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未验证 提交 a60d93fb 编写于 作者: Q Qi Li 提交者： GitHub
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[ROCM] update fluid framework for rocm (part2), test=develop (#31010)

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Showing with 144 addition and 53 deletion
paddle/fluid/framework/fleet/CMakeLists.txt
浏览文件 @ a60d93fb
......@@ -4,6 +4,10 @@ if(WITH_PSLIB)
nv_library(ps_gpu_wrapper SRCS ps_gpu_wrapper.cu ps_gpu_wrapper.cc
DEPS heter_ps)
add_subdirectory(heter_ps)
elseif(WITH_RCCL)
hip_library(ps_gpu_wrapper SRCS ps_gpu_wrapper.cu ps_gpu_wrapper.cc
DEPS heter_ps)
add_subdirectory(heter_ps)
else()
cc_library(ps_gpu_wrapper SRCS ps_gpu_wrapper.cc)
endif(WITH_NCCL)
......@@ -12,11 +16,16 @@ else()
cc_library(ps_gpu_wrapper SRCS ps_gpu_wrapper.cc)
endif(WITH_PSLIB)
if(WITH_NCCL)
if(WITH_NCCL OR WITH_RCCL)
cc_library(nccl_wrapper SRCS nccl_wrapper.cc DEPS framework_proto variable_helper scope)
endif()
if(WITH_BOX_PS)
if(WITH_GPU)
nv_library(box_wrapper SRCS box_wrapper.cc box_wrapper.cu DEPS framework_proto lod_tensor box_ps)
endif()
if(WITH_ROCM)
hip_library(box_wrapper SRCS box_wrapper.cc box_wrapper.cu DEPS framework_proto lod_tensor box_ps)
endif()
else()
cc_library(box_wrapper SRCS box_wrapper.cc DEPS framework_proto lod_tensor)
endif(WITH_BOX_PS)
......
paddle/fluid/framework/fleet/box_wrapper.cc
浏览文件 @ a60d93fb
......@@ -25,7 +25,7 @@ namespace paddle {
namespace framework {
std::shared_ptr<BoxWrapper> BoxWrapper::s_instance_ = nullptr;
cudaStream_t BoxWrapper::stream_list_[8];
gpuStream_t BoxWrapper::stream_list_[8];
std::shared_ptr<boxps::BoxPSBase> BoxWrapper::boxps_ptr_ = nullptr;
AfsManager* BoxWrapper::afs_manager = nullptr;
int BoxWrapper::embedx_dim_ = 8;
......
paddle/fluid/framework/fleet/box_wrapper.cu
浏览文件 @ a60d93fb
......@@ -142,8 +142,13 @@ void BoxWrapper::CopyForPull(const paddle::platform::Place& place,
->stream();
auto buf_value = memory::AllocShared(place, values.size() * sizeof(float*));
float** gpu_values = reinterpret_cast<float**>(buf_value->ptr());
#ifdef PADDLE_WITH_HIP
hipMemcpy(gpu_values, values.data(), values.size() * sizeof(float*),
hipMemcpyHostToDevice);
#else
cudaMemcpy(gpu_values, values.data(), values.size() * sizeof(float*),
cudaMemcpyHostToDevice);
#endif
#define EMBEDX_CASE(i, ...) \
case i: { \
constexpr size_t EmbedxDim = i; \
......@@ -155,6 +160,19 @@ void BoxWrapper::CopyForPull(const paddle::platform::Place& place,
} \
} break
#ifdef PADDLE_WITH_HIP
#define EXPAND_EMBED_PUSH_CASE(i, ...) \
case i: { \
constexpr size_t ExpandDim = i; \
hipLaunchKernelGGL( \
PushCopy<EmbedxDim, ExpandDim>, dim3((total_length + 512 - 1) / 512), \
dim3(512), 0, stream, gpu_values, \
reinterpret_cast<boxps::FeatureValueGpu<EmbedxDim, ExpandDim>*>( \
total_values_gpu), \
gpu_len, hidden_size, expand_embed_dim, slot_num, total_length, \
gpu_keys); \
} break
#else
