADDLE_ENFORCE_GPU_SUCCESS(cudaMemcpyAsync(
output_ptrs, h_odatas, d_output_ptrs.size() * sizeof(float*),
cudaMemcpyHostToDevice, stream));
......@@ -279,7 +279,7 @@ int SplitPluginDynamic::enqueue(const nvinfer1::PluginTensorDesc* input_desc,
half* const* h_odatas = reinterpret_cast<half* const*>(outputs);
half** output_ptrs = thrust::raw_pointer_cast(&d_output_ptrs[0]);
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemcpyAsync(
PADDLE_ENFORCE_GPU_SUCCESS(cudaMemcpyAsync(
output_ptrs, h_odatas, d_output_ptrs.size() * sizeof(half*),
cudaMemcpyHostToDevice, stream));
......
paddle/fluid/inference/tensorrt/trt_int8_calibrator.cc
浏览文件 @ a6d2fddb
......@@ -85,7 +85,7 @@ bool TRTInt8Calibrator::setBatch(
engine_name_, it.first));
}
const auto& d = dataptr->second;
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaMemcpy(d.first, it.second, d.second, cudaMemcpyDeviceToDevice));
}
......
paddle/fluid/memory/allocation/allocator_facade.cc
浏览文件 @ a6d2fddb
......@@ -30,13 +30,10 @@
#include "paddle/fluid/memory/allocation/pinned_allocator.h"
#include "paddle/fluid/memory/allocation/stream_safe_cuda_allocator.h"
#include "paddle/fluid/memory/allocation/thread_local_allocator.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#ifdef PADDLE_WITH_CUDA
#include <cuda_runtime.h>
#include "paddle/fluid/platform/cuda_graph.h"
#else
#include <hip/hip_runtime.h>
#include "paddle/fluid/platform/device/gpu/cuda/cuda_graph.h"
#endif
#if CUDA_VERSION >= 10020
......@@ -145,8 +142,7 @@ class AllocatorFacadePrivate {
"naive_best_fit strategy";
FLAGS_use_stream_safe_cuda_allocator = false;
}
for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount();
++dev_id) {
for (int dev_id = 0; dev_id < platform::GetGPUDeviceCount(); ++dev_id) {
InitNaiveBestFitCUDAAllocator(platform::CUDAPlace(dev_id));
}
InitNaiveBestFitCUDAPinnedAllocator();
......@@ -172,13 +168,13 @@ class AllocatorFacadePrivate {
if (FLAGS_use_stream_safe_cuda_allocator) {
// TODO(Ruibiao): Support multi-stream allocator for other strategies
default_stream_ = nullptr;
for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount();
for (int dev_id = 0; dev_id < platform::GetGPUDeviceCount();
++dev_id) {
InitStreamSafeCUDAAllocator(platform::CUDAPlace(dev_id),
default_stream_);
}
} else {
for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount();
for (int dev_id = 0; dev_id < platform::GetGPUDeviceCount();
++dev_id) {
InitAutoGrowthCUDAAllocator(platform::CUDAPlace(dev_id),
allow_free_idle_chunk_);
......@@ -208,8 +204,7 @@ class AllocatorFacadePrivate {
FLAGS_use_stream_safe_cuda_allocator = false;
}
for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount();
++dev_id) {
for (int dev_id = 0; dev_id < platform::GetGPUDeviceCount(); ++dev_id) {
InitThreadLocalCUDAAllocator(platform::CUDAPlace(dev_id));
}
InitNaiveBestFitCUDAPinnedAllocator();
......@@ -399,10 +394,10 @@ class AllocatorFacadePrivate {
CUdevice device;
int val;
try {
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
paddle::platform::dynload::cuDeviceGet(&device, p.GetDeviceId()));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
paddle::platform::dynload::cuDeviceGetAttribute(
&val, CU_DEVICE_ATTRIBUTE_VIRTUAL_ADDRESS_MANAGEMENT_SUPPORTED,
device));
......@@ -476,10 +471,10 @@ class AllocatorFacadePrivate {
CUdevice device;
int val;
try {
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
paddle::platform::dynload::cuDeviceGet(&device, p.GetDeviceId()));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
paddle::platform::dynload::cuDeviceGetAttribute(
&val, CU_DEVICE_ATTRIBUTE_VIRTUAL_ADDRESS_MANAGEMENT_SUPPORTED,
device));
......@@ -599,7 +594,7 @@ class AllocatorFacadePrivate {
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
system_allocators_[platform::CUDAPinnedPlace()] =
std::make_shared<CPUPinnedAllocator>();
int device_count = platform::GetCUDADeviceCount();
int device_count = platform::GetGPUDeviceCount();
for (int i = 0; i < device_count; ++i) {
platform::CUDAPlace p(i);
system_allocators_[p] = std::make_shared<CUDAAllocator>(p);
......@@ -612,7 +607,7 @@ class AllocatorFacadePrivate {
std::vector<platform::Place> places;
places.emplace_back(platform::CPUPlace());
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
int device_count = platform::GetCUDADeviceCount();
int device_count = platform::GetGPUDeviceCount();
for (int dev_id = 0; dev_id < device_count; ++dev_id) {
places.emplace_back(platform::CUDAPlace(dev_id));
}
......
paddle/fluid/memory/allocation/allocator_facade.h
浏览文件 @ a6d2fddb
......@@ -19,7 +19,7 @@
#include "paddle/fluid/memory/allocation/npu_pinned_allocator.h"
#endif
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#endif
#include "paddle/fluid/platform/place.h"
......
paddle/fluid/memory/allocation/auto_growth_best_fit_allocator_facade_test.cc
浏览文件 @ a6d2fddb
......@@ -19,7 +19,7 @@
#include <thread> // NOLINT
#include "gflags/gflags.h"
#include "paddle/fluid/memory/allocation/allocator_facade.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
DECLARE_double(fraction_of_gpu_memory_to_use);
......
paddle/fluid/memory/allocation/cuda_allocator.cc
浏览文件 @ a6d2fddb
......@@ -25,8 +25,8 @@
#include <string>
#include "paddle/fluid/platform/cuda_device_guard.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/gpu_info.h"
namespace paddle {
namespace memory {
......@@ -37,8 +37,8 @@ void CUDAAllocator::FreeImpl(Allocation* allocation) {
BOOST_GET_CONST(platform::CUDAPlace, allocation->place()), place_,
platform::errors::PermissionDenied(
"GPU memory is freed in incorrect device. This may be a bug"));
platform::RecordedCudaFree(allocation->ptr(), allocation->size(),
place_.device);
platform::RecordedGpuFree(allocation->ptr(), allocation->size(),
place_.device);
delete allocation;
}
......@@ -46,13 +46,13 @@ Allocation* CUDAAllocator::AllocateImpl(size_t size) {
std::call_once(once_flag_, [this] { platform::SetDeviceId(place_.device); });
void* ptr;
auto result = platform::RecordedCudaMalloc(&ptr, size, place_.device);
auto result = platform::RecordedGpuMalloc(&ptr, size, place_.device);
if (LIKELY(result == gpuSuccess)) {
return new Allocation(ptr, size, platform::Place(place_));
}
size_t avail, total, actual_avail, actual_total;
bool is_limited = platform::RecordedCudaMemGetInfo(
bool is_limited = platform::RecordedGpuMemGetInfo(
&avail, &total, &actual_avail, &actual_total, place_.device);
size_t allocated = total - avail;
......
