paddlepaddle--paddle/paddle/phi/backends/gpu/rocm/hip_graph.cc

// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// 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 "paddle/phi/backends/gpu/rocm/hip_graph.h"
#include "glog/logging.h"
#include "paddle/common/flags.h"

COMMON_DECLARE_bool(use_cuda_malloc_async_allocator);
COMMON_DECLARE_bool(auto_free_cudagraph_allocations_on_launch);

#ifdef PADDLE_WITH_HIP

namespace phi {
namespace backends {
namespace gpu {

std::unique_ptr<CUDAGraph> CUDAGraph::capturing_graph_{nullptr};
paddle::optional<std::thread::id> CUDAGraph::capturing_thread_id_{paddle::none};

static std::vector<hipGraphNode_t> ToposortCUDAGraph(hipGraph_t graph) {
  size_t num_nodes;
  PADDLE_ENFORCE_GPU_SUCCESS(hipGraphGetNodes(graph, nullptr, &num_nodes));
  std::vector<hipGraphNode_t> nodes(num_nodes);
  PADDLE_ENFORCE_GPU_SUCCESS(hipGraphGetNodes(graph, nodes.data(), &num_nodes));

  size_t num_edges;
  PADDLE_ENFORCE_GPU_SUCCESS(
      hipGraphGetEdges(graph, nullptr, nullptr, &num_edges));
  std::vector<hipGraphNode_t> from(num_edges), to(num_edges);
  PADDLE_ENFORCE_GPU_SUCCESS(
      hipGraphGetEdges(graph, from.data(), to.data(), &num_edges));

  std::unordered_map<hipGraphNode_t, std::unordered_set<hipGraphNode_t>>
      in_edges, out_edges;
  for (auto node : nodes) {
    in_edges[node];
    out_edges[node];
  }

  for (size_t i = 0; i < num_edges; ++i) {
    in_edges[to[i]].insert(from[i]);
    out_edges[from[i]].insert(to[i]);
  }

  std::queue<hipGraphNode_t> q;
  for (const auto &pair : in_edges) {
    if (pair.second.empty()) {
      q.push(pair.first);
    }
  }

  nodes.clear();
  while (!q.empty()) {
    auto cur = q.front();
    q.pop();
    nodes.push_back(cur);

    for (auto out_node : out_edges.at(cur)) {
      auto &in_nodes = in_edges.at(out_node);
      in_nodes.erase(cur);
      if (in_nodes.empty()) {
        q.push(out_node);
      }
    }
  }
  PADDLE_ENFORCE_EQ(
      nodes.size(),
      num_nodes,
      common::errors::InvalidArgument("Toposort error, this may be a bug."));
  return nodes;
}

CUDAGraphID CUDAGraph::UniqueID() {
  static std::atomic<CUDAGraphID> id;
  return id.fetch_add(1);
}

int64_t CUDAGraph::UniqueMemoryPoolID() {
  static std::atomic<int64_t> id(CUDAGraph::kDefaultPoolID + 1);
  return id.fetch_add(1);
}

void CUDAGraph::Reset() {
  if (is_reset_) return;
  for (auto graph : graphs_) {
    PADDLE_ENFORCE_GPU_SUCCESS(hipGraphDestroy(graph));
  }
  graphs_.clear();
  for (auto exec_graph : exec_graphs_) {
    PADDLE_ENFORCE_GPU_SUCCESS(hipGraphExecDestroy(exec_graph));
  }
  exec_graphs_.clear();
  // callback should be called in reverse order because the latter added
  // callback may rely on the former added callback.
  for (auto iter = cudagraph_post_reset_callbacks_.rbegin();
       iter != cudagraph_post_reset_callbacks_.rend();
       ++iter) {
    (*iter)(*this);
  }
  cudagraph_post_reset_callbacks_.clear();
  is_reset_ = true;
}

void CUDAGraph::Replay() {
  PADDLE_ENFORCE_EQ(is_reset_,
                    false,
                    common::errors::PermissionDenied(
                        "Cannot replay the CUDA Graph after reset is called."));
  size_t n = exec_graphs_.size();
  for (size_t i = 0; i < n; ++i) {
    if (!is_first_run_) {
      for (auto &hook : cudagraph_pre_replay_callbacks_[i]) {
        hook(exec_graphs_[i]);
      }
    }
    PADDLE_ENFORCE_GPU_SUCCESS(hipGraphLaunch(exec_graphs_[i], stream_));
  }
  is_first_run_ = false;
}