#define EXPAND_EMBED_PULL_CASE(i, ...) \
case i: { \
constexpr size_t ExpandDim = i; \
......@@ -166,6 +184,7 @@ void BoxWrapper::CopyForPull(const paddle::platform::Place& place,
gpu_len, hidden_size, expand_embed_dim, slot_num, total_length, \
gpu_keys); \
} break
#endif
switch (hidden_size - 3) {
EMBEDX_CASE(8, EXPAND_EMBED_PULL_CASE(0); EXPAND_EMBED_PULL_CASE(8);
......@@ -187,9 +206,16 @@ void BoxWrapper::CopyKeys(const paddle::platform::Place& place,
platform::DeviceContextPool::Instance().Get(
BOOST_GET_CONST(platform::CUDAPlace, place)))
->stream();
#ifdef PADDLE_WITH_HIP
hipLaunchKernelGGL(CopyKeysKernel, dim3((total_len + 512 - 1) / 512),
dim3(512), 0, stream, origin_keys, total_keys, gpu_len,
slot_num, total_len);
hipStreamSynchronize(stream);
#else
CopyKeysKernel<<<(total_len + 512 - 1) / 512, 512, 0, stream>>>(
origin_keys, total_keys, gpu_len, slot_num, total_len);
cudaStreamSynchronize(stream);
#endif
}
void BoxWrapper::CopyForPush(const paddle::platform::Place& place,
......@@ -217,12 +243,21 @@ void BoxWrapper::CopyForPush(const paddle::platform::Place& place,
int64_t* gpu_len = reinterpret_cast<int64_t*>(buf_length->ptr());
int* d_slot_vector = reinterpret_cast<int*>(buf_slot_vector->ptr());
#ifdef PADDLE_WITH_HIP
hipMemcpy(gpu_values, grad_values.data(), grad_values.size() * sizeof(float*),
hipMemcpyHostToDevice);
hipMemcpy(gpu_len, slot_lengths_lod.data(),
slot_lengths.size() * sizeof(int64_t), hipMemcpyHostToDevice);
hipMemcpy(d_slot_vector, slot_vector_.data(),
slot_lengths_lod.size() * sizeof(int), hipMemcpyHostToDevice);
#else
cudaMemcpy(gpu_values, grad_values.data(),
grad_values.size() * sizeof(float*), cudaMemcpyHostToDevice);
cudaMemcpy(gpu_len, slot_lengths_lod.data(),
slot_lengths.size() * sizeof(int64_t), cudaMemcpyHostToDevice);
cudaMemcpy(d_slot_vector, slot_vector_.data(),
slot_lengths_lod.size() * sizeof(int), cudaMemcpyHostToDevice);
#endif
#define EMBEDX_CASE(i, ...) \
case i: { \
......@@ -235,6 +270,18 @@ void BoxWrapper::CopyForPush(const paddle::platform::Place& place,
} \
} break
#ifdef PADDLE_WITH_HIP
#define EXPAND_EMBED_PUSH_CASE(i, ...) \
case i: { \
constexpr size_t ExpandDim = i; \
hipLaunchKernelGGL(PushCopy<EmbedxDim, ExpandDim>, \
dim3(total_length + 512 - 1) / 512), dim3(512), 0, stream, \
reinterpret_cast<boxps::FeaturePushValueGpu<EmbedxDim, ExpandDim>*>( \
total_grad_values_gpu), \
gpu_values, gpu_len, hidden_size, expand_embed_dim, \
slot_lengths.size(), total_length, batch_size, d_slot_vector); \
} break
#else
#define EXPAND_EMBED_PUSH_CASE(i, ...) \
case i: { \
constexpr size_t ExpandDim = i; \
......@@ -245,6 +292,7 @@ void BoxWrapper::CopyForPush(const paddle::platform::Place& place,
gpu_values, gpu_len, hidden_size, expand_embed_dim, \
slot_lengths.size(), total_length, batch_size, d_slot_vector); \
} break
#endif
switch (hidden_size - 3) {
EMBEDX_CASE(8, EXPAND_EMBED_PUSH_CASE(0); EXPAND_EMBED_PUSH_CASE(8);
......