paddle/fluid/memory/allocation/cuda_device_context_allocator.h
浏览文件 @ a6d2fddb
......@@ -81,10 +81,10 @@ class CUDADeviceContextAllocator : public Allocator {
: place_(place), default_stream_(default_stream) {
platform::CUDADeviceGuard guard(place_.device);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipEventCreateWithFlags(&event_, hipEventDisableTiming));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventCreate(&event_, cudaEventDisableTiming));
#endif
}
......@@ -93,9 +93,9 @@ class CUDADeviceContextAllocator : public Allocator {
if (event_) {
platform::CUDADeviceGuard guard(place_.device);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventDestroy(event_));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventDestroy(event_));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(event_));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventDestroy(event_));
#endif
}
}
......@@ -111,12 +111,11 @@ class CUDADeviceContextAllocator : public Allocator {
new CUDADeviceContextAllocation(memory::Alloc(place_, size));
// Wait for the event on stream
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventRecord(event_, default_stream_));
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamWaitEvent(default_stream_, event_, 0));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventRecord(event_, default_stream_));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamWaitEvent(default_stream_, event_, 0));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event_, default_stream_));
PADDLE_ENFORCE_CUDA_SUCCESS(
cudaStreamWaitEvent(default_stream_, event_, 0));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventRecord(event_, default_stream_));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamWaitEvent(default_stream_, event_, 0));
#endif
return allocation;
}
......
paddle/fluid/memory/allocation/cuda_virtual_mem_allocator.cc
浏览文件 @ a6d2fddb
......@@ -23,8 +23,8 @@
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/cuda_device_guard.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/dynload/cuda_driver.h"
#include "paddle/fluid/platform/gpu_info.h"
#endif
#if CUDA_VERSION >= 10020
......@@ -49,10 +49,10 @@ CUDAVirtualMemAllocator::CUDAVirtualMemAllocator(
// Prepare the access descriptor array indicating where and how the backings
// should be visible.
for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount(); ++dev_id) {
for (int dev_id = 0; dev_id < platform::GetGPUDeviceCount(); ++dev_id) {
if (place.device != dev_id) {
int capable = 0;
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaDeviceCanAccessPeer(&capable, place.device, dev_id));
if (!capable) {
VLOG(1) << "device(" << place.device
......@@ -73,10 +73,10 @@ CUDAVirtualMemAllocator::CUDAVirtualMemAllocator(
// Get the minimum granularity needed for all devices
// (the max of the minimum granularity of each participating device)
granularity_ = 0;
for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount(); ++dev_id) {
for (int dev_id = 0; dev_id < platform::GetGPUDeviceCount(); ++dev_id) {
size_t granularity;
prop.location.id = dev_id;
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
paddle::platform::dynload::cuMemGetAllocationGranularity(
&granularity, &prop, CU_MEM_ALLOC_GRANULARITY_MINIMUM));
granularity_ = std::max(granularity, granularity_);
......@@ -84,7 +84,7 @@ CUDAVirtualMemAllocator::CUDAVirtualMemAllocator(
size_t actual_avail, actual_total;
paddle::platform::CUDADeviceGuard guard(place.device);
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemGetInfo(&actual_avail, &actual_total));
PADDLE_ENFORCE_GPU_SUCCESS(cudaMemGetInfo(&actual_avail, &actual_total));
virtual_mem_size_ = AlignedSize(actual_total, granularity_);
......@@ -93,7 +93,7 @@ CUDAVirtualMemAllocator::CUDAVirtualMemAllocator(
// GPU,
// so the virtual address space size we reserve is equal to the GPU video
// memory size
PADDLE_ENFORCE_CUDA_SUCCESS(paddle::platform::dynload::cuMemAddressReserve(
PADDLE_ENFORCE_GPU_SUCCESS(paddle::platform::dynload::cuMemAddressReserve(
&virtual_mem_base_, virtual_mem_size_, 0, 0, 0));
virtual_mem_alloced_offset_ = 0;
......@@ -123,11 +123,11 @@ void CUDAVirtualMemAllocator::FreeImpl(Allocation* allocation) {
auto result =
paddle::platform::dynload::cuMemUnmap(iter->first, iter->second.second);
if (result != CUDA_ERROR_DEINITIALIZED) {
PADDLE_ENFORCE_CUDA_SUCCESS(result);
PADDLE_ENFORCE_GPU_SUCCESS(result);
}
if (result != CUDA_ERROR_DEINITIALIZED) {
PADDLE_ENFORCE_CUDA_SUCCESS(platform::RecordedCuMemRelease(
PADDLE_ENFORCE_GPU_SUCCESS(platform::RecordedGpuMemRelease(
iter->second.first, iter->second.second, place_.device));
}
......@@ -166,12 +166,12 @@ Allocation* CUDAVirtualMemAllocator::AllocateImpl(size_t size) {
// Create physical memory backing allocation.
auto result =
platform::RecordedCuMemCreate(&handle, size, &prop_, 0, place_.device);
platform::RecordedGpuMemCreate(&handle, size, &prop_, 0, place_.device);
if (result != CUDA_SUCCESS) {
if (result == CUDA_ERROR_OUT_OF_MEMORY) {
size_t actual_avail, actual_total;
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemGetInfo(&actual_avail, &actual_total));
PADDLE_ENFORCE_GPU_SUCCESS(cudaMemGetInfo(&actual_avail, &actual_total));
size_t actual_allocated = actual_total - actual_avail;
PADDLE_THROW_BAD_ALLOC(platform::errors::ResourceExhausted(
......@@ -186,7 +186,7 @@ Allocation* CUDAVirtualMemAllocator::AllocateImpl(size_t size) {
string::HumanReadableSize(actual_allocated),
string::HumanReadableSize(actual_avail), place_.device));
} else {
PADDLE_ENFORCE_CUDA_SUCCESS(result);
PADDLE_ENFORCE_GPU_SUCCESS(result);
}
return nullptr;
}
......@@ -197,8 +197,8 @@ Allocation* CUDAVirtualMemAllocator::AllocateImpl(size_t size) {
result = paddle::platform::dynload::cuMemMap(ptr, size, 0, handle, 0);
if (result != CUDA_SUCCESS) {
platform::RecordedCuMemRelease(handle, size, place_.device);
PADDLE_ENFORCE_CUDA_SUCCESS(result);
platform::RecordedGpuMemRelease(handle, size, place_.device);
PADDLE_ENFORCE_GPU_SUCCESS(result);
return nullptr;
}
......@@ -208,8 +208,8 @@ Allocation* CUDAVirtualMemAllocator::AllocateImpl(size_t size) {
if (result != CUDA_SUCCESS) {
paddle::platform::dynload::cuMemUnmap(ptr, size);
platform::RecordedCuMemRelease(handle, size, place_.device);
PADDLE_ENFORCE_CUDA_SUCCESS(result);
platform::RecordedGpuMemRelease(handle, size, place_.device);
PADDLE_ENFORCE_GPU_SUCCESS(result);
return nullptr;
}
......
