Add Event for TensorCopy (#15953)

Add Event for TensorCopy

paddle/fluid/framework/CMakeLists.txt

@@ -38,10 +38,10 @@ if(WITH_GPU)
     nv_library(tensor SRCS tensor.cc .tensor_util.cu DEPS place memory data_type device_context)
     add_dependencies(tensor tensor_util)
   else()
-    nv_library(tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type device_context )
+    nv_library(tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type device_context profiler)
   endif(WIN32)
 else()
-  cc_library(tensor SRCS tensor.cc tensor_util.cc DEPS place memory data_type device_context )
+  cc_library(tensor SRCS tensor.cc tensor_util.cc DEPS place memory data_type device_context profiler)
 endif()
 
 cc_test(tensor_test SRCS tensor_test.cc DEPS tensor)

paddle/fluid/framework/tensor_util.cc

@@ -14,8 +14,11 @@
 #include "paddle/fluid/framework/tensor_util.h"
 #include <algorithm>
 #include <limits>
+#include <memory>
+#include <utility>
 #include <vector>
 #include "paddle/fluid/framework/data_type.h"
+#include "paddle/fluid/platform/profiler.h"
 
 namespace paddle {
 namespace framework {
@@ -135,16 +138,19 @@ void TensorCopySync(const Tensor& src, const platform::Place& dst_place,
 #ifdef PADDLE_WITH_CUDA
   else if (platform::is_gpu_place(src_place) &&  // NOLINT
            platform::is_cpu_place(dst_place)) {
+    platform::RecordEvent record_event("TensorCopy:GPU->CPU");
     auto src_gpu_place = boost::get<platform::CUDAPlace>(src_place);
     auto dst_cpu_place = boost::get<platform::CPUPlace>(dst_place);
     memory::Copy(dst_cpu_place, dst_ptr, src_gpu_place, src_ptr, size, nullptr);
   } else if (platform::is_cpu_place(src_place) &&
              platform::is_gpu_place(dst_place)) {
+    platform::RecordEvent record_event("TensorCopy:CPU->GPU");
     auto src_cpu_place = boost::get<platform::CPUPlace>(src_place);
     auto dst_gpu_place = boost::get<platform::CUDAPlace>(dst_place);
     memory::Copy(dst_gpu_place, dst_ptr, src_cpu_place, src_ptr, size, nullptr);
   } else if (platform::is_gpu_place(src_place) &&
              platform::is_gpu_place(dst_place)) {
+    platform::RecordEvent record_event("TensorCopy:GPU->GPU");
     if (src_ptr == dst_ptr && platform::is_same_place(src_place, dst_place)) {
       VLOG(3) << "Skip copy the same data from " << src_place << " to "
               << dst_place;
@@ -155,6 +161,7 @@ void TensorCopySync(const Tensor& src, const platform::Place& dst_place,
     memory::Copy(dst_gpu_place, dst_ptr, src_gpu_place, src_ptr, size, nullptr);
   } else if (platform::is_cuda_pinned_place(src_place) &&
              platform::is_gpu_place(dst_place)) {
+    platform::RecordEvent record_event("TensorCopy:CUDAPinned->GPU");
     auto src_pinned_place = boost::get<platform::CUDAPinnedPlace>(src_place);
     auto dst_gpu_place = boost::get<platform::CUDAPlace>(dst_place);
     memory::Copy(dst_gpu_place, dst_ptr, src_pinned_place, src_ptr, size,

paddle/fluid/memory/CMakeLists.txt

@@ -1,6 +1,6 @@
 add_subdirectory(detail)
 add_subdirectory(allocation)
-cc_library(malloc SRCS malloc.cc DEPS place enforce allocator_facade)
+cc_library(malloc SRCS malloc.cc DEPS place enforce allocator_facade profiler)
 cc_library(memcpy SRCS memcpy.cc DEPS place)
 
 cc_library(memory

paddle/fluid/memory/memcpy.cc

@@ -15,6 +15,7 @@ limitations under the License. */
 #include "paddle/fluid/memory/memcpy.h"
 
