the integrated communicator (#19849)

* add a base class for the Communicator
* add AsyncCommunicator Impl for async distributed training

paddle/fluid/framework/details/async_ssa_graph_executor.cc

@@ -86,13 +86,10 @@ void ProcessGraph(std::vector<ir::Graph *> graphs, Scope *scope) {
   if (send_varname_to_ctx.size() > 0) {
     VLOG(3) << "this is distribute mode, will use communicator";
 
-    if (operators::distributed::Communicator::GetInstance() == nullptr) {
-      operators::distributed::Communicator::Init(send_varname_to_ctx,
+    auto *instance = operators::distributed::Communicator::InitInstance<
+        operators::distributed::AsyncCommunicator>(send_varname_to_ctx,
                                                    recv_varname_to_ctx, scope);
-      operators::distributed::Communicator::GetInstance()->Start();
-    } else {
-      VLOG(3) << "communicator has been initialized, skip";
-    }
+    if (!instance->IsRunning()) instance->Start();
   }
 #endif
 }

paddle/fluid/operators/distributed/communicator.cc

@@ -52,14 +52,16 @@ inline double GetCurrentUS() {
   return 1e+6 * time.tv_sec + time.tv_usec;
 }
 
+std::once_flag Communicator::init_flag_;
 std::shared_ptr<Communicator> Communicator::communicator_(nullptr);
 
-Communicator::Communicator(const RpcCtxMap &send_varname_to_ctx,
+void AsyncCommunicator::InitImpl(const RpcCtxMap &send_varname_to_ctx,
                                  const RpcCtxMap &recv_varname_to_ctx,
-                           Scope *recv_scope)
-    : send_varname_to_ctx_(send_varname_to_ctx),
-      recv_varname_to_ctx_(recv_varname_to_ctx),
-      recv_scope_(recv_scope) {
+                                 Scope *recv_scope) {
+  send_varname_to_ctx_ = std::move(send_varname_to_ctx);
+  recv_varname_to_ctx_ = std::move(recv_varname_to_ctx);
+  recv_scope_ = std::move(recv_scope);
+
   // get all send information from graph, build vars_to_send
   VLOG(0) << "communicator_independent_recv_thread: "
           << FLAGS_communicator_independent_recv_thread;
@@ -98,7 +100,51 @@ Communicator::Communicator(const RpcCtxMap &send_varname_to_ctx,
   }
 }
 
-Communicator::~Communicator() {
+void AsyncCommunicator::InitImpl(const paddle::framework::ProgramDesc &program,
+                                 Scope *param_scope) {
+  using RpcCtxMap = operators::distributed::RpcCtxMap;
+  VLOG(3) << "ProcessGraph";
+  RpcCtxMap send_varname_to_ctx;
+  RpcCtxMap recv_varname_to_ctx;
+  for (auto *op : program.Block(0).AllOps()) {
+    VLOG(3) << "node name " << op->Type();
+    if (op->Type() == "send") {
+      auto send_var_name = op->Input("X")[0];
+      auto send_varnames = boost::get<std::vector<std::string>>(
+          op->GetNullableAttr("send_varnames"));
+      auto epmap =
+          boost::get<std::vector<std::string>>(op->GetNullableAttr("epmap"));
+      auto height_section =
+          boost::get<std::vector<int64_t>>(op->GetNullableAttr("sections"));
+      auto trainer_id = boost::get<int>(op->GetNullableAttr("trainer_id"));
+      send_varname_to_ctx[send_var_name] = operators::distributed::RpcContext(
+          send_var_name, send_varnames, epmap, height_section, trainer_id);
+      VLOG(3) << "find and init an send op: "
+              << send_varname_to_ctx[send_var_name];
+    } else if (op->Type() == "recv") {
+      auto do_not_run = boost::get<int>(op->GetNullableAttr("do_not_run"));
+      PADDLE_ENFORCE_GT(do_not_run, 0, "recv should not run!");
+      auto recv_var_name = op->Output("Out")[0];
+      auto recv_varnames = boost::get<std::vector<std::string>>(
+          op->GetNullableAttr("recv_varnames"));
+      auto epmap =
+          boost::get<std::vector<std::string>>(op->GetNullableAttr("epmap"));
+      auto trainer_id = boost::get<int>(op->GetNullableAttr("trainer_id"));
+      recv_varname_to_ctx[recv_var_name] = operators::distributed::RpcContext(
+          recv_var_name, recv_varnames, epmap, {}, trainer_id);
+    }
+  }
+
+  // init communicator here
+  if (send_varname_to_ctx.size() == 0 && recv_varname_to_ctx.size() == 0) {
+    LOG(WARNING) << "no var need to send and recv!!";
+  }
+
+  operators::distributed::AsyncCommunicator::InitImpl(
+      send_varname_to_ctx, recv_varname_to_ctx, param_scope);
+}
+
+AsyncCommunicator::~AsyncCommunicator() {
   if (FLAGS_v >= 3) {
     std::string msg("~Communicator");
     fwrite(msg.c_str(), msg.length(), 1, stdout);
@@ -112,7 +158,7 @@ Communicator::~Communicator() {
   }
 }
 