paddle/fluid/memory/allocation/naive_best_fit_allocator.cc
浏览文件 @ a6d2fddb
......@@ -20,8 +20,8 @@
#include "glog/logging.h"
#include "paddle/fluid/memory/detail/buddy_allocator.h"
#include "paddle/fluid/memory/detail/system_allocator.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/profiler.h"
#include "paddle/fluid/string/printf.h"
......
paddle/fluid/memory/allocation/pinned_allocator.cc
浏览文件 @ a6d2fddb
......@@ -20,18 +20,18 @@ namespace allocation {
bool CPUPinnedAllocator::IsAllocThreadSafe() const { return true; }
void CPUPinnedAllocator::FreeImpl(Allocation *allocation) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipHostFree(allocation->ptr()));
PADDLE_ENFORCE_GPU_SUCCESS(hipHostFree(allocation->ptr()));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaFreeHost(allocation->ptr()));
PADDLE_ENFORCE_GPU_SUCCESS(cudaFreeHost(allocation->ptr()));
#endif
delete allocation;
}
Allocation *CPUPinnedAllocator::AllocateImpl(size_t size) {
void *ptr;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipHostMalloc(&ptr, size, hipHostMallocPortable));
PADDLE_ENFORCE_GPU_SUCCESS(hipHostMalloc(&ptr, size, hipHostMallocPortable));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaHostAlloc(&ptr, size, cudaHostAllocPortable));
PADDLE_ENFORCE_GPU_SUCCESS(cudaHostAlloc(&ptr, size, cudaHostAllocPortable));
#endif
return new Allocation(ptr, size, platform::CUDAPinnedPlace());
}
......
paddle/fluid/memory/allocation/stream_safe_cuda_allocator.cc
浏览文件 @ a6d2fddb
......@@ -112,13 +112,13 @@ void StreamSafeCUDAAllocator::CreateEventForAllRecordedStream(
for (gpuStream_t stream : *recorded_streams) {
gpuEvent_t event;
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaEventCreateWithFlags(&event, cudaEventDisableTiming));
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event, stream));
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventRecord(event, stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipEventCreateWithFlags(&event, hipEventDisableTiming));
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventRecord(event, stream));
PADDLE_ENFORCE_GPU_SUCCESS(hipEventRecord(event, stream));
#endif
outstanding_events->emplace_back(event);
VLOG(9) << "Record event " << event << " in stream " << stream;
......@@ -162,8 +162,8 @@ void StreamSafeCUDAAllocator::ProcessEventsAndFree() {
outstanding_events.erase(outstanding_events.begin(), deque_it);
break;
}
PADDLE_ENFORCE_CUDA_SUCCESS(err);
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(*deque_it));
PADDLE_ENFORCE_GPU_SUCCESS(err);
PADDLE_ENFORCE_GPU_SUCCESS(cudaEventDestroy(*deque_it));
#else
gpuError_t err = hipEventQuery(*deque_it);
if (err == hipErrorNotReady) {
......@@ -173,8 +173,8 @@ void StreamSafeCUDAAllocator::ProcessEventsAndFree() {
outstanding_events.erase(outstanding_events.begin(), deque_it);
break;
}
PADDLE_ENFORCE_CUDA_SUCCESS(err);
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventDestroy(*deque_it));
PADDLE_ENFORCE_GPU_SUCCESS(err);
PADDLE_ENFORCE_GPU_SUCCESS(hipEventDestroy(*deque_it));
#endif
++deque_it;
}
......
paddle/fluid/memory/allocation/thread_local_allocator.h
浏览文件 @ a6d2fddb
......@@ -20,7 +20,7 @@
#include "paddle/fluid/memory/allocation/allocator.h"
#include "paddle/fluid/memory/detail/buddy_allocator.h"
#include "paddle/fluid/memory/detail/system_allocator.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
namespace paddle {
namespace memory {
......
paddle/fluid/memory/detail/buddy_allocator.h
浏览文件 @ a6d2fddb
......@@ -25,8 +25,8 @@ limitations under the License. */
#include "paddle/fluid/memory/detail/memory_block.h"
#include "paddle/fluid/memory/detail/system_allocator.h"
#include "paddle/fluid/platform/cpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/device/npu/npu_info.h"
#include "paddle/fluid/platform/gpu_info.h"
namespace paddle {
namespace memory {
......
paddle/fluid/memory/detail/buddy_allocator_test.cc
浏览文件 @ a6d2fddb
......@@ -24,8 +24,8 @@ limitations under the License. */
#include "gflags/gflags.h"
#include "gtest/gtest.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/device/npu/npu_info.h"
#include "paddle/fluid/platform/gpu_info.h"
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP) || \
defined(PADDLE_WITH_ASCEND_CL)
......
paddle/fluid/memory/detail/system_allocator.cc
浏览文件 @ a6d2fddb
......@@ -27,9 +27,9 @@ limitations under the License. */
#include "gflags/gflags.h"
#include "paddle/fluid/memory/allocation/allocator.h"
#include "paddle/fluid/platform/cpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/device/npu/npu_info.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/gpu_info.h"
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#include "paddle/fluid/platform/cuda_device_guard.h"
......@@ -115,7 +115,7 @@ void* GPUAllocator::Alloc(size_t* index, size_t size) {
if (size <= 0) return nullptr;
void* p;
auto result = platform::RecordedCudaMalloc(&p, size, gpu_id_);
auto result = platform::RecordedGpuMalloc(&p, size, gpu_id_);
if (result == gpuSuccess) {
*index = 0;
......@@ -123,7 +123,7 @@ void* GPUAllocator::Alloc(size_t* index, size_t size) {
return p;
} else {
size_t avail, total, actual_avail, actual_total;
bool is_limited = platform::RecordedCudaMemGetInfo(
bool is_limited = platform::RecordedGpuMemGetInfo(
&avail, &total, &actual_avail, &actual_total, gpu_id_);
size_t allocated = total - avail;
......@@ -166,7 +166,7 @@ void GPUAllocator::Free(void* p, size_t size, size_t index) {
size, gpu_alloc_size_));
gpu_alloc_size_ -= size;
platform::RecordedCudaFree(p, size, gpu_id_);
platform::RecordedGpuFree(p, size, gpu_id_);
}
bool GPUAllocator::UseGpu() const { return true; }
......
