!274 GPU multiple stream feature

Merge pull request !274 from ZPaC/gpu-backend-supports-multiple-streams

mindspore/ccsrc/device/gpu/gpu_device_manager.cc

@@ -25,7 +25,7 @@ namespace device {
 namespace gpu {
 void GPUDeviceManager::InitDevice() {
   CHECK_OP_RET_WITH_EXCEPT(CudaDriver::set_current_device(SizeToInt(cur_dev_id_)), "Failed to set current device id");
-  CHECK_OP_RET_WITH_EXCEPT(CudaDriver::CreateStream(&stream_), "Failed to create CUDA stream.");
+  CHECK_OP_RET_WITH_EXCEPT(CreateStream(&default_stream_), "Failed to create CUDA stream.");
   CHECK_CUDNN_RET_WITH_EXCEPT(cudnnCreate(&cudnn_handle_), "Failed to create cuDNN handle");
   CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetStream(cudnn_handle_, reinterpret_cast<cudaStream_t>(default_stream())),
                               "Failed to set stream for cuDNN handle.");
@@ -36,19 +36,27 @@ void GPUDeviceManager::InitDevice() {
 }
 
 void GPUDeviceManager::ReleaseDevice() {
-  if (stream_ != nullptr) {
-    CHECK_OP_RET_WITH_ERROR(CudaDriver::DestroyStream(stream_), "Failed to destroy cuda stream.");
+  for (DeviceStream stream : gpu_streams_) {
+    if (stream != nullptr) {
+      CHECK_OP_RET_WITH_ERROR(CudaDriver::DestroyStream(stream), "Failed to destroy CUDA stream.");
+    }
   }
   if (cudnn_handle_ != nullptr) {
-    CHECK_CUDNN_RET_WITH_ERROR(cudnnDestroy(cudnn_handle_), "Failed to destroy cudnn handle");
+    CHECK_CUDNN_RET_WITH_ERROR(cudnnDestroy(cudnn_handle_), "Failed to destroy cuDNN handle");
   }
   if (cublas_handle_ != nullptr) {
-    CHECK_CUBLAS_RET_WITH_ERROR(cublasDestroy(cublas_handle_), "Failed to destroy cublas handle.");
+    CHECK_CUBLAS_RET_WITH_ERROR(cublasDestroy(cublas_handle_), "Failed to destroy cuBLAS handle.");
   }
   CHECK_OP_RET_WITH_ERROR(GPUMemoryAllocator::GetInstance().Finalize(), "Failed to destroy gpu memory allocator");
 }
 
-const DeviceStream& GPUDeviceManager::default_stream() const { return stream_; }
+bool GPUDeviceManager::CreateStream(DeviceStream* stream) {
+  CHECK_OP_RET_WITH_EXCEPT(CudaDriver::CreateStream(stream), "Failed to create CUDA stream");
+  gpu_streams_.emplace_back(*stream);
+  return true;
+}
+
+const DeviceStream& GPUDeviceManager::default_stream() const { return default_stream_; }
 
 int GPUDeviceManager::device_count() const { return CudaDriver::device_count(); }
 

mindspore/ccsrc/device/gpu/gpu_device_manager.h

@@ -19,6 +19,7 @@
 
 #include <cudnn.h>
 #include <cublas_v2.h>
+#include <vector>
 #include <memory>
 #include "device/gpu/cuda_driver.h"
 #include "device/gpu/gpu_memory_allocator.h"
@@ -36,13 +37,15 @@ class GPUDeviceManager {
   uint32_t cur_device_id() const;
   bool is_device_id_init() const;
 
+  bool CreateStream(DeviceStream* stream);
+  bool SyncStream(const DeviceStream& stream) const;
   const DeviceStream& default_stream() const;
+
   const cudnnHandle_t& GetCudnnHandle() const;
   const cublasHandle_t& GetCublasHandle() const;
 
   bool CopyDeviceMemToHost(const HostMemPtr& dst, const DeviceMemPtr& src, size_t size) const;
   bool CopyHostMemToDevice(const DeviceMemPtr& dst, const void* src, size_t size) const;
-  bool SyncStream(const DeviceStream& stream) const;
 
   static GPUDeviceManager& GetInstance() {
     static GPUDeviceManager instance;
@@ -55,13 +58,16 @@ class GPUDeviceManager {
   GPUDeviceManager(const GPUDeviceManager&) = delete;
   GPUDeviceManager& operator=(const GPUDeviceManager&) = delete;
 