-void Communicator::SendThread() {
+void AsyncCommunicator::SendThread() {
   VLOG(3) << "SendThread start!";
   while (running_) {
     std::vector<std::future<void>> task_futures;
@@ -175,50 +221,12 @@ void Communicator::SendThread() {
 
     VLOG(3) << "run send graph use time "
             << after_run_send_graph - before_run_send_graph;
-    RecvNonIndependent();
+    Recv();
   }
   VLOG(0) << "communicator stopped, send thread exit";
 }
 
-void Communicator::RecvNonIndependent() {
-  if (FLAGS_communicator_independent_recv_thread) {
-    return;
-  }
-
-  auto grad_num = grad_num_.load();
-  if (grad_num > 0) {
-    RecvAll();
-    grad_num_.store(0);
-  } else {
-    std::this_thread::sleep_for(std::chrono::milliseconds(10));
-  }
-}
-
-void Communicator::RecvAll() {
-  VLOG(3) << "parallel run recv graph";
-  if (!running_) return;
-  auto before_send = GetCurrentUS();
-  std::vector<std::future<void>> task_futures;
-  task_futures.reserve(recv_varname_to_ctx_.size());
-  for (auto &iter : recv_varname_to_ctx_) {
-    auto recv_task = [this, &iter] {
-      auto &var_name = iter.first;
-      VLOG(4) << "recv var " << var_name;
-      auto recv_functor = distributed::ParameterRecv<float>();
-      if (!FLAGS_communicator_fake_rpc) {
-        recv_functor(iter.second, *recv_scope_);
-      }
-    };
-    task_futures.emplace_back(recv_threadpool_->enqueue(std::move(recv_task)));
-  }
-  for (auto &task : task_futures) {
-    task.wait();
-  }
-  auto after_recv = GetCurrentUS();
-  VLOG(1) << "run recv graph use time " << after_recv - before_send;
-}
-
-void Communicator::RecvThread() {
+void AsyncCommunicator::RecvThread() {
   VLOG(3) << "RecvThread start!";
   while (running_) {
     auto grad_num = grad_num_.load();
@@ -233,7 +241,7 @@ void Communicator::RecvThread() {
   VLOG(0) << "communicator stopped, recv thread exit";
 }
 
-void Communicator::Send(const std::string &var_name,
+void AsyncCommunicator::Send(const std::string &var_name,
                              const framework::Scope &scope) {
   VLOG(3) << "communicator send " << var_name;
   // push var into send queue by var_name
@@ -255,56 +263,45 @@ void Communicator::Send(const std::string &var_name,
   }
 }
 