paddle/fluid/memory/detail/system_allocator_test.cc
浏览文件 @ a6d2fddb
......@@ -19,6 +19,9 @@ limitations under the License. */
#include "gflags/gflags.h"
#include "gtest/gtest.h"
#include "paddle/fluid/memory/allocation/allocator.h"
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#endif
DECLARE_bool(use_pinned_memory);
......@@ -77,11 +80,7 @@ TEST(GPUAllocator, AllocFailure) {
allocator.Alloc(&index, alloc_size);
ASSERT_TRUE(false);
} catch (paddle::memory::allocation::BadAlloc&) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipGetLastError());
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaGetLastError());
#endif
PADDLE_ENFORCE_GPU_SUCCESS(paddle::platform::GpuGetLastError());
}
}
#endif
......
paddle/fluid/memory/memcpy.h
浏览文件 @ a6d2fddb
......@@ -14,7 +14,7 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/place.h"
namespace paddle {
......
paddle/fluid/memory/pinned_memory_test.cu
浏览文件 @ a6d2fddb
......@@ -19,7 +19,7 @@ limitations under the License. */
#include "paddle/fluid/memory/memory.h"
#include "paddle/fluid/platform/cpu_info.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/place.h"
// This unit test is an example comparing the performance between using pinned
......
paddle/fluid/memory/stream_safe_cuda_alloc_test.cu
浏览文件 @ a6d2fddb
......@@ -26,7 +26,7 @@
#include "gtest/gtest.h"
#include "paddle/fluid/memory/malloc.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
namespace paddle {
namespace memory {
......@@ -53,9 +53,9 @@ class StreamSafeCUDAAllocTest : public ::testing::Test {
for (size_t i = 1; i < stream_num_; ++i) {
gpuStream_t stream;
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&stream));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamCreate(&stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamCreate(&stream));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamCreate(&stream));
#endif
streams_.emplace_back(stream);
}
......@@ -65,10 +65,10 @@ class StreamSafeCUDAAllocTest : public ::testing::Test {
std::shared_ptr<Allocation> allocation =
AllocShared(place_, allocation_size, streams_[i]);
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaMemset(allocation->ptr(), 0, allocation->size()));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
hipMemset(allocation->ptr(), 0, allocation->size()));
#endif
allocations_.emplace_back(allocation);
......@@ -111,13 +111,13 @@ class StreamSafeCUDAAllocTest : public ::testing::Test {
// tricky code, the allocations are still accessible even though
// allocations_.clear() has been called
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
cudaMemcpy(host_x.get(), allocations_[i]->ptr(),
data_num_ * sizeof(int), cudaMemcpyDeviceToHost));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
hipMemcpy(host_x.get(), allocations_[i]->ptr(),
data_num_ * sizeof(int), hipMemcpyDeviceToHost));
PADDLE_ENFORCE_GPU_SUCCESS(hipMemcpy(host_x.get(), allocations_[i]->ptr(),
data_num_ * sizeof(int),
hipMemcpyDeviceToHost));
#endif
for (int j = 0; j < data_num_; ++j) {
EXPECT_TRUE(host_x[j] == (j % thread_num) * stream_num_);
......@@ -127,9 +127,9 @@ class StreamSafeCUDAAllocTest : public ::testing::Test {
void TearDown() override {
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(cudaDeviceSynchronize());
PADDLE_ENFORCE_GPU_SUCCESS(cudaDeviceSynchronize());
#else
PADDLE_ENFORCE_CUDA_SUCCESS(hipDeviceSynchronize());
PADDLE_ENFORCE_GPU_SUCCESS(hipDeviceSynchronize());
#endif
for (gpuStream_t stream : streams_) {
Release(place_, stream);
......@@ -137,14 +137,14 @@ class StreamSafeCUDAAllocTest : public ::testing::Test {
for (size_t i = 1; i < stream_num_; ++i) {
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamDestroy(streams_[i]));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamDestroy(streams_[i]));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamDestroy(streams_[i]));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamDestroy(streams_[i]));
#endif
}
uint64_t cuda_malloc_size =
platform::RecordedCudaMallocSize(place_.GetDeviceId());
platform::RecordedGpuMallocSize(place_.GetDeviceId());
ASSERT_EQ(cuda_malloc_size, 0) << "Found " << cuda_malloc_size
<< " bytes memory that not released yet,"
<< " there may be a memory leak problem";
......@@ -192,11 +192,11 @@ TEST(StreamSafeCUDAAllocRetryTest, RetryTest) {
platform::CUDAPlace place = platform::CUDAPlace();
gpuStream_t stream1, stream2;
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&stream1));
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&stream2));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamCreate(&stream1));
PADDLE_ENFORCE_GPU_SUCCESS(cudaStreamCreate(&stream2));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamCreate(&stream1));
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamCreate(&stream2));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamCreate(&stream1));
PADDLE_ENFORCE_GPU_SUCCESS(hipStreamCreate(&stream2));
#endif
size_t available_size = platform::GpuAvailableMemToAlloc();
// alloc_size < available_size < 2 * alloc_size
......@@ -216,9 +216,9 @@ TEST(StreamSafeCUDAAllocRetryTest, RetryTest) {
allocation2.reset();
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE_CUDA_SUCCESS(cudaDeviceSynchronize());
PADDLE_ENFORCE_GPU_SUCCESS(cudaDeviceSynchronize());
#else
PADDLE_ENFORCE_CUDA_SUCCESS(hipDeviceSynchronize());
PADDLE_ENFORCE_GPU_SUCCESS(hipDeviceSynchronize());
#endif
Release(place, stream1);
......
paddle/fluid/operators/activation_cudnn.cu.cc
浏览文件 @ a6d2fddb
......@@ -14,11 +14,7 @@
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/activation_op.h"
#ifdef PADDLE_WITH_HIP
#include "paddle/fluid/platform/miopen_desc.h"
#else
#include "paddle/fluid/platform/cudnn_desc.h"
#endif
#include "paddle/fluid/platform/device/gpu/gpu_dnn.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/activation_cudnn_op.cu.cc
浏览文件 @ a6d2fddb
......@@ -14,11 +14,7 @@
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/activation_op.h"
#ifdef PADDLE_WITH_HIP
#include "paddle/fluid/platform/miopen_desc.h"
#else
#include "paddle/fluid/platform/cudnn_desc.h"
#endif
#include "paddle/fluid/platform/device/gpu/gpu_dnn.h"
namespace paddle {
namespace platform {
......@@ -64,13 +60,13 @@ struct CudnnActivationFunctor {
x_desc.set(x);
out_desc.set(GET_DATA_SAFELY(out, "Output", "Out", "CudnnActivation"));
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::miopenActivationForward(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::miopenActivationForward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), x_desc.desc(), x.data<T>(),
platform::CudnnDataType<T>::kZero(), out_desc.desc(),
out->mutable_data<T>(ctx_.GetPlace())));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::cudnnActivationForward(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::cudnnActivationForward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), x_desc.desc(), x.data<T>(),
platform::CudnnDataType<T>::kZero(), out_desc.desc(),
......@@ -108,14 +104,14 @@ struct CudnnActivationGradFunctor {
dout_desc.set(dout);
dx_desc.set(GET_DATA_SAFELY(dx, "Output", "X@GRAD", "CudnnActivationGrad"));
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::miopenActivationBackward(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::miopenActivationBackward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), out_desc.desc(), out.data<T>(),
dout_desc.desc(), dout.data<T>(), x_desc.desc(), x.data<T>(),
platform::CudnnDataType<T>::kZero(), dx_desc.desc(),
dx->mutable_data<T>(ctx_.GetPlace())));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::cudnnActivationBackward(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::cudnnActivationBackward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), out_desc.desc(), out.data<T>(),
dout_desc.desc(), dout.data<T>(), x_desc.desc(), x.data<T>(),
......