paddle/fluid/framework/fleet/box_wrapper.h
浏览文件 @ a60d93fb
......@@ -396,7 +396,7 @@ class BoxWrapper {
const std::string& model_path) {
if (nullptr != s_instance_) {
VLOG(3) << "Begin InitializeGPU";
std::vector<cudaStream_t*> stream_list;
std::vector<gpuStream_t*> stream_list;
for (int i = 0; i < platform::GetCUDADeviceCount(); ++i) {
VLOG(3) << "before get context i[" << i << "]";
platform::CUDADeviceContext* context =
......@@ -542,8 +542,12 @@ class BoxWrapper {
auto* gpu_data = gpu_tensor.data<T>();
auto len = gpu_tensor.numel();
data->resize(len);
#ifdef PADDLE_WITH_HIP
hipMemcpy(data->data(), gpu_data, sizeof(T) * len, hipMemcpyDeviceToHost);
#else
cudaMemcpy(data->data(), gpu_data, sizeof(T) * len,
cudaMemcpyDeviceToHost);
#endif
}
static inline std::pair<int, int> parse_cmatch_rank(uint64_t x) {
// first 32 bit store cmatch and second 32 bit store rank
......@@ -819,7 +823,7 @@ class BoxWrapper {
}
private:
static cudaStream_t stream_list_[8];
static gpuStream_t stream_list_[8];
static std::shared_ptr<boxps::BoxPSBase> boxps_ptr_;
boxps::PSAgentBase* p_agent_ = nullptr;
// TODO(hutuxian): magic number, will add a config to specify
......
paddle/fluid/framework/fleet/box_wrapper_impl.h
浏览文件 @ a60d93fb
......@@ -43,7 +43,7 @@ void BoxWrapper::PullSparseCase(const paddle::platform::Place& place,
PADDLE_THROW(platform::errors::Unimplemented(
"Warning:: CPUPlace is not supported in PaddleBox now."));
} else if (platform::is_gpu_place(place)) {
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
#if (defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)) && !defined(_WIN32)
VLOG(3) << "Begin copy keys, key_num[" << total_length << "]";
int device_id = BOOST_GET_CONST(platform::CUDAPlace, place).GetDeviceId();
LoDTensor& total_keys_tensor = keys_tensor[device_id];
......@@ -60,11 +60,17 @@ void BoxWrapper::PullSparseCase(const paddle::platform::Place& place,
memory::AllocShared(place, slot_lengths.size() * sizeof(int64_t));
uint64_t** gpu_keys = reinterpret_cast<uint64_t**>(buf_key->ptr());
int64_t* gpu_len = reinterpret_cast<int64_t*>(buf_length->ptr());
#ifdef PADDLE_WITH_HIP
hipMemcpy(gpu_keys, keys.data(), keys.size() * sizeof(uint64_t*),
hipMemcpyHostToDevice);
hipMemcpy(gpu_len, slot_lengths_lod.data(),
slot_lengths.size() * sizeof(int64_t), hipMemcpyHostToDevice);
#else
cudaMemcpy(gpu_keys, keys.data(), keys.size() * sizeof(uint64_t*),
cudaMemcpyHostToDevice);
cudaMemcpy(gpu_len, slot_lengths_lod.data(),
slot_lengths.size() * sizeof(int64_t), cudaMemcpyHostToDevice);
#endif
this->CopyKeys(place, gpu_keys, total_keys, gpu_len,
static_cast<int>(slot_lengths.size()),
static_cast<int>(total_length));
......@@ -124,7 +130,7 @@ void BoxWrapper::PushSparseGradCase(
PADDLE_THROW(platform::errors::Unimplemented(
"Warning:: CPUPlace is not supported in PaddleBox now."));
} else if (platform::is_gpu_place(place)) {
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
#if (defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)) && !defined(_WIN32)
int device_id = BOOST_GET_CONST(platform::CUDAPlace, place).GetDeviceId();
LoDTensor& cached_total_keys_tensor = keys_tensor[device_id];
uint64_t* total_keys =
......