-void Communicator::Init(const paddle::framework::ProgramDesc &program,
-                        Scope *param_scope) {
-  using RpcCtxMap = operators::distributed::RpcCtxMap;
-  VLOG(3) << "ProcessGraph";
-  RpcCtxMap send_varname_to_ctx;
-  RpcCtxMap recv_varname_to_ctx;
-  for (auto *op : program.Block(0).AllOps()) {
-    VLOG(3) << "node name " << op->Type();
-    if (op->Type() == "send") {
-      auto send_var_name = op->Input("X")[0];
-      auto send_varnames = boost::get<std::vector<std::string>>(
-          op->GetNullableAttr("send_varnames"));
-      auto epmap =
-          boost::get<std::vector<std::string>>(op->GetNullableAttr("epmap"));
-      auto height_section =
-          boost::get<std::vector<int64_t>>(op->GetNullableAttr("sections"));
-      auto trainer_id = boost::get<int>(op->GetNullableAttr("trainer_id"));
-      send_varname_to_ctx[send_var_name] = operators::distributed::RpcContext(
-          send_var_name, send_varnames, epmap, height_section, trainer_id);
-      VLOG(3) << "find and init an send op: "
-              << send_varname_to_ctx[send_var_name];
-    } else if (op->Type() == "recv") {
-      auto do_not_run = boost::get<int>(op->GetNullableAttr("do_not_run"));
-      PADDLE_ENFORCE_GT(do_not_run, 0, "recv should not run!");
-      auto recv_var_name = op->Output("Out")[0];
-      auto recv_varnames = boost::get<std::vector<std::string>>(
-          op->GetNullableAttr("recv_varnames"));
-      auto epmap =
-          boost::get<std::vector<std::string>>(op->GetNullableAttr("epmap"));
-      auto trainer_id = boost::get<int>(op->GetNullableAttr("trainer_id"));
-      recv_varname_to_ctx[recv_var_name] = operators::distributed::RpcContext(
-          recv_var_name, recv_varnames, epmap, {}, trainer_id);
-    }
+void AsyncCommunicator::Recv() {
+  if (FLAGS_communicator_independent_recv_thread) {
+    return;
   }
 
-  // init communicator here
-  if (send_varname_to_ctx.size() == 0 && recv_varname_to_ctx.size() == 0) {
-    LOG(WARNING) << "no var need to send and recv!!";
+  auto grad_num = grad_num_.load();
+  if (grad_num > 0) {
+    RecvAll();
+    grad_num_.store(0);
+  } else {
+    std::this_thread::sleep_for(std::chrono::milliseconds(10));
   }
-  operators::distributed::Communicator::Init(send_varname_to_ctx,
-                                             recv_varname_to_ctx, param_scope);
 }
 
-Communicator *Communicator::GetInstance() { return communicator_.get(); }
-
-std::shared_ptr<Communicator> Communicator::GetInstantcePtr() {
-  return communicator_;
+void AsyncCommunicator::RecvAll() {
+  VLOG(3) << "parallel run recv graph";
+  if (!running_) return;
+  auto before_send = GetCurrentUS();
+  std::vector<std::future<void>> task_futures;
+  task_futures.reserve(recv_varname_to_ctx_.size());
+  for (auto &iter : recv_varname_to_ctx_) {
+    auto recv_task = [this, &iter] {
+      auto &var_name = iter.first;
+      VLOG(4) << "recv var " << var_name;
+      auto recv_functor = distributed::ParameterRecv<float>();
+      if (!FLAGS_communicator_fake_rpc) {
+        recv_functor(iter.second, *recv_scope_);
+      }
+    };
+    task_futures.emplace_back(recv_threadpool_->enqueue(std::move(recv_task)));
+  }
+  for (auto &task : task_futures) {
+    task.wait();
+  }
+  auto after_recv = GetCurrentUS();
+  VLOG(1) << "run recv graph use time " << after_recv - before_send;
 }
 