paddle/fluid/operators/activation_op.cu
浏览文件 @ a6d2fddb
......@@ -14,7 +14,7 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise/elementwise_op_impl.cu.h"
#include "paddle/fluid/operators/math/math_cuda_utils.h"
#include "paddle/fluid/platform/bfloat16.h"
#include "paddle/fluid/platform/cuda_device_function.h"
#include "paddle/fluid/platform/device/gpu/gpu_device_function.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/affine_channel_op.cu
浏览文件 @ a6d2fddb
......@@ -23,7 +23,7 @@ namespace cub = hipcub;
#include "paddle/fluid/framework/data_layout.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/affine_grid_cudnn_op.cu.cc
浏览文件 @ a6d2fddb
......@@ -16,7 +16,7 @@ limitations under the License. */
// HIP not support cudnnSpatialTfGridGeneratorForward
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/cudnn_helper.h"
#include "paddle/fluid/platform/device/gpu/gpu_dnn.h"
namespace paddle {
namespace operators {
......@@ -108,7 +108,7 @@ class CUDNNAffineGridGradOpKernel : public framework::OpKernel<T> {
const T* output_grad_data = output_grad->data<T>();
T* theta_grad_data = theta_grad->mutable_data<T>(ctx.GetPlace());
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnSpatialTfGridGeneratorBackward(
handle, cudnn_st_desc, output_grad_data, theta_grad_data));
}
......
paddle/fluid/operators/affine_grid_op.cc
浏览文件 @ a6d2fddb
......@@ -18,12 +18,7 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/cudnn_helper.h"
#endif
#ifdef PADDLE_WITH_HIP
#include "paddle/fluid/platform/miopen_helper.h"
#endif
#include "paddle/fluid/platform/device/gpu/gpu_dnn.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/affine_grid_op.cu
浏览文件 @ a6d2fddb
......@@ -14,9 +14,9 @@ limitations under the License. */
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/affine_grid_op.h"
#include "paddle/fluid/platform/cuda_device_function.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_device_function.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/argsort_op.cu
浏览文件 @ a6d2fddb
......@@ -26,8 +26,8 @@ namespace cub = hipcub;
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/argsort_op.h"
#include "paddle/fluid/operators/transpose_op.h"
#include "paddle/fluid/platform/cuda_device_function.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/device/gpu/gpu_device_function.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#ifdef __HIPCC__
namespace rocprim {
......@@ -169,7 +169,7 @@ void ArgFullSort(const platform::CUDADeviceContext& ctx, const Tensor* input,
num_rows, segment_offsets_t, segment_offsets_t + 1, 0, sizeof(T) * 8,
cu_stream);
}
PADDLE_ENFORCE_CUDA_SUCCESS(err);
PADDLE_ENFORCE_GPU_SUCCESS(err);
Tensor temp_storage;
temp_storage.mutable_data<uint8_t>(ctx.GetPlace(), temp_storage_bytes);
......@@ -188,7 +188,7 @@ void ArgFullSort(const platform::CUDADeviceContext& ctx, const Tensor* input,
cu_stream);
}
PADDLE_ENFORCE_CUDA_SUCCESS(err);
PADDLE_ENFORCE_GPU_SUCCESS(err);
}
template <typename T, typename IndType>
......
paddle/fluid/operators/average_accumulates_op.cu
浏览文件 @ a6d2fddb
......@@ -13,7 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/average_accumulates_op.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/batch_fc_op.cu
浏览文件 @ a6d2fddb
......@@ -16,8 +16,8 @@ limitations under the License. */
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/operators/batch_fc_op.h"
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/batch_norm_op.cu
浏览文件 @ a6d2fddb
......@@ -197,18 +197,18 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
// miopenTensorDescriptor_t bn_param_desc_;
// miopenBatchNormMode_t mode_;
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenCreateTensorDescriptor(&data_desc_));
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenCreateTensorDescriptor(&bn_param_desc_));
#else
cudnnTensorDescriptor_t data_desc_;
cudnnTensorDescriptor_t bn_param_desc_;
cudnnBatchNormMode_t mode_;
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnCreateTensorDescriptor(&data_desc_));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnCreateTensorDescriptor(&bn_param_desc_));
#endif
......@@ -251,23 +251,22 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
#ifdef PADDLE_WITH_HIP
// TODO(wangran16): wait for MIOpen to improve the performance of BN
// PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::miopenSetTensorDescriptor(
// PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::miopenSetTensorDescriptor(
// data_desc_, CudnnDataType<T>::type,
// x_dims.size() > 3 ? x_dims.size() : 4, const_cast<int *>(dims.data()),
// const_cast<int *>(strides.data())));
// Note: PERSISTENT not implemented for inference
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenDeriveBNTensorDescriptor(
// bn_param_desc_, data_desc_, test_mode ? miopenBNSpatial : mode_));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::cudnnSetTensorNdDescriptor(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::cudnnSetTensorNdDescriptor(
data_desc_, CudnnDataType<T>::type,
x_dims.size() > 3 ? x_dims.size() : 4, dims.data(), strides.data()));
// Note: PERSISTENT not implemented for inference
PADDLE_ENFORCE_CUDA_SUCCESS(
platform::dynload::cudnnDeriveBNTensorDescriptor(
bn_param_desc_, data_desc_,
test_mode ? CUDNN_BATCHNORM_SPATIAL : mode_));
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::cudnnDeriveBNTensorDescriptor(
bn_param_desc_, data_desc_,
test_mode ? CUDNN_BATCHNORM_SPATIAL : mode_));
#endif
const auto *scale = ctx.Input<Tensor>("Scale");
......@@ -341,7 +340,7 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
}
// TODO(wangran16): wait for MIOpen to improve the performance of BN
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenBatchNormalizationForwardInference(
// handle, miopenBNSpatial,
// const_cast<void *>(
......@@ -364,7 +363,7 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
// est_var->template data<BatchNormParamType<T>>())),
// epsilon));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnBatchNormalizationForwardInference(
handle,
// Note: PERSISTENT not implemented for inference
......@@ -426,7 +425,7 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
"The argument ReserveSpace of batch_norm op is not found."));
// --------------- cudnn batchnorm workspace ---------------
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::
cudnnGetBatchNormalizationForwardTrainingExWorkspaceSize(
/*handle=*/handle,
......@@ -440,7 +439,7 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
/*sizeInBytes=*/&workspace_size));
// -------------- cudnn batchnorm reserve space --------------
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::
cudnnGetBatchNormalizationTrainingExReserveSpaceSize(
/*handle=*/handle,
......@@ -454,7 +453,7 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
ctx.GetPlace(), transformed_x.type(), reserve_space_size);
workspace_ptr = workspace_tensor.mutable_data(
ctx.GetPlace(), transformed_x.type(), workspace_size);
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnBatchNormalizationForwardTrainingEx(
handle, mode_, CUDNN_BATCHNORM_OPS_BN, CudnnDataType<T>::kOne(),
CudnnDataType<T>::kZero(), data_desc_,
......@@ -508,7 +507,7 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
}
// TODO(wangran16): wait for MIOpen to improve the performance of BN
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenBatchNormalizationForwardTraining(
// handle, mode_, const_cast<void *>(static_cast<const void *>(
// CudnnDataType<T>::kOne())),
......@@ -537,7 +536,7 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
// static_cast<void *>(saved_variance->template mutable_data<
// BatchNormParamType<T>>(ctx.GetPlace()))));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnBatchNormalizationForwardTraining(
handle, mode_, CudnnDataType<T>::kOne(),
CudnnDataType<T>::kZero(), data_desc_,
......@@ -568,15 +567,15 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
#ifdef PADDLE_WITH_HIP
// TODO(wangran16): wait for MIOpen to improve the performance of BN
// clean when exit.
