tensorflow/core/distributed_runtime/rpc/grpc_worker_cache.cc

/* Copyright 2016 The TensorFlow 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 "tensorflow/core/distributed_runtime/rpc/grpc_worker_cache.h"

#include "tensorflow/core/distributed_runtime/rpc/coordination/grpc_coordination_client.h"
#include "tensorflow/core/distributed_runtime/rpc/eager/grpc_eager_client.h"
#include "tensorflow/core/distributed_runtime/rpc/grpc_remote_worker.h"
#include "tensorflow/core/distributed_runtime/rpc/grpc_util.h"
#include "tensorflow/core/distributed_runtime/worker_cache_logger.h"
#include "tensorflow/core/distributed_runtime/worker_cache_partial.h"
#include "tensorflow/core/distributed_runtime/worker_interface.h"
#include "tensorflow/core/platform/cpu_info.h"
#include "tensorflow/core/platform/mutex.h"
#include "tensorflow/core/util/env_var.h"

namespace tensorflow {

namespace {

class GrpcWorkerCache : public WorkerCachePartial {
 public:
  explicit GrpcWorkerCache(std::shared_ptr<GrpcChannelCache> channel_cache,
                           WorkerInterface* local_worker,
                           const string& local_target,
                           GrpcWorkerEnv* worker_env)
      : local_target_(local_target),
        local_worker_(local_worker),
        channel_cache_(channel_cache),
        worker_env_(worker_env),
        next_round_robin_assignment_(0) {}

  void ListWorkers(std::vector<string>* workers) const override {
    channel_cache_->ListWorkers(workers);
  }

  void ListWorkersInJob(const string& job_name,
                        std::vector<string>* workers) const override {
    channel_cache_->ListWorkersInJob(job_name, workers);
  }

  WorkerInterface* GetOrCreateWorker(const string& target) override {
    if (target == local_target_) {
      return local_worker_;
    } else {
      SharedGrpcChannelPtr channel = channel_cache_->FindWorkerChannel(target);
      if (!channel) {
        return nullptr;
      }
      size_t index = AssignWorkerToThread(target);
      return NewGrpcRemoteWorker(
          channel, worker_env_->GetCompletionQueue(index),
          worker_env_->GetThreadPool(), &logger_, target);
    }
  }

  void ReleaseWorker(const string& target, WorkerInterface* worker) override {
    if (target == local_target_) {
      CHECK_EQ(worker, local_worker_)
          << "Releasing a worker that was not returned by this WorkerCache";
    } else {
      WorkerCacheInterface::ReleaseWorker(target, worker);
    }
  }

  Status GetEagerClientCache(
      std::unique_ptr<eager::EagerClientCache>* eager_client_cache) override {
    eager_client_cache->reset(eager::NewGrpcEagerClientCache(channel_cache_));
    return OkStatus();
  }

  Status GetCoordinationClientCache(std::unique_ptr<CoordinationClientCache>*
                                        coordination_client_cache) override {
    coordination_client_cache->reset(
        NewGrpcCoordinationClientCache(channel_cache_));
    return OkStatus();
  }

  void SetLogging(bool v) override { logger_.SetLogging(v); }

  void ClearLogs() override { logger_.ClearLogs(); }

  bool RetrieveLogs(int64_t step_id, StepStats* ss) override {
    return logger_.RetrieveLogs(step_id, ss);
  }

 private:
  size_t AssignWorkerToThread(const string& target) {
    // Round-robin target assignment, but keeps the same target on the same
    // polling thread always, as this is important for gRPC performance
    mutex_lock lock(assignment_mu_);
    auto it = target_assignments_.find(target);
    if (it == target_assignments_.end()) {
      it = target_assignments_
               .insert(std::make_pair(target,
                                      (next_round_robin_assignment_++) %
                                          worker_env_->CompletionQueueSize()))
               .first;
    }
    return it->second;
  }

  const string local_target_;
  WorkerInterface* const local_worker_;  // Not owned.
  std::shared_ptr<GrpcChannelCache> channel_cache_;
  WorkerCacheLogger logger_;
  GrpcWorkerEnv* worker_env_;  // Not owned

  mutex assignment_mu_;
  std::unordered_map<std::string, size_t> target_assignments_
      TF_GUARDED_BY(assignment_mu_);
  size_t next_round_robin_assignment_ TF_GUARDED_BY(assignment_mu_);
};

}  // namespace

GrpcWorkerEnv::GrpcWorkerEnv(size_t num_completion_queues, size_t num_threads)
    : threadpool_(new thread::ThreadPool(
          Env::Default(), ThreadOptions(), "GrpcWorkerEnvQueues", num_threads,
          /*low_latency_hint=*/false, /*allocator=*/nullptr)),
      threads_(num_completion_queues) {}

GrpcWorkerEnv::~GrpcWorkerEnv() { threads_.clear(); }

GrpcWorkerEnv::GrpcWorkerCacheThread::GrpcWorkerCacheThread() {
  thread_.reset(Env::Default()->StartThread(
      ThreadOptions(), "GrpcWorkerEnvPool", [this]() {
        void* tag;
        bool ok;
        while (completion_queue_.Next(&tag, &ok)) {
          GrpcClientCQTag* callback_tag = static_cast<GrpcClientCQTag*>(tag);
          callback_tag->OnCompleted(ok);
        }
      }));
}

GrpcWorkerEnv::GrpcWorkerCacheThread::~GrpcWorkerCacheThread() {
  completion_queue_.Shutdown();
  thread_.reset();
}

GrpcWorkerEnv* CreateGrpcWorkerEnv() {
  int num_cpus = port::NumSchedulableCPUs();
  int64_t num_completion_queues;
  Status status = ReadInt64FromEnvVar("TF_GRPC_WORKER_CACHE_QUEUES", 64,
                                      &num_completion_queues);
  if (!status.ok()) {
    LOG(ERROR) << "Error parsing TF_GRPC_WORKER_CACHE_QUEUES: " << status;
  }
  int64_t num_threads;
  status = ReadInt64FromEnvVar("TF_GRPC_WORKER_CACHE_THREADS", num_cpus,
                               &num_threads);
  if (!status.ok()) {
    LOG(ERROR) << "Error parsing TF_GRPC_WORKER_CACHE_THREADS: " << status;
  }
  return new GrpcWorkerEnv(num_completion_queues, num_threads);
}

WorkerCacheInterface* NewGrpcWorkerCache(std::shared_ptr<GrpcChannelCache> cc,
                                         GrpcWorkerEnv* worker_env) {
  return new GrpcWorkerCache(cc, /*local_worker=*/nullptr, /*local_target=*/"",
                             worker_env);
}

WorkerCacheInterface* NewGrpcWorkerCacheWithLocalWorker(
    std::shared_ptr<GrpcChannelCache> cc, GrpcWorkerEnv* worker_env,
    WorkerInterface* local_worker, const string& local_target) {
  return new GrpcWorkerCache(cc, local_worker, local_target, worker_env);
}

}  // namespace tensorflow