-void Communicator::Start() {
+void AsyncCommunicator::Start() {
   VLOG(0) << "Communicator start";
   if (!communicator_) {
     VLOG(0) << "Communicator is not inited, do nothing";
@@ -313,15 +310,15 @@ void Communicator::Start() {
     running_ = true;
     // start send and recv thread
     send_thread_.reset(
-        new std::thread(std::bind(&Communicator::SendThread, this)));
+        new std::thread(std::bind(&AsyncCommunicator::SendThread, this)));
     if (FLAGS_communicator_independent_recv_thread) {
       recv_thread_.reset(
-          new std::thread(std::bind(&Communicator::RecvThread, this)));
+          new std::thread(std::bind(&AsyncCommunicator::RecvThread, this)));
     }
   }
 }
 
-void Communicator::Stop() {
+void AsyncCommunicator::Stop() {
   VLOG(0) << "Communicator stop";
   running_ = false;
   if (!communicator_) {

paddle/fluid/operators/distributed/communicator.h

@@ -161,27 +161,97 @@ using RpcCtxMap = std::unordered_map<std::string, RpcContext>;
 
 class Communicator {
  public:
-  Communicator(const RpcCtxMap& send_varname_to_ctx,
-               const RpcCtxMap& recv_varname_to_ctx, Scope* recv_scope);
+  Communicator() {}
+  virtual ~Communicator() {}
 
-  ~Communicator();
+  virtual void Start() = 0;
+  virtual void Stop() = 0;
+  virtual bool IsRunning() { return running_; }
 
-  void Start();
-  void Stop();
+  virtual void Send(const std::string& var_name,
+                    const framework::Scope& scope) = 0;
+  virtual void Recv() = 0;
 
-  bool IsRunning() { return running_; }
+  virtual void InitImpl(const RpcCtxMap& send_varname_to_ctx,
+                        const RpcCtxMap& recv_varname_to_ctx,
+                        Scope* recv_scope) = 0;
 
-  // send grad
-  void Send(const std::string& var_name, const framework::Scope& scope);
+  virtual void InitImpl(const paddle::framework::ProgramDesc& program,
+                        Scope* recv_scope) = 0;
 
- private:
-  // recv all parameter
+  static Communicator* GetInstance() { return communicator_.get(); }
+
+  static std::shared_ptr<Communicator> GetInstantcePtr() {
+    return communicator_;
+  }
+
+  template <typename T>
+  static Communicator* InitInstance(const RpcCtxMap& send_varname_to_ctx,
+                                    const RpcCtxMap& recv_varname_to_ctx,
+                                    Scope* recv_scope) {
+    std::call_once(init_flag_, &Communicator::InitWithRpcCtx<T>,
+                   send_varname_to_ctx, recv_varname_to_ctx, recv_scope);
+    return communicator_.get();
+  }
+
+  // Init is called by InitInstance.
+  template <typename T>
+  static void InitWithRpcCtx(const RpcCtxMap& send_varname_to_ctx,
+                             const RpcCtxMap& recv_varname_to_ctx,
+                             Scope* recv_scope) {
+    if (communicator_.get() == nullptr) {
+      communicator_.reset(new T());
+      communicator_->InitImpl(send_varname_to_ctx, recv_varname_to_ctx,
+                              recv_scope);
+    }
+  }
+
+  template <typename T>
+  static Communicator* InitInstance(
+      const paddle::framework::ProgramDesc& program, Scope* recv_scope) {
+    std::call_once(init_flag_, &Communicator::InitWithProgram<T>, program,
+                   recv_scope);
+    return communicator_.get();
+  }
+
+  template <typename T>
+  static void InitWithProgram(const paddle::framework::ProgramDesc& program,
+                              Scope* recv_scope) {
+    if (communicator_.get() == nullptr) {
+      communicator_.reset(new T());
+      communicator_->InitImpl(program, recv_scope);
+    }
+  }
+
+ protected:
+  bool running_ = false;
+  static std::shared_ptr<Communicator> communicator_;
+  static std::once_flag init_flag_;
+};
+
+class AsyncCommunicator : public Communicator {
+ public:
+  AsyncCommunicator() {}
+  ~AsyncCommunicator();
+  void Start() override;
+  void Stop() override;
+
+  void Send(const std::string& var_name,
+            const framework::Scope& scope) override;
+  void Recv() override;
   void RecvAll();
-  void RecvNonIndependent();
+
+  void InitImpl(const RpcCtxMap& send_varname_to_ctx,
+                const RpcCtxMap& recv_varname_to_ctx,
+                Scope* recv_scope) override;
+
+  void InitImpl(const paddle::framework::ProgramDesc& program,
+                Scope* recv_scope) override;
+
   void SendThread();
   void RecvThread();
 