void CUDAGraph::BeginSegmentCapture() {
  ThrowErrorIfNotSupportCUDAGraph();
  PADDLE_ENFORCE_EQ(IsCapturing(),
                    true,
                    common::errors::PermissionDenied(
                        "BeginSegmentCapture should be called when CUDA "
                        "Graph is capturing."));
  if (IsThreadLocalCapturing()) {
    PADDLE_ENFORCE_EQ(IsThisThreadCapturing(),
                      true,
                      common::errors::PermissionDenied(
                          "When capturing CUDA Graph in the thread local mode, "
                          "you cannot begin segmented capturing in the thread "
                          "which is not the one that starts the capturing."));
  }
  PADDLE_ENFORCE_GPU_SUCCESS(hipStreamBeginCapture(
      capturing_graph_->stream_, capturing_graph_->capture_mode_));
  PADDLE_ENFORCE_EQ(IsValidCapturing(),
                    true,
                    common::errors::PermissionDenied(
                        "CUDA Graph should not be invalidated."));
  VLOG(10) << "Begin to capture CUDA Graph with ID " << capturing_graph_->id_
           << ", segment id " << capturing_graph_->graphs_.size()
           << ", memory pool id " << capturing_graph_->pool_id_;
}

void CUDAGraph::BeginCapture(phi::GPUPlace place,
                             gpuStream_t stream,
                             hipStreamCaptureMode mode,
                             bool enable_replace) {
  ThrowErrorIfNotSupportCUDAGraph();
  PADDLE_ENFORCE_EQ(IsCapturing(),
                    false,
                    common::errors::PermissionDenied(
                        "CUDA Graph can only captured one by one."));
  PADDLE_ENFORCE_NOT_NULL(
      stream,
      common::errors::PermissionDenied(
          "CUDA Graph cannot be captured in default CUDA stream 0."));
  capturing_graph_.reset(new CUDAGraph(enable_replace));
  capturing_graph_->place_ = place;
  capturing_graph_->stream_ = stream;
  capturing_graph_->capture_mode_ = mode;
  if (mode == hipStreamCaptureModeThreadLocal) {
    capturing_thread_id_ = std::this_thread::get_id();
    VLOG(10) << "Capturing CUDA Graph in thread local mode, thread id: "
             << capturing_thread_id_;
  }
  BeginSegmentCapture();
}

void CUDAGraph::EndSegmentCapture() {
  ThrowErrorIfNotSupportCUDAGraph();
  PADDLE_ENFORCE_EQ(
      IsCapturing(),
      true,
      common::errors::PermissionDenied("No CUDA Graph is capturing."));
  hipGraph_t graph;
  PADDLE_ENFORCE_GPU_SUCCESS(
      hipStreamEndCapture(capturing_graph_->stream_, &graph));
  auto num_nodes = static_cast<size_t>(-1);
  PADDLE_ENFORCE_GPU_SUCCESS(hipGraphGetNodes(graph, nullptr, &num_nodes));
  if (num_nodes == 0) {
    PADDLE_ENFORCE_GPU_SUCCESS(hipGraphDestroy(graph));
    VLOG(10) << "Skip empty CUDA Graph with ID " << capturing_graph_->id_
             << ", segment id " << capturing_graph_->graphs_.size()
             << ", memory pool id " << capturing_graph_->pool_id_;
    return;
  }

  for (auto &cudagraph_post_capture_callback :
       capturing_graph_->cudagraph_post_capture_callbacks_) {
    cudagraph_post_capture_callback();
  }
  capturing_graph_->cudagraph_post_capture_callbacks_.clear();

  capturing_graph_->cudagraph_pre_replay_callbacks_.emplace_back(
      CUDAGraphNodeLauncher::Instance().GetParameterSettersForExecGraph(graph));

  // if forward graph is registered, this graph is a backward graph
  // we check whether there is remain blocks that is unreleased by this
  hipGraphExec_t exec_graph;
  if (FLAGS_use_cuda_malloc_async_allocator &&
      FLAGS_auto_free_cudagraph_allocations_on_launch) {
    VLOG(1) << "hipGraphInstantiateFlagAutoFreeOnLaunch is enabled!";
    PADDLE_ENFORCE_GPU_SUCCESS(hipGraphInstantiateWithFlags(
        &exec_graph, graph, hipGraphInstantiateFlagAutoFreeOnLaunch));
  } else {
    PADDLE_ENFORCE_GPU_SUCCESS(
        hipGraphInstantiate(&exec_graph, graph, nullptr, nullptr, 0));
  }
  VLOG(10) << "End to capture CUDA Graph with ID " << capturing_graph_->id_
           << ", segment id " << capturing_graph_->graphs_.size()
           << ", memory pool id " << capturing_graph_->pool_id_;
  capturing_graph_->graphs_.emplace_back(graph);
  capturing_graph_->exec_graphs_.emplace_back(exec_graph);
}

