From d144310415c04966746bfd1b9315fbfa36a81b11 Mon Sep 17 00:00:00 2001 From: Dong Zhihong Date: Fri, 13 Oct 2017 16:03:26 -0700 Subject: [PATCH] "nccl add interface" --- paddle/operators/CMakeLists.txt | 1 + paddle/operators/nccl/CMakeLists.txt | 8 ++ paddle/operators/nccl/nccl_gpu_common.cc | 49 ++++++++++ paddle/operators/nccl/nccl_gpu_common.h | 92 +++++++++++++++---- paddle/operators/nccl/nccl_gpu_common_test.cc | 23 +++++ paddle/operators/nccl/nccl_ops.cc | 57 ++++++------ paddle/operators/nccl/nccl_ops.h | 58 +++++++----- paddle/platform/place.h | 1 + .../v2/framework/tests/test_nccl_ops.py | 60 +++++++++++- 9 files changed, 279 insertions(+), 70 deletions(-) create mode 100644 paddle/operators/nccl/CMakeLists.txt create mode 100644 paddle/operators/nccl/nccl_gpu_common_test.cc diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index ad941bde2..702a71d75 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -106,6 +106,7 @@ function(op_library TARGET) endfunction() add_subdirectory(math) +add_subdirectory(nccl) set(DEPS_OPS recurrent_op diff --git a/paddle/operators/nccl/CMakeLists.txt b/paddle/operators/nccl/CMakeLists.txt new file mode 100644 index 000000000..05c27f08f --- /dev/null +++ b/paddle/operators/nccl/CMakeLists.txt @@ -0,0 +1,8 @@ +if(WITH_GPU) + nv_library(nccl_common SRCS nccl_gpu_common DEPS device_context operator) + nv_library(nccl_op SRCS nccl_ops.cc DEPS nccl_common) +else() + cc_library(nccl_common SRCS nccl_gpu_common DEPS device_context operator) +endif() + +cc_test(nccl_gpu_common_test SRCS nccl_gpu_common_test.cc DEPS nccl_common) diff --git a/paddle/operators/nccl/nccl_gpu_common.cc b/paddle/operators/nccl/nccl_gpu_common.cc index 0144d9396..492d79ca5 100644 --- a/paddle/operators/nccl/nccl_gpu_common.cc +++ b/paddle/operators/nccl/nccl_gpu_common.cc @@ -1,9 +1,58 @@ #include "paddle/operators/nccl/nccl_gpu_common.h" +#include "paddle/platform/gpu_info.h" namespace paddle { namespace platform { +NCCLManager::NCCLManager() {} +NCCLManager::~NCCLManager() { + for (auto& p : comm_table) { + auto* comm = p.second; + auto& gpus_ = comm->gpus_; + for (int i = 0; i < gpus_.size(); ++i) { + int gid = gpus_[i]; + platform::SetDeviceId(gid); + + // mapping gid to idx + int idx = gid % gpus_.size(); + // wait finish + NCCL_CHECK( + cudaStreamWaitEvent(*comm->streams_[idx], comm->events_[idx], 0)); + + NCCL_CHECK(cudaEventDestroy(comm->events_[idx])); + + NCCL_CHECK(ncclCommDestroy(comm->comms_[idx])); + } + delete comm; + } +} + +Communicator* NCCLManager::GetCommunicator(const std::vector& gpus) const { + std::string key; + for (auto& id : gpus) { + key += std::to_string(id); + } + std::sort(key.begin(), key.end()); + + std::mutex mu; + std::lock_guard lk(mu); + auto* comm = comm_table[key]; + if (comm == nullptr) { + comm = new Communicator(gpus.size()); + NCCL_CHECK(ncclCommInitAll(comm->comms_.data(), gpus.size(), gpus.data())); + + for (size_t i = 0; i < gpus.size(); ++i) { + platform::SetDeviceId(gpus[i]); + + // block wait + NCCL_CHECK(cudaEventCreateWithFlags( + &events_[i], cudaEventBlockingSync | cudaEventDisableTiming)); + } + comm_table[key] = comm; + } + return comm; +} } // namespace operators } // namespace paddle diff --git a/paddle/operators/nccl/nccl_gpu_common.h b/paddle/operators/nccl/nccl_gpu_common.h index cace87807..a50490f39 100644 --- a/paddle/operators/nccl/nccl_gpu_common.h +++ b/paddle/operators/nccl/nccl_gpu_common.h @@ -1,17 +1,62 @@ #pragma once #include +#include +#include #include #include -#include -#include +#include #include +#include #include "paddle/platform/device_context.h" namespace paddle { namespace platform { +#define NCCL_CHECK(condition) \ + do { \ + ncclResult_t ret = (condition); \ + PADDLE_ENFORCE(ret == ncclSuccess, "Error invoking NCCL: ", __FILE__, \ + __LINE__, ncclGetErrorString(ret)); \ + } while (0) + +class WaitGroup { + public: + inline void Add(int n) { + std::unique_lock lk(mu_); + PADDLE_ENFORCE(n >= 0, "add wait must >=0."); + counter_ += n; + } + + inline void Done(int n) { + std::unique_lock lk(mu_); + PADDLE_ENFORCE(n <= counter_, " wait group done unmatch to add."); + counter_ -= n; + if (counter_ == 0) { + cv_.notify_all(); + } + } + + inline void Add() { Add(1); } + + inline void Done() { Done(1); } + + inline void Wait() { + std::unique_lock lk(mu_); + cv_.wait(lk, [&] { return counter_ == 0; }); + } + + inline int GetCount() { + std::unique_lock lk(mu_); + return counter_; + } + + private: + int counter_ = 0; + std::mutex mu_; + std::condition_variable cv_; +}; // class NCCLContext : public DeviceContext { // public: @@ -23,8 +68,26 @@ namespace platform { // std::vector streams_; // }; +// TODO(dzh) : make resources managed unified with framework +struct Communicator { + std::vector comms_; + std::vector streams_; + std::vector events_; + std::vector gpus_; + WaitGroup wg_; + int root_gpu = -1; + // cudaEvent_t root_monitor; + explicit Communicator(const std::vector& gpus) : gpus_(gpus) { + comms_.resize(gpus.size()); + streams_.resize(gpus.size()); + events_.resize(gpus.size()); + } + // Communicator(int num_device): comms_.resize(num_device) {} + + inline int get_root_gpu() const { return root_gpu; } -class Communicator; + inline void set_root_gpu(int id) { root_gpu = id; } +}; class NCCLManager { public: @@ -33,27 +96,20 @@ class NCCLManager { return &m; } - NCCLManager() { - } - ~NCCLManager() {} + NCCLManager(); + + ~NCCLManager(); // for each card only have one communicator - Communicator* GetCommunicator() const; + Communicator* GetCommunicator(const std::vector& gpus) const; private: - struct Communicator { - std::vector comms_; - std::vector streams_; // do not own - std::vector events_; - int root_gpu; - }; - - // the gpu id list available. Note that only support - // whole world communication. - std::vector _gpu_worlds; + // // the gpu id list available. Note that only support + // // whole world communication. + // std::vector _gpu_worlds; // communicator list - std::unordered_map comms_; + std::unordered_map comm_table; }; } // namespace operators diff --git a/paddle/operators/nccl/nccl_gpu_common_test.cc b/paddle/operators/nccl/nccl_gpu_common_test.cc new file mode 100644 index 000000000..9b46ea31b --- /dev/null +++ b/paddle/operators/nccl/nccl_gpu_common_test.cc @@ -0,0 +1,23 @@ +#include "paddle/operators/nccl/nccl_gpu_common.h" + +#include + +#include +#include +#include + +TEST(WaitGroup, wait) { + WaitGroup wg; + auto run_thread = [](int idx) { + wg.Add(1); + std::this_thread::sleep_for(std::chrono::seconds(1)); + wg.Done(); + }; + + std::vector ths; + constexpr const int TNUM = 5; + for (int i = 0; i < TNUM; ++i) { + ths.emplace_back(std::thread(run_thread, i)); + } + wg.Wait(); +} diff --git a/paddle/operators/nccl/nccl_ops.cc b/paddle/operators/nccl/nccl_ops.cc index 4b7bfa723..ccb22f305 100644 --- a/paddle/operators/nccl/nccl_ops.cc +++ b/paddle/operators/nccl/nccl_ops.cc @@ -11,25 +11,20 @@ class NCCLAllReduceOp : public framework::OperatorWithKernel { protected: // allreduce do nothing in infershape void InferShape(const framework::InferShapeContext &ctx) const override { - PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), - " Input(X) of AllReduce op input should not be NULL"); + PADDLE_ENFORCE_NOT_NULL( + ctx.InputVar("X"), + " Input(X) of AllReduce op input should not be NULL"); auto ins = ctx.MultiInput("X"); auto outs = ctx.MultiOutput("Out"); - PADDLE_ENFORCE(ins.size() == outs.size(), "Input(X) and Output(Out) must have same size"); - for(size_t i=0; i < ins.size(); ++i) { + PADDLE_ENFORCE(ins.size() == outs.size(), + "Input(X) and Output(Out) must have same size"); + for (size_t i = 0; i < ins.size(); ++i) { outs[i]->Resize(ins[i]->dims()); } std::string reduction = ctx.Attr("reduction"); - PADDLE_ENFORCE( (reduction == "ncclSum" || reduction == "ncclProd" || - reduction == "ncclMin" || reduction == "ncclMax"), "invalid reduction!"); - } -}; - -template -class NCCLAllreduceOp : public framework::OpKernel { - public: - void Compute(const framework::ExecutionContext &context) const override { - auto *ctx = static_cast(context.device_context()); + PADDLE_ENFORCE((reduction == "ncclSum" || reduction == "ncclProd" || + reduction == "ncclMin" || reduction == "ncclMax"), + "invalid reduction!"); } }; @@ -41,8 +36,9 @@ class NCCLBcastSendOp final : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), - " Input(X) of BcastSend op input should not be NULL"); + PADDLE_ENFORCE_NOT_NULL( + ctx.InputVar("X"), + " Input(X) of BcastSend op input should not be NULL"); } }; @@ -54,18 +50,21 @@ class NCCLBcastRecvOp final : public framework::OperatorWithKernel { protected: void InferShape(const framework::InferShapeContext &ctx) const override { - PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"), - " Input(X) of BcastRecv op input should not be NULL"); + PADDLE_ENFORCE_NOT_NULL( + ctx.OutputVar("Out"), + " Input(X) of BcastRecv op input should not be NULL"); } }; - class NCCLAllReduceOpMaker : public framework::OpProtoAndCheckerMaker { - NCCLAllReduceOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) - : OpProtoAndCheckerMaker(proto, op_checker) { + NCCLAllReduceOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { AddInput("X", "The input of AllReduce op"); AddOutput("Out", "The output of AllReduce op"); - AddAttr("reduction: {'min', 'max', 'prod', 'sum'}."); + AddAttr("reduction", + "{'ncclmin', 'ncclmax', 'ncclprod', 'ncclsum'}."); + AddAttr>("gpus", "gpu id lists"); AddComment(R"DOC( AllReduce the input tensors. )DOC"); @@ -73,8 +72,9 @@ class NCCLAllReduceOpMaker : public framework::OpProtoAndCheckerMaker { }; class NCCLBcastSendOpMaker : public framework::OpProtoAndCheckerMaker { - NCCLAllReduceOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) - : OpProtoAndCheckerMaker(proto, op_checker) { + NCCLAllReduceOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { AddInput("X", "The input of BcastSend op"); AddComment(R"DOC( BcastSend the tensors. @@ -83,8 +83,9 @@ class NCCLBcastSendOpMaker : public framework::OpProtoAndCheckerMaker { }; class NCCLBcastRecvOpMaker : public framework::OpProtoAndCheckerMaker { - NCCLAllReduceOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) - : OpProtoAndCheckerMaker(proto, op_checker) { + NCCLAllReduceOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { AddOutput("Out", "The output of BcastRecv op"); AddComment(R"DOC( BcastRecv the tensors. @@ -92,5 +93,5 @@ class NCCLBcastRecvOpMaker : public framework::OpProtoAndCheckerMaker { } }; -} -} +} // operators +} // paddle diff --git a/paddle/operators/nccl/nccl_ops.h b/paddle/operators/nccl/nccl_ops.h index 3664d2f55..7e348a601 100644 --- a/paddle/operators/nccl/nccl_ops.h +++ b/paddle/operators/nccl/nccl_ops.h @@ -7,29 +7,27 @@ namespace paddle { namespace operators { - -template +template class NCCLTypeWrapper; -template<> +template <> class NCCLTypeWrapper { static const ncclDataType_t type = ncclFloat; }; -template<> +template <> class NCCLTypeWrapper { static const ncclDataType_t type = ncclDouble; }; - - -template +template class NCCLAllReduceKernel : public framework::OpKernel { -public: + public: void Compute(const framework::ExecutionContext& ctx) const override { auto ins = ctx.MultiInput("X"); auto outs = ctx.MultiOutput("Out"); std::string reduction = ctx.Attr("reduction"); + std::vector gpus = ctx.Attr>("gpus"); ncclRedOp_t op_type; if (reduction == "ncclSum") { op_type = ncclSum; @@ -37,24 +35,40 @@ public: op_type = ncclProd; } else