-  bool running_ = false;
+ private:
   std::unordered_map<std::string,
                      std::shared_ptr<BlockingQueue<std::shared_ptr<Variable>>>>
       send_varname_to_queue_;
@@ -194,26 +264,6 @@ class Communicator {
   std::unique_ptr<::ThreadPool> send_threadpool_{nullptr};
   std::unique_ptr<::ThreadPool> recv_threadpool_{nullptr};
   std::atomic_uint grad_num_{0};  // the num of gradient sent since last recv
-
-  // the following code is for initialize the commnunicator
- public:
-  static void Init(const RpcCtxMap& send_varname_to_ctx,
-                   const RpcCtxMap& recv_varname_to_ctx, Scope* recv_scope) {
-    if (communicator_ == nullptr) {
-      communicator_.reset(new Communicator(send_varname_to_ctx,
-                                           recv_varname_to_ctx, recv_scope));
-    }
-  }
-
-  static void Init(const paddle::framework::ProgramDesc& program,
-                   Scope* param_scope);
-
-  static Communicator* GetInstance();
-
-  static std::shared_ptr<Communicator> GetInstantcePtr();
-
- private:
-  static std::shared_ptr<Communicator> communicator_;
 };
 
 }  // namespace distributed

paddle/fluid/operators/distributed_ops/send_op.cc

@@ -48,14 +48,7 @@ class SendOp : public framework::OperatorBase {
 
     if (send_varnames.size() > 0) {
       PADDLE_ENFORCE_EQ(ins.size(), 1, "");
-      if (distributed::Communicator::GetInstance() == nullptr) {
-        auto send_functor = distributed::ParameterSend<float>();
-        auto rpc_ctx = distributed::RpcContext(ins[0], send_varnames, epmap,
-                                               height_sections, trainer_id);
-        send_functor(rpc_ctx, scope, true);
-      } else {
       distributed::Communicator::GetInstance()->Send(ins[0], scope);
-      }
     } else {
       platform::DeviceContextPool& pool =
           platform::DeviceContextPool::Instance();

paddle/fluid/pybind/communicator_py.cc

@@ -26,6 +26,7 @@ namespace py = pybind11;
 
 using paddle::framework::ProgramDesc;
 using paddle::operators::distributed::Communicator;
+using paddle::operators::distributed::AsyncCommunicator;
 using paddle::framework::Scope;
 
 namespace paddle {
@@ -36,7 +37,7 @@ void BindCommunicator(py::module* m) {
   py::class_<Communicator, std::shared_ptr<Communicator>>(*m,
                                                           "DistCommunicator")
       .def(py::init([](const ProgramDesc& program, Scope* param_scope) {
-        Communicator::Init(program, param_scope);
+        Communicator::InitInstance<AsyncCommunicator>(program, param_scope);
         return Communicator::GetInstantcePtr();
       }))
       .def("stop", &Communicator::Stop)

python/paddle/fluid/tests/unittests/test_dist_base.py

@@ -75,11 +75,14 @@ class TestDistRunnerBase(object):
                        sync_mode,
                        dc_asgd=False,
                        current_endpoint=None,
-                       nccl_comm_num=1):
+                       nccl_comm_num=1,
+                       hogwild_mode=False):
         # NOTE: import fluid until runtime, or else forking processes will cause error.
         config = fluid.DistributeTranspilerConfig()
         config.enable_dc_asgd = dc_asgd
         config.sync_mode = sync_mode
+        config.runtime_split_send_recv = hogwild_mode
+
         if nccl_comm_num > 1:
             config.nccl_comm_num = nccl_comm_num
         # config.runtime_split_send_recv = True
@@ -89,6 +92,7 @@ class TestDistRunnerBase(object):
             program=main_program,
             pservers=pserver_endpoints,
             trainers=trainers,
+            sync_mode=sync_mode,
             current_endpoint=current_endpoint)
         return t
 