std::unique_ptr<CUDAGraph> CUDAGraph::EndCapture() {
  EndSegmentCapture();
  capturing_thread_id_ = paddle::none;
  return std::move(capturing_graph_);
}

bool CUDAGraph::IsValidCapturing() {
  if (!IsCapturing()) return false;
  hipStreamCaptureStatus status;
  CUDAGraphID id;
  PADDLE_ENFORCE_GPU_SUCCESS(
      hipStreamGetCaptureInfo(capturing_graph_->stream_, &status, &id));
  return status == hipStreamCaptureStatusActive;
}

static std::string ConcatPath(const std::string &dirname,
                              const std::string &filename) {
#ifdef _WIN32
  const std::array<char, 3> kFileSep = {"\\"};
#else
  const std::array<char, 2> kFileSep = {"/"};
#endif
  if (!dirname.empty() && dirname.back() == kFileSep[0]) {
    return dirname + filename;
  } else {
    return dirname + kFileSep.data() + filename;
  }
}

void CUDAGraph::PrintToDotFiles(const std::string &dirname,
                                unsigned int flags) {
  ThrowErrorIfNotSupportCUDAGraph();
  PADDLE_THROW(common::errors::Unimplemented(
      "The print_to_dot_files() method is not supported on ROCm/HIP"));
}

void CUDAGraphNodeLauncher::KernelNodeLaunch(
    parameterSetter_t parameterSetter, gpuKernelCallback_t cudaKernelCallback) {
  if (UNLIKELY(phi::backends::gpu::CUDAGraph::IsThisThreadCapturing())) {
    unsigned int id = GenerateIdentifier();
    auto cudaFunc = cudaKernelCallback(id);

    parameterSetters[cudaFunc][id] = parameterSetter;
    VLOG(10) << "[KernelNodeLaunch] Launch kernel with cudaFunc = " << cudaFunc
             << " id = " << id;
  } else {
    cudaKernelCallback(0);
  }
}

std::vector<cudaGraphExecuterSetter_t>
CUDAGraphNodeLauncher::GetParameterSettersForExecGraph(hipGraph_t graph) {
  size_t num_nodes;
  PADDLE_ENFORCE_GPU_SUCCESS(hipGraphGetNodes(graph, nullptr, &num_nodes));
  std::vector<hipGraphNode_t> nodes(num_nodes);
  PADDLE_ENFORCE_GPU_SUCCESS(hipGraphGetNodes(graph, nodes.data(), &num_nodes));

  std::vector<std::function<void(hipGraphExec_t)>> hooks;
  for (auto node : nodes) {
    hipGraphNode_t gpuNode = node;
    hipGraphNodeType pType;
    PADDLE_ENFORCE_GPU_SUCCESS(hipGraphNodeGetType(gpuNode, &pType));
    if (pType == hipGraphNodeTypeKernel) {
      hipKernelNodeParams gpuParams;
      PADDLE_ENFORCE_GPU_SUCCESS(
          gpuGraphKernelNodeGetParams(gpuNode, &gpuParams));
      gpuKernelParams kernel_params(gpuParams.kernelParams);
      auto kernel =
          parameterSetters.find(static_cast<gpuFunction_t>(gpuParams.func));
      VLOG(10) << "[GetParameterSettersForExecGraph] gpuParams.func = "
               << gpuParams.func;
      // There exists a parameter setter
      if (kernel != parameterSetters.end()) {
        auto launchSequence = kernel->second;
        unsigned int id = kernel_params.As<int>(0);

        VLOG(10) << "[GetParameterSettersForExecGraph] Find launch kernel id = "
                 << id;
        auto parameterSetter = launchSequence.find(id);
        if (parameterSetter != launchSequence.end()) {
          auto setter = parameterSetter->second;
          hooks.emplace_back(
              [setter, gpuNode, gpuParams](hipGraphExec_t exec_graph) {
                gpuKernelParams kernel_params(gpuParams.kernelParams);
                setter(kernel_params);
                PADDLE_ENFORCE_GPU_SUCCESS(hipGraphExecKernelNodeSetParams(
                    exec_graph, gpuNode, &gpuParams));
              });
        } else {
          PADDLE_THROW(common::errors::InvalidArgument(
              "Error: does not find launch id"));
        }
      }
    }
  }

  return hooks;
}

}  // namespace gpu
}  // namespace backends
}  // namespace phi

#endif