paddle/fluid/framework/fleet/fleet_wrapper.cc
浏览文件 @ a60d93fb
......@@ -698,13 +698,14 @@ void FleetWrapper::PushDenseVarsSync(
Scope* scope, const uint64_t table_id,
const std::vector<std::string>& var_names) {}
#if (defined PADDLE_WITH_CUDA) && (defined PADDLE_WITH_PSLIB)
#if (defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)) && \
(defined PADDLE_WITH_PSLIB)
void FleetWrapper::PushDenseVarsAsync(
const Scope& scope, const uint64_t table_id,
const std::vector<std::string>& var_names,
std::vector<::std::future<int32_t>>* push_sparse_status,
float scale_datanorm, int batch_size, const paddle::platform::Place& place,
cudaStream_t stream, cudaEvent_t event) {
gpuStream_t stream, gpuEvent_t event) {
std::vector<paddle::ps::Region> regions;
for (auto& t : var_names) {
Variable* var = scope.FindVar(t);
......@@ -719,8 +720,13 @@ void FleetWrapper::PushDenseVarsAsync(
memory::Copy(platform::CUDAPinnedPlace(), pin_g,
BOOST_GET_CONST(platform::CUDAPlace, place), g_data,
sizeof(float) * count, stream);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipEventRecord(event, stream));
hipEventSynchronize(event);
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event, stream));
cudaEventSynchronize(event);
#endif
float* g = pin_g;
if (scale_datanorm >= 0) {
......
paddle/fluid/framework/fleet/fleet_wrapper.h
浏览文件 @ a60d93fb
......@@ -152,14 +152,14 @@ class FleetWrapper {
// Push dense variables to server in async mode
// Param<in>: scope, table_id, var_names, scale_datanorm, batch_size
// Param<out>: push_sparse_status
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
void PushDenseVarsAsync(
const Scope& scope, const uint64_t table_id,
const std::vector<std::string>& var_names,
std::vector<::std::future<int32_t>>* push_sparse_status,
float scale_datanorm, int batch_size,
const paddle::platform::Place& place, cudaStream_t stream,
cudaEvent_t event);
const paddle::platform::Place& place, gpuStream_t stream,
gpuEvent_t event);
#endif
#ifdef PADDLE_WITH_XPU
void PushDenseVarsAsync(
......
paddle/fluid/framework/fleet/heter_context.h
浏览文件 @ a60d93fb
......@@ -14,7 +14,8 @@ limitations under the License. */
#pragma once
#if (defined PADDLE_WITH_NCCL) && (defined PADDLE_WITH_PSLIB)
#if (defined PADDLE_WITH_NCCL || defined PADDLE_WITH_RCCL) && \
(defined PADDLE_WITH_PSLIB)
#include <algorithm>
#include <map>
......