@@ -96,9 +100,15 @@ class TestDistRunnerBase(object):
         self.lr = args.lr
         self.get_model(batch_size=args.batch_size)
         # NOTE: pserver should not call memory optimize
-        t = self.get_transpiler(args.trainer_id,
-                                fluid.default_main_program(), args.endpoints,
-                                args.trainers, args.sync_mode, args.dc_asgd)
+
+        t = self.get_transpiler(
+            trainer_id=args.trainer_id,
+            main_program=fluid.default_main_program(),
+            pserver_endpoints=args.endpoints,
+            trainers=args.trainers,
+            sync_mode=args.sync_mode,
+            dc_asgd=args.dc_asgd,
+            hogwild_mode=args.hogwild)
         pserver_prog = t.get_pserver_program(args.current_endpoint)
         startup_prog = t.get_startup_program(args.current_endpoint,
                                              pserver_prog)
@@ -120,7 +130,7 @@ class TestDistRunnerBase(object):
 
         dist_strategy = DistributedStrategy()
         dist_strategy.exec_strategy = exec_strategy
-        dist_strategy.fuse_memory_size = 1  #MB
+        dist_strategy.fuse_memory_size = 1  # MB
         dist_strategy.fuse_laryer_size = 1
         if args.use_local_sgd:
             dist_strategy.use_local_sgd = True
@@ -130,8 +140,8 @@ class TestDistRunnerBase(object):
         role = role_maker.PaddleCloudRoleMaker(is_collective=True)
         fleet.init(role)
         print_to_err("gpu_fleet", "fleet.node_num:")
-        #"fleet.node_id:", fleet.node_id(),
-        #"fleet.trainer_num:", fleet.worker_num())
+        # "fleet.node_id:", fleet.node_id(),
+        # "fleet.trainer_num:", fleet.worker_num())
 
         test_program, avg_cost, train_reader, test_reader, batch_acc, predict = \
             self.get_model(batch_size=args.batch_size, dist_strategy=dist_strategy)
@@ -196,10 +206,15 @@ class TestDistRunnerBase(object):
             print_to_err(
                 type(self).__name__,
                 "begin to run transpile on trainer with pserver mode")
-            t = self.get_transpiler(args.trainer_id,
-                                    fluid.default_main_program(),
-                                    args.endpoints, args.trainers,
-                                    args.sync_mode, args.dc_asgd)
+            t = self.get_transpiler(
+                trainer_id=args.trainer_id,
+                main_program=fluid.default_main_program(),
+                pserver_endpoints=args.endpoints,
+                trainers=args.trainers,
+                sync_mode=args.sync_mode,
+                dc_asgd=args.dc_asgd,
+                hogwild_mode=args.hogwild)
+
             trainer_prog = t.get_trainer_program()
             print_to_err(
                 type(self).__name__,
@@ -251,6 +266,9 @@ class TestDistRunnerBase(object):
         build_stra.enable_inplace = False
         build_stra.memory_optimize = False
 
+        if args.hogwild:
+            build_stra.async_mode = True
+
         if args.enable_backward_deps:
             build_stra.enable_backward_optimizer_op_deps = True
 