 #include <cstring>  // for memcpy
+#include "paddle/fluid/platform/profiler.h"
 
 namespace paddle {
 namespace memory {
@@ -29,14 +30,23 @@ void Copy<platform::CPUPlace, platform::CPUPlace>(platform::CPUPlace, void* dst,
 #ifdef PADDLE_WITH_CUDA
 static constexpr size_t kMaxGpuAsyncCopyBytes = 64 * 1024;  // 64K
 
+// NOTE(zcd): Do not use GpuMemcpySync as much as possible.
+// because GpuMemcpySync issues the copying command to the default stream,
+// which will make two commands from different streams cannot run concurrently.
+// Reference:
+// https://devblogs.nvidia.com/gpu-pro-tip-cuda-7-streams-simplify-concurrency/
+
 template <>
 void Copy<platform::CPUPlace, platform::CUDAPlace>(
     platform::CPUPlace dst_place, void* dst, platform::CUDAPlace src_place,
     const void* src, size_t num, cudaStream_t stream) {
   platform::SetDeviceId(src_place.device);
+
   if (stream) {
+    platform::RecordEvent record_event("GpuMemcpyAsync:GPU->CPU");
     platform::GpuMemcpyAsync(dst, src, num, cudaMemcpyDeviceToHost, stream);
   } else {
+    platform::RecordEvent record_event("GpuMemcpySync:GPU->CPU");
     platform::GpuMemcpySync(dst, src, num, cudaMemcpyDeviceToHost);
     // FIXME(zjl): do we really need it?
     if (num <= kMaxGpuAsyncCopyBytes) {
@@ -51,8 +61,10 @@ void Copy<platform::CUDAPlace, platform::CPUPlace>(
     const void* src, size_t num, cudaStream_t stream) {
   platform::SetDeviceId(dst_place.device);
   if (stream) {
+    platform::RecordEvent record_event("GpuMemcpyAsync:CPU->GPU");
     platform::GpuMemcpyAsync(dst, src, num, cudaMemcpyHostToDevice, stream);
   } else {
+    platform::RecordEvent record_event("GpuMemcpySync:CPU->GPU");
     platform::GpuMemcpySync(dst, src, num, cudaMemcpyHostToDevice);
     // FIXME(zjl): do we really need it?
     if (num <= kMaxGpuAsyncCopyBytes) {
@@ -68,15 +80,19 @@ void Copy<platform::CUDAPlace, platform::CUDAPlace>(
   if (dst_place == src_place) {
     platform::SetDeviceId(src_place.device);
     if (stream) {
+      platform::RecordEvent record_event("GpuMemcpyAsync(same_gpu):GPU->GPU");
       platform::GpuMemcpyAsync(dst, src, num, cudaMemcpyDeviceToDevice, stream);
     } else {
+      platform::RecordEvent record_event("GpuMemcpySync(same_gpu):GPU->GPU");
       platform::GpuMemcpySync(dst, src, num, cudaMemcpyDeviceToDevice);
     }
   } else {
     if (stream) {
+      platform::RecordEvent record_event("GpuMemcpyPeerAsync:GPU->GPU");
       platform::GpuMemcpyPeerAsync(dst, dst_place.device, src, src_place.device,
                                    num, stream);
     } else {
+      platform::RecordEvent record_event("GpuMemcpyPeerSync:GPU->GPU");
       platform::GpuMemcpyPeerSync(dst, dst_place.device, src, src_place.device,
                                   num);
     }
@@ -111,8 +127,10 @@ void Copy<platform::CUDAPinnedPlace, platform::CUDAPlace>(
     cudaStream_t stream) {
   platform::SetDeviceId(src_place.device);
   if (stream) {
+    platform::RecordEvent record_event("GpuMemcpyAsync:GPU->CUDAPinned");
     platform::GpuMemcpyAsync(dst, src, num, cudaMemcpyDeviceToHost, stream);
   } else {
+    platform::RecordEvent record_event("GpuMemcpySync:GPU->CUDAPinned");
     platform::GpuMemcpySync(dst, src, num, cudaMemcpyDeviceToHost);
   }
 }
@@ -124,8 +142,10 @@ void Copy<platform::CUDAPlace, platform::CUDAPinnedPlace>(
     cudaStream_t stream) {
   platform::SetDeviceId(dst_place.device);
   if (stream) {
+    platform::RecordEvent record_event("GpuMemcpyAsync:CUDAPinned->GPU");
     platform::GpuMemcpyAsync(dst, src, num, cudaMemcpyHostToDevice, stream);
   } else {
+    platform::RecordEvent record_event("GpuMemcpySync:CUDAPinned->GPU");
     platform::GpuMemcpySync(dst, src, num, cudaMemcpyHostToDevice);
   }
 }