paddle/fluid/framework/fleet/heter_ps/CMakeLists.txt
浏览文件 @ a60d93fb
nv_library(heter_comm SRCS heter_comm.h feature_value.h heter_resource.cc
heter_resource.h hashtable.h DEPS cub device_context)
nv_test(test_heter_comm SRCS test_heter_comm.cu feature_value.h DEPS
heter_comm)
nv_library(heter_ps SRCS heter_ps.cu DEPS heter_comm)
IF(WITH_GPU)
nv_library(heter_comm SRCS heter_comm.h feature_value.h heter_resource.cc heter_resource.h hashtable.h DEPS cub device_context)
nv_test(test_heter_comm SRCS test_heter_comm.cu feature_value.h DEPS heter_comm)
nv_library(heter_ps SRCS heter_ps.cu DEPS heter_comm)
ENDIF()
IF(WITH_ROCM)
hip_library(heter_comm SRCS heter_comm.h feature_value.h heter_resource.cc heter_resource.h hashtable.h DEPS cub device_context)
hip_test(test_heter_comm SRCS test_heter_comm.cu feature_value.h DEPS heter_comm)
hip_library(heter_ps SRCS heter_ps.cu DEPS heter_comm)
ENDIF()
paddle/fluid/framework/fleet/heter_ps/hashtable.h
浏览文件 @ a60d93fb
......@@ -45,15 +45,15 @@ class HashTable {
HashTable(const HashTable&) = delete;
HashTable& operator=(const HashTable&) = delete;
void insert(const KeyType* d_keys, const ValType* d_vals, size_t len,
cudaStream_t stream);
gpuStream_t stream);
void get(const KeyType* d_keys, ValType* d_vals, size_t len,
cudaStream_t stream);
gpuStream_t stream);
void show();
void dump_to_cpu(int devid, cudaStream_t stream);
template <typename GradType, typename Sgd>
void update(const KeyType* d_keys, const GradType* d_grads, size_t len,
Sgd sgd, cudaStream_t stream);
Sgd sgd, gpuStream_t stream);
private:
TableContainer<KeyType, ValType>* container_;
......
paddle/fluid/framework/fleet/heter_ps/hashtable_inl.h
浏览文件 @ a60d93fb
......@@ -87,7 +87,7 @@ void HashTable<KeyType, ValType>::show() {
template <typename KeyType, typename ValType>
void HashTable<KeyType, ValType>::get(const KeyType* d_keys, ValType* d_vals,
size_t len, cudaStream_t stream) {
size_t len, gpuStream_t stream) {
if (len == 0) {
return;
}
......@@ -99,7 +99,7 @@ void HashTable<KeyType, ValType>::get(const KeyType* d_keys, ValType* d_vals,
template <typename KeyType, typename ValType>
void HashTable<KeyType, ValType>::insert(const KeyType* d_keys,
const ValType* d_vals, size_t len,
cudaStream_t stream) {
gpuStream_t stream) {
if (len == 0) {
return;
}
......@@ -147,7 +147,7 @@ template <typename KeyType, typename ValType>
template <typename GradType, typename Sgd>
void HashTable<KeyType, ValType>::update(const KeyType* d_keys,
const GradType* d_grads, size_t len,
Sgd sgd, cudaStream_t stream) {
Sgd sgd, gpuStream_t stream) {
if (len == 0) {
return;
}
......
paddle/fluid/framework/fleet/heter_ps/heter_comm_inl.h
浏览文件 @ a60d93fb
......@@ -25,7 +25,7 @@ __global__ void fill_idx(T* idx, size_t len) {
}
template <typename T>
void show_tensor(T* input, size_t len, cudaStream_t stream, std::string name) {
void show_tensor(T* input, size_t len, gpuStream_t stream, std::string name) {
T tmp[len];
cudaMemcpyAsync(&tmp, input, sizeof(T) * len, cudaMemcpyDeviceToHost, stream);
cudaStreamSynchronize(stream);
......@@ -270,7 +270,7 @@ void HeterComm<KeyType, ValType, GradType>::build_ps(int num, KeyType* h_keys,
std::vector<std::shared_ptr<memory::Allocation>> d_key_bufs;
std::vector<std::shared_ptr<memory::Allocation>> d_val_bufs;
cudaStream_t streams[stream_num];
gpuStream_t streams[stream_num];
for (int i = 0; i < stream_num; ++i) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&(streams[i])));
auto d_k_buf = memory::AllocShared(place, chunk_size * sizeof(KeyType));
......