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenDestroyTensorDescriptor(data_desc_));
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenDestroyTensorDescriptor(bn_param_desc_));
#else
// clean when exit.
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnDestroyTensorDescriptor(data_desc_));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnDestroyTensorDescriptor(bn_param_desc_));
#endif
}
......@@ -981,18 +980,18 @@ class BatchNormGradKernel<platform::CUDADeviceContext, T>
// miopenTensorDescriptor_t bn_param_desc_;
// miopenBatchNormMode_t mode_;
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenCreateTensorDescriptor(&data_desc_));
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenCreateTensorDescriptor(&bn_param_desc_));
#else
cudnnTensorDescriptor_t data_desc_;
cudnnTensorDescriptor_t bn_param_desc_;
cudnnBatchNormMode_t mode_;
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnCreateTensorDescriptor(&data_desc_));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnCreateTensorDescriptor(&bn_param_desc_));
#endif
if (epsilon <= CUDNN_BN_MIN_EPSILON - FLT_EPSILON) {
......@@ -1022,18 +1021,18 @@ class BatchNormGradKernel<platform::CUDADeviceContext, T>
#ifdef PADDLE_WITH_HIP
// TODO(wangran16): wait for MIOpen to improve the performance of BN
// PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::miopenSetTensorDescriptor(
// PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::miopenSetTensorDescriptor(
// data_desc_, CudnnDataType<T>::type,
// x_dims.size() > 3 ? x_dims.size() : 4, const_cast<int *>(dims.data()),
// const_cast<int *>(strides.data())));
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenDeriveBNTensorDescriptor(bn_param_desc_,
// data_desc_, mode_));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::cudnnSetTensorNdDescriptor(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::cudnnSetTensorNdDescriptor(
data_desc_, CudnnDataType<T>::type,
x_dims.size() > 3 ? x_dims.size() : 4, dims.data(), strides.data()));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnDeriveBNTensorDescriptor(bn_param_desc_,
data_desc_, mode_));
#endif
......@@ -1063,7 +1062,7 @@ class BatchNormGradKernel<platform::CUDADeviceContext, T>
Tensor workspace_tensor;
auto reserve_space_size = reserve_space->memory_size();
// --------------- cudnn batchnorm workspace ---------------
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::
cudnnGetBatchNormalizationBackwardExWorkspaceSize(
/*handle=*/dev_ctx.cudnn_handle(),
......@@ -1081,7 +1080,7 @@ class BatchNormGradKernel<platform::CUDADeviceContext, T>
workspace_ptr = workspace_tensor.mutable_data(
ctx.GetPlace(), transformed_x.type(), workspace_size);
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnBatchNormalizationBackwardEx(
/*handle=*/dev_ctx.cudnn_handle(),
/*mode=*/mode_,
......@@ -1151,7 +1150,7 @@ class BatchNormGradKernel<platform::CUDADeviceContext, T>
}
// TODO(wangran16): wait for MIOpen to improve the performance of BN
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenBatchNormalizationBackward(
// dev_ctx.cudnn_handle(), mode_, CudnnDataType<T>::kOne(),
// CudnnDataType<T>::kZero(), CudnnDataType<T>::kOne(),
......@@ -1166,7 +1165,7 @@ class BatchNormGradKernel<platform::CUDADeviceContext, T>
// ctx.GetPlace()),
// epsilon, saved_mean_data, saved_var_data));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnBatchNormalizationBackward(
dev_ctx.cudnn_handle(), mode_, CudnnDataType<T>::kOne(),
CudnnDataType<T>::kZero(), CudnnDataType<T>::kOne(),
......@@ -1231,15 +1230,15 @@ class BatchNormGradKernel<platform::CUDADeviceContext, T>
#ifdef PADDLE_WITH_HIP
// TODO(wangran16): wait for MIOpen to improve the performance of BN
// clean when exit.
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenDestroyTensorDescriptor(data_desc_));
// PADDLE_ENFORCE_CUDA_SUCCESS(
// PADDLE_ENFORCE_GPU_SUCCESS(
// platform::dynload::miopenDestroyTensorDescriptor(bn_param_desc_));
#else
// clean when exit.
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnDestroyTensorDescriptor(data_desc_));
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
platform::dynload::cudnnDestroyTensorDescriptor(bn_param_desc_));
#endif
} else {
......
paddle/fluid/operators/bce_loss_op.cu
浏览文件 @ a6d2fddb
......@@ -14,8 +14,8 @@ limitations under the License. */
#include <algorithm>
#include "paddle/fluid/operators/bce_loss_op.h"
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/gpu_launch_config.h"
#include "paddle/fluid/platform/device/gpu/gpu_launch_config.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
namespace paddle {
......
paddle/fluid/operators/bilateral_slice_op.cu
浏览文件 @ a6d2fddb
......@@ -12,8 +12,8 @@
#include <algorithm>
#include <string>
#include "paddle/fluid/operators/bilateral_slice_op.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/gpu_launch_config.h"
#include "paddle/fluid/platform/device/gpu/gpu_launch_config.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/bincount_op.cu
浏览文件 @ a6d2fddb
......@@ -14,8 +14,8 @@ limitations under the License. */
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/operators/bincount_op.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/gpu_launch_config.h"
#include "paddle/fluid/platform/device/gpu/gpu_launch_config.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
namespace paddle {
......