@@ -411,6 +429,7 @@ def runtime_main(test_class):
     parser.add_argument('--use_dgc', action='store_true')
     parser.add_argument('--use_reduce', action='store_true')
     parser.add_argument('--dc_asgd', action='store_true')
+    parser.add_argument('--hogwild', action='store_true')
     parser.add_argument(
         '--use_reader_alloc', action='store_true', required=False)
     parser.add_argument('--batch_size', required=False, type=int, default=2)
@@ -467,6 +486,7 @@ class TestDistBase(unittest.TestCase):
             self._find_free_port(), self._find_free_port())
         self._python_interp = sys.executable
         self._sync_mode = True
+        self._hogwild_mode = False
         self._enforce_place = None
         self._use_reduce = False
         self._dc_asgd = False  # must use with async mode
@@ -630,6 +650,9 @@ class TestDistBase(unittest.TestCase):
         if self._sync_mode:
             tr0_cmd += " --sync_mode"
             tr1_cmd += " --sync_mode"
+        if self._hogwild_mode:
+            tr0_cmd += " --hogwild"
+            tr1_cmd += " --hogwild"
         if self._use_reduce:
             tr0_cmd += " --use_reduce"
             tr1_cmd += " --use_reduce"
@@ -825,7 +848,7 @@ class TestDistBase(unittest.TestCase):
             required_envs["GLOG_v"] = "10"
             required_envs["GLOG_logtostderr"] = "1"
 
-        local_losses\
+        local_losses \
             = self._run_local(model_file, required_envs,
                               check_error_log)
         if self._nccl2_mode:

python/paddle/fluid/tests/unittests/test_dist_ctr.py

@@ -11,6 +11,7 @@
 # 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.
+
 from __future__ import print_function
 
 import os
@@ -29,14 +30,13 @@ def skip_ci(func):
     return __func__
 
 
-@skip_ci
 class TestDistCTR2x2(TestDistBase):
     def _setup_config(self):
         self._sync_mode = True
         self._enforce_place = "CPU"
 
     def test_dist_ctr(self):
-        self.check_with_place("dist_ctr.py", delta=1e-7, check_error_log=False)
+        self.check_with_place("dist_ctr.py", delta=1e-2, check_error_log=False)
 
 
 @skip_ci
@@ -54,5 +54,40 @@ class TestDistCTRWithL2Decay2x2(TestDistBase):
             need_envs=need_envs)
 
 
+class TestDistCTR2x2_ASYNC(TestDistBase):
+    def _setup_config(self):
+        self._sync_mode = False
+        self._hogwild_mode = True
+        self._enforce_place = "CPU"
+
+    def test_dist_ctr(self):
+        need_envs = {
+            "FLAGS_communicator_send_queue_size": "2",
+            "FLAGS_communicator_max_merge_var_num": "2",
+            "FLAGS_communicator_max_send_grad_num_before_recv": "2",
+        }
+
+        self.check_with_place(
+            "dist_ctr.py", delta=100, check_error_log=True, need_envs=need_envs)
+
+
+class TestDistCTR2x2_ASYNC2(TestDistBase):
+    def _setup_config(self):
+        self._sync_mode = False
+        self._hogwild_mode = True
+        self._enforce_place = "CPU"
+
+    def test_dist_ctr(self):
+        need_envs = {
+            "FLAGS_communicator_send_queue_size": "2",
+            "FLAGS_communicator_max_merge_var_num": "2",
+            "FLAGS_communicator_max_send_grad_num_before_recv": "2",
+            "FLAGS_communicator_independent_recv_thread": "0"
+        }
+
+        self.check_with_place(
+            "dist_ctr.py", delta=100, check_error_log=True, need_envs=need_envs)
+
+
 if __name__ == "__main__":
     unittest.main()

python/paddle/fluid/tests/unittests/test_dist_fleet_ctr.py

@@ -30,7 +30,6 @@ def skip_ci(func):
     return __func__
 
 
-@skip_ci
 class TestDistMnist2x2(TestFleetBase):
     def _setup_config(self):
         self._sync_mode = False

python/paddle/fluid/tests/unittests/test_dist_simnet_bow.py

@@ -33,7 +33,7 @@ class TestDistSimnetBowDense2x2(TestDistBase):
         self.check_with_place(
             "dist_simnet_bow.py",
             delta=1e-5,
-            check_error_log=False,
+            check_error_log=True,
             need_envs=need_envs)