paddle/fluid/framework/fleet/heter_ps/heter_resource.h
浏览文件 @ a60d93fb
......@@ -34,16 +34,16 @@ class GPUResource {
int dev_id() const { return dev_id_; }
int index() const { return index_; }
cudaStream_t local_stream(int num) { return local_streams_[num]; }
cudaStream_t remote_stream() { return remote_stream_; }
cudaStream_t comm_stream(int num) { return comm_streams_[num]; }
gpuStream_t local_stream(int num) { return local_streams_[num]; }
gpuStream_t remote_stream() { return remote_stream_; }
gpuStream_t comm_stream(int num) { return comm_streams_[num]; }
int dev_id_;
int index_;
std::vector<int> dev_ids_;
cudaStream_t remote_stream_;
std::vector<cudaStream_t> local_streams_;
std::vector<cudaStream_t> comm_streams_;
gpuStream_t remote_stream_;
std::vector<gpuStream_t> local_streams_;
std::vector<gpuStream_t> comm_streams_;
};
class HeterPsResource {
......@@ -56,9 +56,9 @@ class HeterPsResource {
int total_gpu();
int get_index_by_devid(int devid);
int dev_id(int num);
cudaStream_t local_stream(int gpu_num, int stream_num);
cudaStream_t remote_stream(int gpu_num);
cudaStream_t comm_stream(int gpu_num, int stream_num);
gpuStream_t local_stream(int gpu_num, int stream_num);
gpuStream_t remote_stream(int gpu_num);
gpuStream_t comm_stream(int gpu_num, int stream_num);
std::vector<std::shared_ptr<GPUResource>> resources_;
std::vector<int> dev_ids_;
......
paddle/fluid/framework/fleet/heter_wrapper.cc
浏览文件 @ a60d93fb
......@@ -114,7 +114,7 @@ void HeterWrapper::SerializeToReq(const std::string& varname, Scope* scope,
memcpy(data_ptr, tensor->data<void>(),
tensor->numel() * SizeOfType(tensor->type()));
} else {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
memory::Copy(platform::CPUPlace(), data_ptr,
BOOST_GET_CONST(platform::CUDAPlace, tensor->place()),
tensor->data<void>(),
......@@ -129,11 +129,11 @@ void HeterWrapper::SerializeToReq(const std::string& varname, Scope* scope,
}
}
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
void HeterWrapper::DeSerializeToTensor(Scope* scope,
const VariableMessage& req_var,
platform::Place place,
cudaStream_t stream) {
gpuStream_t stream) {
// const VariableMessage& req_var = request->vars();
auto* var = scope->FindVar(req_var.varname());
auto* tensor = var->GetMutable<LoDTensor>();
......@@ -157,7 +157,7 @@ void HeterWrapper::DeSerializeToTensor(Scope* scope,
void* tensor_data =
tensor->mutable_data(place, ToVarType(req_var.data_type()));
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
memory::Copy(BOOST_GET_CONST(platform::CUDAPlace, place), tensor_data,
platform::CPUPlace(), req_var.data().data(),
tensor->numel() * SizeOfType(tensor->type()), stream);
......
paddle/fluid/framework/fleet/heter_wrapper.h
浏览文件 @ a60d93fb
......@@ -86,9 +86,9 @@ class HeterWrapper {
framework::proto::VarType::Type ToVarType(VariableMessage::Type type);
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
void DeSerializeToTensor(Scope* scope, const VariableMessage& req_var,
platform::Place place, cudaStream_t stream);
platform::Place place, gpuStream_t stream);
#endif
void DeSerializeToTensor(Scope* scope, const VariableMessage& req_var,
platform::Place place);
......