-  // default cuda stream used for all the kernels.
-  DeviceStream stream_{nullptr};
+  // default CUDA stream used for all the kernels.
+  DeviceStream default_stream_{nullptr};
 
-  // handle used for cudnn kernels.
+  // all gpu CUDA streams including default_stream_.
+  std::vector<DeviceStream> gpu_streams_;
+
+  // handle used for cuDNN kernels.
   cudnnHandle_t cudnn_handle_{nullptr};
 
-  // handle used for cublas kernels.
+  // handle used for cuBLAS kernels.
   cublasHandle_t cublas_handle_{nullptr};
 
   bool dev_id_init_;

mindspore/ccsrc/device/gpu/gpu_stream_assign.cc

@@ -0,0 +1,181 @@
+/**
+ * Copyright 2019 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <set>
+#include <string>
+#include <memory>
+#include <algorithm>
+#include "device/gpu/gpu_common.h"
+#include "device/gpu/kernel_info_setter.h"
+#include "device/gpu/gpu_device_manager.h"
+#include "device/gpu/gpu_stream_assign.h"
+
+namespace mindspore {
+namespace device {
+namespace gpu {
+void AssignGpuStream(const std::shared_ptr<session::KernelGraph> &kernel_graph) {
+  MS_EXCEPTION_IF_NULL(kernel_graph);
+  std::vector<CNodePtr> allreduce_cnodes;
+  auto execution_kernels = kernel_graph->execution_order();
+  for (auto kernel : execution_kernels) {
+    std::string kernel_name = AnfAlgo::GetCNodeName(kernel);
+    if (kernel_name == kAllReduceOpName) {
+      allreduce_cnodes.emplace_back(kernel);
+    }
+  }
+  if (allreduce_cnodes.size() > 1) {
+    DeviceStream comm_stream = nullptr;
+    GPUDeviceManager::GetInstance().CreateStream(&comm_stream);
+    std::transform(allreduce_cnodes.begin(), allreduce_cnodes.end(), allreduce_cnodes.begin(), [&](CNodePtr node) {
+      AnfAlgo::SetNodeAttr("stream_id", MakeValue(reinterpret_cast<uintptr_t>(comm_stream)), node);
+      return node;
+    });
+
+    std::vector<SendRecvPair> send_recv_pairs;
+    FindAllReduceStreamSwitchPos(kernel_graph, &send_recv_pairs);
+    InsertStreamSwitchNode(kernel_graph, send_recv_pairs);
+  }
+}
+
+void FindAllReduceStreamSwitchPos(const std::shared_ptr<session::KernelGraph> &kernel_graph,
+                                  std::vector<SendRecvPair> *send_recv_pairs) {
+  auto execution_kernels = kernel_graph->execution_order();
+  std::vector<CNodePtr>::iterator iter, iter_begin;
+  iter = iter_begin = execution_kernels.begin();
+  std::vector<CNodePtr>::iterator iter_end = execution_kernels.end();
+  for (; iter != execution_kernels.end(); ++iter) {
+    std::string kernel_name = AnfAlgo::GetCNodeName(*iter);
+    if (kernel_name == kAllReduceOpName) {
+      // Find AllReduce node's last input node.
+      std::vector<CNodePtr>::iterator mock_send_node_iter =
+        FindSendNodePos(iter_begin, iter + 1, *iter, kAllReduceStreamSwitch);
+      if (mock_send_node_iter == iter + 1) {
+        MS_LOG(WARNING) << "Can't find send node place before AllReduce node.";
+        continue;
+      }
+      SendRecvPair pair1 = {kAllReduceStreamSwitch, *mock_send_node_iter, *iter,
+                            IntToSize(mock_send_node_iter - iter_begin + 1), IntToSize(iter - iter_begin)};
+      send_recv_pairs->push_back(pair1);
+      // Find node which uses AllReduce as input[0].
+      std::vector<CNodePtr>::iterator mock_recv_node_iter =
+        FindRecvNodePos(iter, iter_end, *iter, kAllReduceStreamSwitch);
+      if (mock_recv_node_iter == iter_end) {
+        MS_LOG(WARNING) << "Can't find send node place before AllReduce node.";
+        continue;
+      }
+      SendRecvPair pair2 = {kAllReduceStreamSwitch, *iter, *mock_recv_node_iter, IntToSize(iter - iter_begin + 1),
+                            IntToSize(mock_recv_node_iter - iter_begin)};
+      send_recv_pairs->push_back(pair2);
+    }
+  }
+}
+
+std::vector<CNodePtr>::iterator FindSendNodePos(std::vector<CNodePtr>::iterator begin,
+                                                std::vector<CNodePtr>::iterator end, const CNodePtr mock_recv_node,
+                                                StreamSwitchType stream_switch_type) {
+  MS_EXCEPTION_IF_NULL(mock_recv_node);
+  if (stream_switch_type == kAllReduceStreamSwitch) {
+    for (auto iter = begin; iter != end; iter++) {
+      if (*(iter + 1) == mock_recv_node) {