paddle/fluid/operators/cast_op.cu
浏览文件 @ a6d2fddb
......@@ -14,8 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/cast_op.h"
#include "paddle/fluid/platform/aligned_vector.h"
#include "paddle/fluid/platform/device/gpu/gpu_launch_config.h"
#include "paddle/fluid/platform/float16.h"
#include "paddle/fluid/platform/gpu_launch_config.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/center_loss_op.cu
浏览文件 @ a6d2fddb
......@@ -14,8 +14,8 @@ limitations under the License. */
#include <iostream>
#include "paddle/fluid/operators/center_loss_op.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/cholesky_op.cu
浏览文件 @ a6d2fddb
......@@ -131,27 +131,26 @@ class CholeskyGPUKernel : public framework::OpKernel<T> {
int lda, int* info) const { \
auto handle = dev_ctx.cusolver_dn_handle(); \
int workspace_size = 0; \
PADDLE_ENFORCE_CUDA_SUCCESS( \
PADDLE_ENFORCE_GPU_SUCCESS( \
platform::dynload::cusolverDn##C##potrf_bufferSize( \
handle, uplo, n, A, lda, &workspace_size)); \
auto workspace = memory::Alloc(dev_ctx, workspace_size); \
T* workspace_ptr = reinterpret_cast<T*>(workspace->ptr()); \
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::cusolverDn##C##potrf( \
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::cusolverDn##C##potrf( \
handle, uplo, n, A, lda, workspace_ptr, workspace_size, info)); \
}
FUNC_WITH_TYPES(POTRF_INSTANCE);
#if CUDA_VERSION >= 9020 && !defined(_WIN32)
#define POTRF_BATCH_INSTANCE(T, C) \
template <> \
void CholeskyGPUKernel<T>::PotrfBatched( \
const platform::CUDADeviceContext& dev_ctx, cublasFillMode_t uplo, \
int n, T* Aarray[], int lda, int* info_array, int batch_size) const { \
auto handle = dev_ctx.cusolver_dn_handle(); \
PADDLE_ENFORCE_CUDA_SUCCESS( \
platform::dynload::cusolverDn##C##potrfBatched( \
handle, uplo, n, Aarray, lda, info_array, batch_size)); \
#define POTRF_BATCH_INSTANCE(T, C) \
template <> \
void CholeskyGPUKernel<T>::PotrfBatched( \
const platform::CUDADeviceContext& dev_ctx, cublasFillMode_t uplo, \
int n, T* Aarray[], int lda, int* info_array, int batch_size) const { \
auto handle = dev_ctx.cusolver_dn_handle(); \
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::cusolverDn##C##potrfBatched( \
handle, uplo, n, Aarray, lda, info_array, batch_size)); \
}
FUNC_WITH_TYPES(POTRF_BATCH_INSTANCE);
......
paddle/fluid/operators/cinn_launch_op.cu.cc
浏览文件 @ a6d2fddb
......@@ -18,9 +18,9 @@ limitations under the License. */
#include "cinn/runtime/cinn_runtime.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/platform/device/gpu/gpu_types.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/type_defs.h"
#ifdef PADDLE_WITH_CUDA
#include <cuda_runtime.h>
......@@ -45,9 +45,9 @@ void CUDART_CB ReleaseBuffers(void* data) {
template <>
void ReleaseResource<platform::CUDADeviceContext>(
const std::vector<void*>& resources, void* stream) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaLaunchHostFunc(
PADDLE_ENFORCE_GPU_SUCCESS(cudaLaunchHostFunc(
static_cast<gpuStream_t>(stream), ReleaseScope, resources[0]));
PADDLE_ENFORCE_CUDA_SUCCESS(cudaLaunchHostFunc(
PADDLE_ENFORCE_GPU_SUCCESS(cudaLaunchHostFunc(
static_cast<gpuStream_t>(stream), ReleaseBuffers, resources[1]));
}
......
paddle/fluid/operators/class_center_sample_op.cu
浏览文件 @ a6d2fddb
......@@ -30,7 +30,7 @@ namespace cub = hipcub;
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/collective_helper.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
namespace paddle {
......@@ -335,7 +335,7 @@ class ClassCenterSampleCUDAKernel : public framework::OpKernel<T> {
static_cast<platform::CUDADeviceContext*>(
platform::DeviceContextPool::Instance().Get(ctx.GetPlace()))
->stream();
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllReduce(
num_classes_per_device_ptr, num_classes_per_device_ptr,
num_classes_per_device.numel(),
platform::ToNCCLDataType(num_classes_per_device.type()), ncclSum,
......@@ -346,13 +346,13 @@ class ClassCenterSampleCUDAKernel : public framework::OpKernel<T> {
// step 2: Determine temporary device storage requirements
int num_buffer_ele = std::max(batch_size, num_classes);
size_t cub_sort_temp_store_size = 0;
PADDLE_ENFORCE_CUDA_SUCCESS((cub::DeviceRadixSort::SortPairs<T, T>(
PADDLE_ENFORCE_GPU_SUCCESS((cub::DeviceRadixSort::SortPairs<T, T>(
nullptr, cub_sort_temp_store_size, nullptr, nullptr, nullptr, nullptr,
num_buffer_ele, 0, sizeof(T) * 8, ctx.cuda_device_context().stream())));
size_t cub_sum_temp_store_size = 0;
NotEqualToPreviousAdjacentIterator<T> unique_counting_iter_temp(nullptr, 0);
PADDLE_ENFORCE_CUDA_SUCCESS(
PADDLE_ENFORCE_GPU_SUCCESS(
(cub::DeviceScan::InclusiveSum<NotEqualToPreviousAdjacentIterator<T>,
T*>(
nullptr, cub_sum_temp_store_size, unique_counting_iter_temp,
......@@ -360,7 +360,7 @@ class ClassCenterSampleCUDAKernel : public framework::OpKernel<T> {
size_t cub_scan_temp_store_size = 0;
ActualNumSampledFunctor<T> actual_num_sampled_op_temp(num_samples);
PADDLE_ENFORCE_CUDA_SUCCESS((cub::DeviceScan::InclusiveScan(
PADDLE_ENFORCE_GPU_SUCCESS((cub::DeviceScan::InclusiveScan(
nullptr, cub_scan_temp_store_size, num_classes_per_device_ptr,
num_classes_per_device_ptr, actual_num_sampled_op_temp, nranks + 1,
ctx.cuda_device_context().stream())));
......@@ -384,7 +384,7 @@ class ClassCenterSampleCUDAKernel : public framework::OpKernel<T> {
void* cub_temp_storage_ptr = memory_buffer.cub_temp_storage_ptr();
// step 4: Calculate class interval among nranks
PADDLE_ENFORCE_CUDA_SUCCESS((cub::DeviceScan::InclusiveSum(
PADDLE_ENFORCE_GPU_SUCCESS((cub::DeviceScan::InclusiveSum(
cub_temp_storage_ptr, cub_temp_storage_bytes,
num_classes_per_device_ptr, class_interval_ptr, nranks + 1,
ctx.cuda_device_context().stream())));
......@@ -415,13 +415,13 @@ class ClassCenterSampleCUDAKernel : public framework::OpKernel<T> {
// step 7: sort class center by ascending, so that positive class center
// always be sampled.