paddle/fluid/framework/fleet/nccl_wrapper.cc
浏览文件 @ a60d93fb
......@@ -21,7 +21,7 @@ std::shared_ptr<NCCLWrapper> NCCLWrapper::s_instance_ = NULL;
bool NCCLWrapper::is_initialized_ = false;
void NCCLWrapper::InitNCCL() {
#if defined(PADDLE_WITH_NCCL)
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclCommInitRank(
&(nccl_info_.comm_), nccl_info_.global_ranks_, nccl_info_.nccl_id_,
nccl_info_.my_global_rank_));
......@@ -30,14 +30,14 @@ void NCCLWrapper::InitNCCL() {
}
void NCCLWrapper::SetNCCLId(const NCCLInfo& nccl_info) {
#if defined(PADDLE_WITH_NCCL)
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
nccl_info_.nccl_id_ = nccl_info.nccl_id_;
#endif
return;
}
NCCLInfo NCCLWrapper::GetNCCLId() {
#if defined(PADDLE_WITH_NCCL)
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
PADDLE_ENFORCE_CUDA_SUCCESS(
platform::dynload::ncclGetUniqueId(&(nccl_info_.nccl_id_)));
#endif
......@@ -46,19 +46,23 @@ NCCLInfo NCCLWrapper::GetNCCLId() {
void NCCLWrapper::SetRankInfo(const int local_rank, const int global_rank,
const int ranks) {
#if defined(PADDLE_WITH_NCCL)
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
nccl_info_.local_rank_ = local_rank;
nccl_info_.my_global_rank_ = global_rank;
nccl_info_.global_ranks_ = ranks;
platform::SetDeviceId(local_rank);
#ifdef PADDLE_WITH_RCCL
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamCreate(&(nccl_info_.stream_)));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&(nccl_info_.stream_)));
#endif
#endif
return;
}
void NCCLWrapper::SyncVar(const int root_rank, const Scope& scope,
const std::vector<std::string>& var_names) {
#if defined(PADDLE_WITH_NCCL)
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
for (auto& name : var_names) {
auto var = scope.FindVar(name);
LoDTensor* tensor = var->GetMutable<LoDTensor>();
......@@ -66,7 +70,11 @@ void NCCLWrapper::SyncVar(const int root_rank, const Scope& scope,
PADDLE_ENFORCE_CUDA_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
hipStreamSynchronize(nccl_info_.stream_);
#else
cudaStreamSynchronize(nccl_info_.stream_);
#endif
}
#endif
return;
......
paddle/fluid/framework/fleet/nccl_wrapper.h
浏览文件 @ a60d93fb
......@@ -25,9 +25,12 @@ limitations under the License. */
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/variable_helper.h"
#if defined(PADDLE_WITH_NCCL)
#ifdef PADDLE_WITH_NCCL
#include "paddle/fluid/platform/dynload/nccl.h"
#endif
#ifdef PADDLE_WITH_RCCL
#include "paddle/fluid/platform/dynload/rccl.h"
#endif
#include "paddle/fluid/platform/macros.h" // for DISABLE_COPY_AND_ASSIGN
namespace paddle {
......@@ -48,10 +51,10 @@ class NCCLInfo {
int local_rank_;
int global_ranks_;
int my_global_rank_;
#if defined(PADDLE_WITH_NCCL)
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
ncclUniqueId nccl_id_;
ncclComm_t comm_;
cudaStream_t stream_;
gpuStream_t stream_;
#endif
};
......
paddle/fluid/framework/fleet/ps_gpu_wrapper.cc
浏览文件 @ a60d93fb
......@@ -26,7 +26,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#if (defined PADDLE_WITH_NCCL) && (defined PADDLE_WITH_PSLIB)
#if (defined PADDLE_WITH_NCCL || defined PADDLE_WITH_RCCL) && \
(defined PADDLE_WITH_PSLIB)
#include <algorithm>
#include <deque>
......
paddle/fluid/framework/fleet/ps_gpu_wrapper.h
浏览文件 @ a60d93fb
......@@ -14,7 +14,8 @@ limitations under the License. */
#pragma once
#if (defined PADDLE_WITH_NCCL) && (defined PADDLE_WITH_PSLIB)
#if (defined PADDLE_WITH_NCCL || defined PADDLE_WITH_RCCL) && \
(defined PADDLE_WITH_PSLIB)
#include <atomic>
#include <ctime>
......
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