+        return iter;
+      }
+    }
+  }
+  return end;
+}
+
+std::vector<CNodePtr>::iterator FindRecvNodePos(std::vector<CNodePtr>::iterator begin,
+                                                std::vector<CNodePtr>::iterator end, const CNodePtr mock_send_node,
+                                                StreamSwitchType stream_switch_type) {
+  MS_EXCEPTION_IF_NULL(mock_send_node);
+  for (auto iter = begin; iter != end; iter++) {
+    auto node = *iter;
+    if (stream_switch_type == kAllReduceStreamSwitch) {
+      for (auto input : node->inputs()) {
+        if (mock_send_node == AnfAlgo::VisitKernel(input, 0).first) {
+          return iter;
+        }
+      }
+    }
+  }
+  return end;
+}
+
+void InsertStreamSwitchNode(const std::shared_ptr<session::KernelGraph> &kernel_graph,
+                            const std::vector<SendRecvPair> &send_recv_pairs) {
+  std::set<StreamSwitchNode> ordered_stream_switch_nodes;
+  for (SendRecvPair pair : send_recv_pairs) {
+    StreamSwitchType stream_switch_type = pair.stream_switch_type;
+    CNodePtr mock_send_node = pair.mock_send_node;
+    CNodePtr mock_recv_node = pair.mock_recv_node;
+    size_t send_node_offset = pair.send_node_offset;
+    size_t recv_node_offset = pair.recv_node_offset;
+    CNodePtr send_node = nullptr;
+    CNodePtr recv_node = nullptr;
+    // Step 1: generate Send and Recv CNodes.
+    if (stream_switch_type == kAllReduceStreamSwitch) {
+      if (!GenSendRecvCNodesForAllReduce(kernel_graph, mock_send_node, mock_recv_node, &send_node, &recv_node)) {
+        MS_LOG(EXCEPTION) << "Generating CNodes for send and recv failed. Stream switch type: kAllReduceStreamSwitch";
+      }
+    }
+    // Step 2: sort send and recv CNodes by offset.
+    ordered_stream_switch_nodes.insert({send_node_offset, send_node});
+    ordered_stream_switch_nodes.insert({recv_node_offset, recv_node});
+  }
+  // Step 3: insert stream switch CNodes into execution kernel list.
+  auto execution_kernels = kernel_graph->execution_order();
+  for (auto node = ordered_stream_switch_nodes.begin(); node != ordered_stream_switch_nodes.end(); node++) {
+    execution_kernels.insert(execution_kernels.begin() + node->offset, node->cnode);
+  }
+  kernel_graph->set_execution_order(execution_kernels);
+}
+
+bool GenSendRecvCNodesForAllReduce(const std::shared_ptr<session::KernelGraph> &kernel_graph,
+                                   const CNodePtr &mock_send_node, const CNodePtr &mock_recv_node, CNodePtr *send_node,
+                                   CNodePtr *recv_node) {
+  *send_node = CreateStreamSwitchNode(kernel_graph, kSendOpName);
+  MS_EXCEPTION_IF_NULL(*send_node);
+  *recv_node = CreateStreamSwitchNode(kernel_graph, kRecvOpName);
+  MS_EXCEPTION_IF_NULL(*recv_node);
+
+  cudaEvent_t event = nullptr;
+  CHECK_CUDA_RET_WITH_EXCEPT(cudaEventCreate(&event, cudaEventDisableTiming), "Creating cuda event failed.");
+  AnfAlgo::SetNodeAttr("record_event", MakeValue(reinterpret_cast<uintptr_t>(event)), *send_node);
+  AnfAlgo::SetNodeAttr("wait_event", MakeValue(reinterpret_cast<uintptr_t>(event)), *recv_node);
+
+  uintptr_t send_stream = AnfAlgo::GetNodeAttr<uintptr_t>(mock_send_node, "stream_id");
+  AnfAlgo::SetNodeAttr("record_event_stream", MakeValue(send_stream), *send_node);
+  uintptr_t recv_stream = AnfAlgo::GetNodeAttr<uintptr_t>(mock_recv_node, "stream_id");
+  AnfAlgo::SetNodeAttr("wait_event_stream", MakeValue(recv_stream), *recv_node);
+  return true;
+}
+
+CNodePtr CreateStreamSwitchNode(const std::shared_ptr<session::KernelGraph> &kernel_graph, const std::string &name) {
+  auto op = std::make_shared<Primitive>(name);
+  auto apply = std::make_shared<ValueNode>(op);
+  std::vector<AnfNodePtr> input_list = {apply};
+  CNodePtr node = kernel_graph->NewCNode(input_list);
+  MS_EXCEPTION_IF_NULL(node);
+  kernel::KernelBuildInfo::KernelBuildInfoBuilder selected_kernel_builder;
+  AnfAlgo::SetSelectKernelBuildInfo(selected_kernel_builder.Build(), node.get());
+  auto abstract_none = std::make_shared<abstract::AbstractNone>();
+  node->set_abstract(abstract_none);
+  SetKernelInfo(node);
+  return node;
+}
+}  // namespace gpu
+}  // namespace device
+}  // namespace mindspore