PADDLE_ENFORCE_CUDA_SUCCESS((cub::DeviceRadixSort::SortPairs<T, T>(
PADDLE_ENFORCE_GPU_SUCCESS((cub::DeviceRadixSort::SortPairs<T, T>(
cub_temp_storage_ptr, cub_temp_storage_bytes, cub_sort_keys_ptr,
cub_sort_keys_out_ptr, cub_sort_values_ptr, cub_sort_values_out_ptr,
num_classes, 0, sizeof(T) * 8, ctx.cuda_device_context().stream())));
// step 8: sort input label ascending
PADDLE_ENFORCE_CUDA_SUCCESS((cub::DeviceRadixSort::SortPairs<T, T>(
PADDLE_ENFORCE_GPU_SUCCESS((cub::DeviceRadixSort::SortPairs<T, T>(
cub_temp_storage_ptr, cub_temp_storage_bytes, label->data<T>(),
cub_sort_keys_out_ptr, cub_sort_values_ptr, cub_sort_keys_ptr,
batch_size, 0, sizeof(T) * 8, ctx.cuda_device_context().stream())));
......@@ -430,8 +430,8 @@ class ClassCenterSampleCUDAKernel : public framework::OpKernel<T> {
// label
NotEqualToPreviousAdjacentIterator<T> unique_counting_iter(
cub_sort_keys_out_ptr, 0);
PADDLE_ENFORCE_CUDA_SUCCESS((cub::DeviceScan::InclusiveSum<
NotEqualToPreviousAdjacentIterator<T>, T*>(
PADDLE_ENFORCE_GPU_SUCCESS((cub::DeviceScan::InclusiveSum<
NotEqualToPreviousAdjacentIterator<T>, T*>(
cub_temp_storage_ptr, cub_temp_storage_bytes, unique_counting_iter,
cub_sort_values_ptr, batch_size, ctx.cuda_device_context().stream())));
......@@ -445,13 +445,13 @@ class ClassCenterSampleCUDAKernel : public framework::OpKernel<T> {
// Since maybe num_positive_class_center > num_samples,
// we need to ensure all positive class center per device are sampled.
ActualNumSampledFunctor<T> actual_num_sampled_op(num_samples);
PADDLE_ENFORCE_CUDA_SUCCESS((cub::DeviceScan::InclusiveScan(
PADDLE_ENFORCE_GPU_SUCCESS((cub::DeviceScan::InclusiveScan(
cub_temp_storage_ptr, cub_temp_storage_bytes, bound_value_ptr,
num_classes_per_device_ptr, actual_num_sampled_op, nranks + 1,
ctx.cuda_device_context().stream())));
// step 12: Calculate actual sampled class interval among nranks
PADDLE_ENFORCE_CUDA_SUCCESS((cub::DeviceScan::InclusiveSum(
PADDLE_ENFORCE_GPU_SUCCESS((cub::DeviceScan::InclusiveSum(
cub_temp_storage_ptr, cub_temp_storage_bytes,
num_classes_per_device_ptr, class_interval_ptr, nranks + 1,
ctx.cuda_device_context().stream())));
......
paddle/fluid/operators/collective/allreduce_op.h
浏览文件 @ a6d2fddb
......@@ -22,7 +22,7 @@ limitations under the License. */
#include "paddle/fluid/framework/op_registry.h"
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
namespace paddle {
......@@ -69,15 +69,11 @@ class AllReduceOpKernel : public framework::OpKernel<T> {
red_type = ncclMin;
break;
}
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllReduce(
sendbuff, recvbuff, numel, static_cast<ncclDataType_t>(dtype), red_type,
comm, stream));
if (ctx.Attr<bool>("sync_mode")) {
#ifdef PADDLE_WITH_RCCL
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
#endif
platform::GpuStreamSync(stream);
}
#else
PADDLE_THROW(platform::errors::PreconditionNotMet(
......
paddle/fluid/operators/collective/alltoall_op.cu.cc
浏览文件 @ a6d2fddb
......@@ -16,7 +16,7 @@ limitations under the License. */
#if defined(PADDLE_WITH_NCCL)
#include "paddle/fluid/platform/collective_helper.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
namespace paddle {
......@@ -62,15 +62,15 @@ class AllToAllOpCUDAKernel : public framework::OpKernel<T> {
auto recv_buf = out->mutable_data<T>(out_dims, place);
size_t offset = 0;
send_numel /= nranks;
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupStart());
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupStart());
for (auto i = 0; i < nranks; ++i) {
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclSend(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclSend(
send_buf + offset, send_numel, dtype, i, comm->comm(), stream));
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclRecv(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclRecv(
recv_buf + offset, send_numel, dtype, i, comm->comm(), stream));
offset += send_numel;
}
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupEnd());
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclGroupEnd());
#else
PADDLE_THROW(
platform::errors::Unavailable("NCCL version >= 2.7.3 is needed."));
......
paddle/fluid/operators/collective/barrier_op.cu.cc
浏览文件 @ a6d2fddb
......@@ -16,7 +16,7 @@ limitations under the License. */
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include "paddle/fluid/platform/collective_helper.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/device/gpu/nccl_helper.h"
#endif
namespace paddle {
......@@ -41,13 +41,9 @@ class BarrierOpCUDAKernel : public framework::OpKernel<T> {
auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
auto stream = static_cast<platform::CUDADeviceContext*>(dev_ctx)->stream();
ncclRedOp_t nccl_red_type = ncclSum;
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclAllReduce(
sendbuff, recvbuff, numel, dtype, nccl_red_type, comm->comm(), stream));
#ifdef PADDLE_WITH_RCCL
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
#endif
platform::GpuStreamSync(stream);
#else
PADDLE_THROW(platform::errors::Unavailable(
"PaddlePaddle should compile with NCCL."));
......
paddle/fluid/operators/conv_op.cc
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paddle/fluid/operators/cvm_op.cu
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paddle/fluid/operators/gather.cu.h
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paddle/fluid/operators/math/prelu.h
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paddle/fluid/operators/mean_op.cu
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paddle/fluid/operators/mish_op.cu
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paddle/fluid/operators/mv_op.cu
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paddle/fluid/operators/pad2d_op.cu
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paddle/fluid/operators/pad3d_op.cu
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paddle/fluid/operators/pool_op.cc
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paddle/fluid/operators/prelu_op.cu
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paddle/fluid/operators/qr_op.cu
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paddle/fluid/operators/range_op.cu
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paddle/fluid/operators/trunc_op.cu
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paddle/fluid/platform/device/gpu/gpu_helper.h 0 → 100644
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paddle/fluid/platform/device/gpu/gpu_types.h 0 → 100644
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paddle/fluid/platform/device/gpu/rocm/CMakeLists.txt 0 → 100644
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paddle/fluid/platform/enforce.h
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paddle/fluid/platform/init_test.cc
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