diff --git a/paddle/fluid/imperative/nccl_context.cc b/paddle/fluid/imperative/nccl_context.cc index abee311d08cf38153d010082b0183223242cada9..9c2c9925a34e80bcef5e4975a8527155ac2bfe3a 100644 --- a/paddle/fluid/imperative/nccl_context.cc +++ b/paddle/fluid/imperative/nccl_context.cc @@ -49,16 +49,20 @@ void NCCLParallelContext::RecvNCCLID(const std::string &ep, address.sin_port = htons(port); int try_times = 0; + int retry_time = 0; while (true) { if (bind(server_fd, (struct sockaddr *)&address, sizeof(address)) < 0) { + retry_time = 3 * (try_times + 1); LOG(WARNING) << "Socket bind worker " << ep - << (try_times < 5 ? " failed, try again after 3 seconds." - : " failed, try again after 3 seconds. " - "Bind on endpoint %s failed. " - "Please confirm whether the " - "communication port or GPU card is " - "occupied."); - std::this_thread::sleep_for(std::chrono::seconds(3)); + << (try_times < 9 + ? " failed, try again after " + + std::to_string(retry_time) + " seconds." + : " failed, try again after " + + std::to_string(retry_time) + + " seconds. Bind on endpoint " + ep + + " failed. Please confirm whether the " + "communication port or GPU card is occupied."); + std::this_thread::sleep_for(std::chrono::seconds(retry_time)); ++try_times; continue; } @@ -129,16 +133,20 @@ void NCCLParallelContext::SendNCCLID(const std::string &ep, } int try_times = 0; + int retry_time = 0; while (true) { if (connect(sock, (struct sockaddr *)&serv_addr, sizeof(serv_addr)) < 0) { + retry_time = 3 * (try_times + 1); LOG(WARNING) << "Socket connect worker " << ep - << (try_times < 5 - ? " failed, try again after 3 seconds." - : " failed, try again after 3 seconds. Maybe that " - "some process is occupied the GPUs of this node " - "now, and you should kill those process manually."); - std::this_thread::sleep_for(std::chrono::seconds(3)); + << (try_times < 9 + ? " failed, try again after " + std::to_string(retry_time) + + " seconds." + : " failed, try again after " + std::to_string(retry_time) + + " seconds. Maybe that some process is occupied the " + "GPUs of this node now, and you should kill those " + "process manually."); + std::this_thread::sleep_for(std::chrono::seconds(retry_time)); ++try_times; continue; } diff --git a/python/paddle/distributed/parallel.py b/python/paddle/distributed/parallel.py index 16b031e116acdc2e06696740a0406daac783c58f..9b6691dac7545a70661115616842f46a13cc836f 100644 --- a/python/paddle/distributed/parallel.py +++ b/python/paddle/distributed/parallel.py @@ -125,7 +125,7 @@ def init_parallel_env(): if ParallelEnv().world_size < 2: return - # 3: init gloo context + # 3: init gloo context (step 1: httpsever start) ep_rank_0 = ParallelEnv().trainer_endpoints[0].split(":") ep_rank = ParallelEnv().trainer_endpoints[ParallelEnv().rank].split(":") manager = Manager() @@ -138,22 +138,6 @@ def init_parallel_env(): http_server.daemon = True http_server_d["running"] = True http_server.start() - wait_server_ready([ParallelEnv().trainer_endpoints[0]]) - - gloo_strategy = core.GlooParallelStrategy() - gloo_strategy.rank = ParallelEnv().rank - gloo_strategy.rank_num = ParallelEnv().world_size - gloo_strategy.ip_address = ep_rank_0[0] - gloo_strategy.ip_port = int(ep_rank_0[1]) - default_init_timeout_seconds = 3600 - default_run_timeout_seconds = 9999999 - gloo_strategy.init_seconds = default_init_timeout_seconds - gloo_strategy.run_seconds = default_run_timeout_seconds - gloo = core.GlooParallelContext(gloo_strategy) - gloo.init() - if ParallelEnv().rank == 0: - http_server_d["running"] = False - http_server.join() # 4. init NCCL ParallelStrategy strategy = ParallelStrategy() @@ -165,7 +149,7 @@ def init_parallel_env(): strategy.current_endpoint = ParallelEnv().current_endpoint # NOTE(chenweihang): [ why config global place here? ] - # the dygraph mode will be set to default mode, + # the dygraph mode will be set to default mode, # users will not call `dygraph.guard` or `enable_dygraph` # directly, if they want to switch default place, # they need to call a function to change default place, @@ -177,6 +161,27 @@ def init_parallel_env(): parallel_helper._set_parallel_ctx(core.NCCLParallelContext(strategy, place)) parallel_helper._init_parallel_ctx() + # 5: init gloo context (step 2: gloo init) + # dividing init_gloo into two part beacause nccl and gloo + # are separately looking for free ports which sometimes + # leads to port-conflict. + wait_server_ready([ParallelEnv().trainer_endpoints[0]]) + + gloo_strategy = core.GlooParallelStrategy() + gloo_strategy.rank = ParallelEnv().rank + gloo_strategy.rank_num = ParallelEnv().world_size + gloo_strategy.ip_address = ep_rank_0[0] + gloo_strategy.ip_port = int(ep_rank_0[1]) + default_init_timeout_seconds = 3600 + default_run_timeout_seconds = 9999999 + gloo_strategy.init_seconds = default_init_timeout_seconds + gloo_strategy.run_seconds = default_run_timeout_seconds + gloo = core.GlooParallelContext(gloo_strategy) + gloo.init() + if ParallelEnv().rank == 0: + http_server_d["running"] = False + http_server.join() + def get_rank(): """