mindspore/ccsrc/device/gpu/gpu_stream_assign.h

@@ -0,0 +1,73 @@
+/**
+ * Copyright 2019 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MINDSPORE_CCSRC_DEVICE_GPU_GPU_STREAM_ASSIGN_H_
+#define MINDSPORE_CCSRC_DEVICE_GPU_GPU_STREAM_ASSIGN_H_
+
+#include <vector>
+#include <string>
+#include <memory>
+#include "session/kernel_graph.h"
+#include "session/anf_runtime_algorithm.h"
+
+namespace mindspore {
+namespace device {
+namespace gpu {
+enum StreamSwitchType { kAllReduceStreamSwitch, kStreamSwitchInvalidType = 255 };
+struct SendRecvPair {
+  StreamSwitchType stream_switch_type;
+  CNodePtr mock_send_node;
+  CNodePtr mock_recv_node;
+  size_t send_node_offset;
+  size_t recv_node_offset;
+};
+struct StreamSwitchNode {
+  size_t offset;
+  CNodePtr cnode;
+  bool operator<(const StreamSwitchNode &n) const {
+    if (offset < n.offset) {
+      return true;
+    } else if (offset == n.offset) {
+      return AnfAlgo::GetCNodeName(cnode) == kSendOpName ? true : false;
+    } else {
+      return false;
+    }
+  }
+};
+void AssignGpuStream(const std::shared_ptr<session::KernelGraph> &kernel_graph);
+void FindAllReduceStreamSwitchPos(const std::shared_ptr<session::KernelGraph> &kernel_graph,
+                                  std::vector<SendRecvPair> *send_recv_pairs);
+// Find Send node position according to "mock" recv node.
+// "mock" recv node is a gpu kernel node after a real Recv node, e.g. AllReduce node.
+std::vector<CNodePtr>::iterator FindSendNodePos(std::vector<CNodePtr>::iterator begin,
+                                                std::vector<CNodePtr>::iterator end, const CNodePtr mock_recv_node,
+                                                StreamSwitchType stream_switch_type);
+// Find Recv node position according to "mock" send node.
+// "mock" send node is a gpu kernel node before a real send node, e.g. AllReduce node.
+std::vector<CNodePtr>::iterator FindRecvNodePos(std::vector<CNodePtr>::iterator begin,
+                                                std::vector<CNodePtr>::iterator end, const CNodePtr mock_send_node,
+                                                StreamSwitchType stream_switch_type);
+void InsertStreamSwitchNode(const std::shared_ptr<session::KernelGraph> &kernel_graph,
+                            const std::vector<SendRecvPair> &send_recv_pairs);
+bool GenSendRecvCNodesForAllReduce(const std::shared_ptr<session::KernelGraph> &kernel_graph,
+                                   const CNodePtr &mock_send_node, const CNodePtr &mock_recv_node, CNodePtr *send_node,
+                                   CNodePtr *recv_node);
+CNodePtr CreateStreamSwitchNode(const std::shared_ptr<session::KernelGraph> &kernel_graph, const std::string &name);
+}  // namespace gpu
+}  // namespace device
+}  // namespace mindspore
+
+#endif