paddle/fluid/operators/reader/buffered_reader.cc

@@ -13,9 +13,11 @@
 // limitations under the License.
 
 #include "paddle/fluid/operators/reader/buffered_reader.h"
+#include <memory>
 #include <vector>
 #include "paddle/fluid/framework/data_type.h"
 
+#include "paddle/fluid/platform/profiler.h"
 namespace paddle {
 namespace operators {
 namespace reader {
@@ -49,9 +51,10 @@ BufferedReader::BufferedReader(
                                              .Get(place_)))
             ->stream();
     events.resize(buffer_size);
-    for (auto &event : events)
+    PADDLE_ENFORCE(cudaStreamCreate(&stream));
+    for (auto &event : events) {
       PADDLE_ENFORCE(cudaEventCreateWithFlags(&event, cudaEventDisableTiming));
-    PADDLE_ENFORCE(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
+    }
   }
 #endif
   cpu_buffer_.resize(buffer_size);
@@ -83,12 +86,15 @@ void BufferedReader::ReadAsync(size_t i) {
 
 #ifdef PADDLE_WITH_CUDA
     // NOTE(liangdun): using async copy instead of TensorCopySync
-    // TensorCopySync would block other stream
+    // TensorCopySync would block other stream, because TensorCopySync
+    // issues the copying command to the default stream, it will make two
+    // commands from different streams cannot run concurrently.
     if (platform::is_gpu_place(place_)) {
       platform::SetDeviceId(boost::get<platform::CUDAPlace>(place_).device);
       PADDLE_ENFORCE(cudaStreamWaitEvent(stream, events[i], 0));
       TensorVec &gpu = gpu_buffer_[i];
       gpu.resize(cpu.size());
+      platform::RecordEvent record_event("BufferedReader:MemoryCopy");
       for (size_t i = 0; i < cpu.size(); ++i) {
         gpu[i].Resize(cpu[i].dims());
         gpu[i].set_layout(cpu[i].layout());
@@ -97,20 +103,19 @@ void BufferedReader::ReadAsync(size_t i) {
         auto gpu_ptr = gpu[i].mutable_data(place_, cpu[i].type());
         auto size =
             cpu[i].numel() * paddle::framework::SizeOfType(cpu[i].type());
-        if (platform::is_cuda_pinned_place(cpu_place))
+        if (platform::is_cuda_pinned_place(cpu_place)) {
           memory::Copy(boost::get<platform::CUDAPlace>(place_), gpu_ptr,
                        boost::get<platform::CUDAPinnedPlace>(cpu_place),
                        cpu_ptr, size, stream);
-        else if ((platform::is_gpu_place(cpu_place)))
+        } else if ((platform::is_gpu_place(cpu_place))) {
           memory::Copy(boost::get<platform::CUDAPlace>(place_), gpu_ptr,
                        boost::get<platform::CUDAPlace>(cpu_place), cpu_ptr,
                        size, stream);
-        else
-          // if cpu place is not pinned, async copy is slower than sync copy,
-          // so we use sync copy instead.
+        } else {
           memory::Copy(boost::get<platform::CUDAPlace>(place_), gpu_ptr,
                        boost::get<platform::CPUPlace>(cpu_place), cpu_ptr, size,
-                       0);
+                       stream);
+        }
         gpu[i].set_lod(cpu[i].lod());
       }
       PADDLE_ENFORCE(cudaStreamSynchronize(stream));

paddle/fluid/platform/device_tracer.cc

@@ -30,7 +30,6 @@ limitations under the License. */
 #include "glog/logging.h"
 #include "google/protobuf/text_format.h"
 #include "paddle/fluid/framework/block_desc.h"
-#include "paddle/fluid/platform/profiler.h"
 #include "paddle/fluid/string/printf.h"
 