if (reduction == "ncclMin") { op_type = ncclMin; - } else (reduction == "ncclMax") { - op_type = ncclMax; - } + } else + (reduction == "ncclMax") { op_type = ncclMax; } + + auto dev_ctx = + static_cast(ctx.device_context()); + + NCCLManager* m = NCCLManager::Get(); + + auto* comm = m->GetCommunicator(gpus); + comm->wg_.Add(1); - auto dev_ctx = ctx.device_context(); + auto* stream = &dev_ctx.stream(); - for( size_t i=0; i < ins.size(); ++i) { - ncclAllReduce(ins[i]->data(), - outs[i]->mutable_data(), - outs[i]->numel() * sizeof(T), - NCCLTypeWrapper::type, - op_type, - comm, - stream); + // device id + int gid = ctx.GetPlace().GetDeviceId(); + int idx = gid % gpus.size(); + comm->streams_[idx] = stream; + + for (size_t i = 0; i < ins.size(); ++i) { + NCCL_CHECK(ncclAllReduce(ins[i]->data(), outs[i]->mutable_data(), + outs[i]->numel() * sizeof(T), + NCCLTypeWrapper::type, op_type, + &comm->comms_[idx], comm->streams_[idx])); + NCCL_CHECK(cudaEventRecord(comm->events_[idx], *comms_->streams_[idx])); + + // wait finish + NCCL_CHECK( + cudaStreamWaitEvent(comm->streams_[idx], comm->events_[idx], 0)); } - } -}; + comm->wg_.Done(); + wg.Wait(); + } +}; } } diff --git a/paddle/platform/place.h b/paddle/platform/place.h index 0efc69323..5370360a7 100644 --- a/paddle/platform/place.h +++ b/paddle/platform/place.h @@ -35,6 +35,7 @@ struct GPUPlace { GPUPlace() : GPUPlace(0) {} explicit GPUPlace(int d) : device(d) {} + inline int GetDeviceId() const { return device; } // needed for variant equality comparison inline bool operator==(const GPUPlace &o) const { return device == o.device; } inline bool operator!=(const GPUPlace &o) const { return !(*this == o); } diff --git a/python/paddle/v2/framework/tests/test_nccl_ops.py b/python/paddle/v2/framework/tests/test_nccl_ops.py index 128a9ab21..9bfa4c74d 100644 --- a/python/paddle/v2/framework/tests/test_nccl_ops.py +++ b/python/paddle/v2/framework/tests/test_nccl_ops.py @@ -3,7 +3,7 @@ import numpy as np import paddle.v2 as paddle from paddle.v2.framework.op import Operator import paddle.v2.framework.core as core -from op_test import OpTest, create_op +from op_test import OpTest, create_op, set_input gpu_list = os.environ["NV_LIST"] @@ -11,7 +11,63 @@ if not core.is_compile_gpu() or not gpu_list: exit(0) +def allreduce(tensors, num_device): + assert (len(tensors) == num_device), "not match of tensor and device" + Out = tensors + for i in range(1, len(tensors)): + Out[0] += Out[i] + + for i in range(1, len(tensors)): + Out[i] = Out[0] + + return Out + + class TestNCCLAllReduce(unittest.TestCase): def __init__(self): self.op_type = "nnclAllReduce" - self.scope = core.Scope() + + self.gpus = [int(g) for g in gpu_list] + + self.scopes = [] + self.ops = [] + self.places = [] + + self.input_data = [] + for i in range(len(self.gpus)): + input_data.append(np.random.random((32, 32))) + self.output_data = allreduce(input_data) + + for i in range(len(self.gpus)): + scope = core.Scope() + place = core.GPUPlace(self.gpus[i]) + inputs = {"X": self.input_data[i]} + outputs = {"Out": self.output_data[i]} + attrs = {"gpus": self.gpus} + + op = create_op(scope, self.op_type, inputs, outputs, attrs) + set_input(scope, op, inputs, place) + + self.scopes.append(scope) + self.ops.append(op) + self.places.append(place) + + def test_output(self): + idx = 0 + for scope, place, op in zip(self.scopes, self.places, self.ops): + ctx = core.DeviceContext.create(place) + op.run(scope, ctx) + + for out_name, out_dup in Operator.get_op_outputs(self.op.type()): + actual = np.array(scope.find_var(out_name).get_tensor()) + expect = self.output_data[idx] + + idx += 1 + self.assertTrue(actual, expect), "has diff" + + +if __name__ == "__main__": + # usage : export NV_LIST=0,1,2,3 python *.py + + os.environ["NV_LIST"] = ["0,1,2,3"] + unittest.main() -- GitLab