mindspore/ccsrc/kernel/gpu/nccl/nccl_gpu_kernel.h

@@ -52,7 +52,8 @@ class NcclGpuKernel : public GpuKernel {
         nccl_reduce_type_(ncclSum),
         input_size_(0),
         output_size_(0),
-        collective_handle_(nullptr) {}
+        collective_handle_(nullptr),
+        comm_stream_(nullptr) {}
   ~NcclGpuKernel() override = default;
 
   const std::vector<size_t> &GetInputSizeList() const override { return input_size_list_; }
@@ -63,34 +64,33 @@ class NcclGpuKernel : public GpuKernel {
     T *input_addr = GetDeviceAddress<T>(inputs, 0);
     T *output_addr = GetDeviceAddress<T>(outputs, 0);
 
+    cudaStream_t stream = comm_stream_ ? comm_stream_ : reinterpret_cast<cudaStream_t>(stream_ptr);
     switch (nccl_kernel_type_) {
       case NCCL_ALL_REDUCE: {
         auto all_reduce_funcptr =
           reinterpret_cast<AllReduce>(dlsym(const_cast<void *>(collective_handle_), "AllReduce"));
         MS_EXCEPTION_IF_NULL(all_reduce_funcptr);
-        CHECK_NCCL_RET_WITH_EXCEPT(
-          (*all_reduce_funcptr)(input_addr, output_addr, output_size_ / sizeof(T), nccl_data_type_, nccl_reduce_type_,
-                                reinterpret_cast<cudaStream_t>(stream_ptr)),
-          "ncclAllReduce failed");
+        CHECK_NCCL_RET_WITH_EXCEPT((*all_reduce_funcptr)(input_addr, output_addr, output_size_ / sizeof(T),
+                                                         nccl_data_type_, nccl_reduce_type_, stream),
+                                   "ncclAllReduce failed");
         break;
       }
       case NCCL_ALL_GATHER: {
         auto all_gather_funcptr =
           reinterpret_cast<AllGather>(dlsym(const_cast<void *>(collective_handle_), "AllGather"));
         MS_EXCEPTION_IF_NULL(all_gather_funcptr);
-        CHECK_NCCL_RET_WITH_EXCEPT((*all_gather_funcptr)(input_addr, output_addr, input_size_ / sizeof(T),
-                                                         nccl_data_type_, reinterpret_cast<cudaStream_t>(stream_ptr)),
-                                   "ncclAllGather failed");
+        CHECK_NCCL_RET_WITH_EXCEPT(
+          (*all_gather_funcptr)(input_addr, output_addr, input_size_ / sizeof(T), nccl_data_type_, stream),
+          "ncclAllGather failed");
         break;
       }
       case NCCL_REDUCE_SCATTER: {
         auto reduce_scatter_funcptr =
           reinterpret_cast<ReduceScatter>(dlsym(const_cast<void *>(collective_handle_), "ReduceScatter"));
         MS_EXCEPTION_IF_NULL(reduce_scatter_funcptr);
-        CHECK_NCCL_RET_WITH_EXCEPT(
-          (*reduce_scatter_funcptr)(input_addr, output_addr, output_size_ / sizeof(T), nccl_data_type_,
-                                    nccl_reduce_type_, reinterpret_cast<cudaStream_t>(stream_ptr)),
-          "ncclReduceScatter failed");
+        CHECK_NCCL_RET_WITH_EXCEPT((*reduce_scatter_funcptr)(input_addr, output_addr, output_size_ / sizeof(T),
+                                                             nccl_data_type_, nccl_reduce_type_, stream),
+                                   "ncclReduceScatter failed");
         break;
       }
       default: {
@@ -167,6 +167,7 @@ class NcclGpuKernel : public GpuKernel {
   std::vector<size_t> output_size_list_;
   std::vector<size_t> workspace_size_list_;
   const void *collective_handle_;
+  cudaStream_t comm_stream_;
 };
 }  // namespace kernel
 }  // namespace mindspore

mindspore/ccsrc/session/gpu_session.cc

@@ -17,6 +17,7 @@
 #include "device/gpu/kernel_info_setter.h"
 #include "device/gpu/gpu_kernel_build.h"
 #include "device/gpu/gpu_kernel_runtime.h"
+#include "device/gpu/gpu_stream_assign.h"
 #include "pre_activate/common/optimizer.h"
 #include "pre_activate/common/pass_manager.h"
 #include "pre_activate/common/ir_fusion/allreduce_fusion.h"
@@ -55,6 +56,11 @@ void GPUSession::Optimize(const std::shared_ptr<KernelGraph> &kernel_graph) {
   kernel_graph->SetExecOrderByDefault();
 }
 
+void GPUSession::AssignStream(const std::shared_ptr<KernelGraph> &kernel_graph) {
+  MS_EXCEPTION_IF_NULL(kernel_graph);
+  device::gpu::AssignGpuStream(kernel_graph);
+}
+
 void GPUSession::BuildKernel(const std::shared_ptr<KernelGraph> &kernel_graph) const {
   device::gpu::GpuBuild(kernel_graph);
 }
@@ -94,6 +100,8 @@ GraphId GPUSession::CompileGraph(const AnfNodePtrList &lst, const AnfNodePtrList
   StartKernelRT();
   // AllReduce Optimize
   Optimize(graph);
+  // Assign CUDA streams
+  AssignStream(graph);
   // Build kernel if node is cnode
   BuildKernel(graph);
   // Set graph execution order before memory alloc, ensure that memory alloc is according to the reorder graph

mindspore/ccsrc/session/gpu_session.h

@@ -49,6 +49,8 @@ class GPUSession : public SessionBasic {
 
   void Optimize(const std::shared_ptr<KernelGraph> &kernel_graph);
 
+  void AssignStream(const std::shared_ptr<KernelGraph> &kernel_graph);
+
   void BuildKernel(const std::shared_ptr<KernelGraph> &kernel_graph) const;
 
   void AllocateMemory(KernelGraph *kernel_graph) const;

mindspore/ccsrc/utils/utils.h

@@ -113,6 +113,8 @@ constexpr auto kFusedMulAddNOpName = "FusedMulAddN";
 constexpr auto kFusedMulApplyMomentumOpName = "FusedMulApplyMomentum";
 constexpr auto kBiasAddOpName = "BiasAdd";
 constexpr auto kConfusionMulGradOpName = "ConfusionMulGrad";
+constexpr auto kSendOpName = "Send";
+constexpr auto kRecvOpName = "Recv";
 
 // attr key name
 constexpr auto kAttrInputNames = "input_names";