 namespace paddle {
@@ -222,19 +221,24 @@ void CUPTIAPI bufferCompleted(CUcontext ctx, uint32_t streamId, uint8_t *buffer,
           }
           case CUPTI_ACTIVITY_KIND_DRIVER: {
             auto *api = reinterpret_cast<const CUpti_ActivityAPI *>(record);
-            if (api->start != 0 && api->end != 0)
-              // -1 device id represents CUDA api call
-              tracer->AddCPURecords(
+            if (api->start != 0 && api->end != 0) {
+              // -1 device id represents ActiveKind api call
+              tracer->AddActiveKindRecords(
                   DriverKind(api->cbid), api->start, api->end, -1,
-                  GetThreadIdFromSystemThreadId(api->threadId));
+                  GetThreadIdFromSystemThreadId(api->threadId),
+                  api->correlationId);
+            }
             break;
           }
           case CUPTI_ACTIVITY_KIND_RUNTIME: {
             auto *api = reinterpret_cast<const CUpti_ActivityAPI *>(record);
-            if (api->start != 0 && api->end != 0)
-              tracer->AddCPURecords(
+            if (api->start != 0 && api->end != 0) {
+              // -1 device id represents ActiveKind api call
+              tracer->AddActiveKindRecords(
                   RuntimeKind(api->cbid), api->start, api->end, -1,
-                  GetThreadIdFromSystemThreadId(api->threadId));
+                  GetThreadIdFromSystemThreadId(api->threadId),
+                  api->correlationId);
+            }
             break;
           }
           default: { break; }
@@ -313,6 +317,25 @@ class DeviceTracerImpl : public DeviceTracer {
                                       stream_id, correlation_id, bytes});
   }
 
+  void AddActiveKindRecords(const std::string &anno, uint64_t start_ns,
+                            uint64_t end_ns, int64_t device_id,
+                            int64_t thread_id, uint32_t correlation_id) {
+    if (anno.empty()) {
+      VLOG(1) << "Empty timeline annotation.";
+      return;
+    }
+    thread_local std::forward_list<ActiveKindRecord>
+        *local_active_kind_records = nullptr;
+    if (local_active_kind_records == nullptr) {
+      std::lock_guard<std::mutex> l(trace_mu_);
+      active_kind_records_.emplace_front();
+      local_active_kind_records = &active_kind_records_.front();
+    }
+    //  lock is not needed, only one thread call this function.
+    local_active_kind_records->push_front(ActiveKindRecord{
+        anno, start_ns, end_ns, device_id, thread_id, correlation_id});
+  }
+
   void AddKernelRecords(std::string name, uint64_t start, uint64_t end,
                         int64_t device_id, int64_t stream_id,
                         uint32_t correlation_id) {
@@ -355,6 +378,7 @@ class DeviceTracerImpl : public DeviceTracer {
     }
     const std::vector<int> cbids {
       CUPTI_RUNTIME_TRACE_CBID_cudaMemcpy_v3020,
+          CUPTI_RUNTIME_TRACE_CBID_cudaSetupArgument_v3020,
           CUPTI_RUNTIME_TRACE_CBID_cudaMemcpyAsync_v3020,
           CUPTI_RUNTIME_TRACE_CBID_cudaMemset_v3020,
           CUPTI_RUNTIME_TRACE_CBID_cudaMemsetAsync_v3020,
@@ -385,6 +409,7 @@ class DeviceTracerImpl : public DeviceTracer {
     correlations_.clear();
     for (auto &tmp : correlations_pairs) tmp.clear();
     for (auto &tmp : cpu_records_) tmp.clear();
+    for (auto &tmp : active_kind_records_) tmp.clear();
   }
 
   void GenEventKernelCudaElapsedTime() {
@@ -437,7 +462,7 @@ class DeviceTracerImpl : public DeviceTracer {
       event->set_device_id(r.device_id);
     }
     VLOG(1) << "KernelRecord event miss: " << miss << " find: " << find;
-    for (auto &tmp : cpu_records_)
+    for (auto &tmp : cpu_records_) {
       for (const CPURecord &r : tmp) {
         auto *event = profile_pb.add_events();
         event->set_type(proto::Event::CPU);
@@ -447,6 +472,24 @@ class DeviceTracerImpl : public DeviceTracer {
         event->set_sub_device_id(r.thread_id);
         event->set_device_id(r.device_id);
       }
+    }
+    for (auto &tmp : active_kind_records_) {
+      for (const ActiveKindRecord &r : tmp) {
+        auto *event = profile_pb.add_events();
+        event->set_type(proto::Event::CPU);
+        auto c = correlations_.find(r.correlation_id);
+        if (c != correlations_.end() && c->second != nullptr) {
+          event->set_name(c->second->name());
+          event->set_detail_info(r.name);
+        } else {
+          event->set_name(r.name);
+        }
+        event->set_start_ns(r.start_ns);
+        event->set_end_ns(r.end_ns);
+        event->set_sub_device_id(r.thread_id);
+        event->set_device_id(r.device_id);
+      }
+    }
     miss = find = 0;
     for (const MemRecord &r : mem_records_) {
       auto *event = profile_pb.add_events();
@@ -510,6 +553,7 @@ class DeviceTracerImpl : public DeviceTracer {
   std::forward_list<KernelRecord> kernel_records_;
   std::forward_list<MemRecord> mem_records_;
   std::forward_list<std::forward_list<CPURecord>> cpu_records_;
+  std::forward_list<std::forward_list<ActiveKindRecord>> active_kind_records_;
   std::forward_list<std::forward_list<std::pair<uint32_t, Event *>>>
       correlations_pairs;
   std::unordered_map<uint32_t, Event *> correlations_;
@@ -613,6 +657,7 @@ void initCuptiCbidStr() {
   REGISTER_RUNTIME_CBID_STR(cudaUnbindTexture_v3020);
   REGISTER_RUNTIME_CBID_STR(cudaSetupArgument_v3020);
   REGISTER_RUNTIME_CBID_STR(cudaLaunch_v3020);
+  REGISTER_RUNTIME_CBID_STR(cudaDeviceGetPCIBusId_v4010);
 #if CUDA_VERSION >= 9000
   REGISTER_RUNTIME_CBID_STR(cudaLaunchCooperativeKernel_v9000);
   REGISTER_RUNTIME_CBID_STR(cudaLaunchCooperativeKernelMultiDevice_v9000);

paddle/fluid/platform/device_tracer.h

@@ -63,7 +63,14 @@ class DeviceTracer {
     uint32_t correlation_id;
     uint64_t bytes;
   };
-
+  struct ActiveKindRecord {
+    std::string name;
+    uint64_t start_ns;
+    uint64_t end_ns;
+    int64_t device_id;
+    int64_t thread_id;
+    uint32_t correlation_id;
+  };
   virtual ~DeviceTracer() {}
   // Needs to be called once before use.
   virtual void Enable() = 0;
@@ -85,6 +92,10 @@ class DeviceTracer {
   virtual void AddCPURecords(const std::string& anno, uint64_t start_ns,
                              uint64_t end_ns, int64_t device_id,
                              int64_t thread_id) = 0;
+  virtual void AddActiveKindRecords(const std::string& anno, uint64_t start_ns,
+                                    uint64_t end_ns, int64_t device_id,
+                                    int64_t thread_id,
+                                    uint32_t correlation_id) = 0;
 
   // Add a cuda kernel stats. `correlation_id` will be mapped to annotation
   // added before for human readability.

tools/timeline.py

@@ -131,7 +131,7 @@ class Timeline(object):
                     if (k, event.device_id, "CPU") not in self._devices:
                         pid = self._allocate_pid()
                         self._devices[(k, event.device_id, "CPU")] = pid
-                        # -1 device id represents CUDA api call
+                        # -1 device id represents CUDA API(RunTime) call.(e.g. cudaLaunch, cudaMemcpy)
                         if event.device_id == -1:
                             self._chrome_trace.emit_pid("%s:cuda_api" % k, pid)
                         else: