[hybrid performance] Optimize tensor parallel plus pipeline parallel …

…send recv size (#34110)

paddle/fluid/operators/collective/partial_allgather_op.cc

@@ -0,0 +1,85 @@
+/* Copyright (c) 2019 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/fluid/operators/collective/partial_allgather_op.h"
+
+namespace paddle {
+namespace operators {
+
+class PartialAllGatherOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+  void InferShape(framework::InferShapeContext *ctx) const override {
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "PartialAllGather");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Input", "Out", "PartialAllGather");
+    int nranks = ctx->Attrs().Get<int>("nranks");
+    int rank = ctx->Attrs().Get<int>("rank");
+
+    PADDLE_ENFORCE_GE(nranks, 2, platform::errors::InvalidArgument(
+                                     "The value of nranks should be >=2."));
+    PADDLE_ENFORCE_EQ(
+        (rank >= 0 && rank < nranks), true,
+        platform::errors::InvalidArgument(
+            "The rank (%d) for partial_allgather op must >=0 and <nranks (%d)",
+            rank, nranks));
+
+    framework::DDim dim = ctx->GetInputDim("X");
+    ctx->SetOutputDim("Out", dim);
+  }
+};
+
+class PartialAllGatherOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() {
+    AddInput("X", "(Tensor) tensor to be partial allgather");
+    AddOutput("Out", "(Tensor) the allgather result");
+    AddAttr<int>("ring_id", "(int default 0) communication ring id.")
+        .SetDefault(0);
+#if defined(PADDLE_WITH_ASCEND_CL)
+    AddAttr<std::string>("tag", "(string default tag) tag for all gather.")
+        .SetDefault("tag");
+#endif
+    AddAttr<bool>(
+        "use_calc_stream",
+        "(bool default false) eject CUDA operations to calculation stream.")
+        .SetDefault(false);
+    AddAttr<int>("nranks",
+                 "Total trainer count of the distributed training job");
+    AddAttr<int>("rank", "Rand of the distributed training job");
+    AddComment(R"DOC(
+PartialAllGather Operator.
+Divide the Input into nranks copies and only use the rank part.
+Each rank receives the aggregation of data from all ranks in the order of the ranks.
+
+
+reference: https://docs.nvidia.com/deeplearning/sdk/nccl-developer-guide/docs/usage/operations.html#allgather
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_WITHOUT_GRADIENT(partial_allgather, ops::PartialAllGatherOp,
+                             ops::PartialAllGatherOpMaker);
+
+REGISTER_OP_CPU_KERNEL(partial_allgather,
+                       ops::PartialAllGatherOpCPUKernel<float>,
+                       ops::PartialAllGatherOpCPUKernel<double>,
+                       ops::PartialAllGatherOpCPUKernel<int>,
+                       ops::PartialAllGatherOpCPUKernel<int64_t>,
+                       ops::PartialAllGatherOpCPUKernel<plat::float16>);

paddle/fluid/operators/collective/partial_allgather_op.cu.cc

@@ -0,0 +1,91 @@
+/* Copyright (c) 2019 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/fluid/operators/collective/partial_allgather_op.h"
+
+#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
+#include "paddle/fluid/platform/collective_helper.h"
+#include "paddle/fluid/platform/nccl_helper.h"
+#endif
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class PartialAllGatherOpCUDAKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
+    auto in = ctx.Input<framework::Tensor>("X");
+    auto out = ctx.Output<framework::Tensor>("Out");
+    int64_t numel = in->numel();
+    ncclDataType_t dtype = platform::ToNCCLDataType(in->type());
+
+    int nranks = ctx.Attr<int>("nranks");
+    int rank = ctx.Attr<int>("rank");
+    int rid = ctx.Attr<int>("ring_id");
+    auto place = ctx.GetPlace();
+    auto comm = platform::NCCLCommContext::Instance().Get(rid, place);
+
+    PADDLE_ENFORCE_EQ(
+        nranks, comm->nranks(),
+        platform::errors::InvalidArgument("nranks: %s should equal to %s",
+                                          nranks, comm->nranks()));
+    PADDLE_ENFORCE_EQ(rank, comm->rank(),
+                      platform::errors::InvalidArgument(
+                          "rank: %s should equal to %s", rank, comm->rank()));
+    PADDLE_ENFORCE_EQ(
+        (numel % nranks), 0,
+        platform::errors::InvalidArgument(
+            "The input numel (%d) must be divisible by nranks(%d)", numel,
+            nranks));
+
+    framework::DDim dims = in->dims();
+    out->mutable_data<T>(dims, place);
+
+    int64_t send_numel = numel / nranks;
+    int offset = send_numel * rank;
+    const T* send_buff = in->data<T>() + offset;
+    T* recv_buff = out->data<T>();
+
+    gpuStream_t stream = nullptr;
+    if (ctx.Attr<bool>("use_calc_stream")) {
+      auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
+      stream = static_cast<platform::CUDADeviceContext*>(dev_ctx)->stream();
+    } else {
+      stream = comm->stream();
+    }
+
+    PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllGather(
+        send_buff, recv_buff, send_numel, static_cast<ncclDataType_t>(dtype),
+        comm->comm(), stream));
+#else
+    PADDLE_THROW(platform::errors::PreconditionNotMet(
+        "PaddlePaddle should compile with GPU."));
+#endif
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_CUDA_KERNEL(partial_allgather,
+                        ops::PartialAllGatherOpCUDAKernel<float>,
+                        ops::PartialAllGatherOpCUDAKernel<double>,
+                        ops::PartialAllGatherOpCUDAKernel<int>,
+                        ops::PartialAllGatherOpCUDAKernel<int64_t>,
+                        ops::PartialAllGatherOpCUDAKernel<plat::float16>);

paddle/fluid/operators/collective/partial_allgather_op.h

@@ -0,0 +1,39 @@
+/* Copyright (c) 2021 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. */
+
+#pragma once
+
+#include <algorithm>
+#include <utility>
+#include <vector>
+
+#include "paddle/fluid/framework/data_type.h"
+#include "paddle/fluid/framework/ddim.h"
+#include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+class PartialAllGatherOpCPUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    PADDLE_THROW(platform::errors::Unavailable(
+        "Do not support partial_allgather for cpu kernel now."));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

paddle/fluid/operators/collective/partial_recv_op.cc

@@ -0,0 +1,131 @@
+/* Copyright (c) 2020 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/fluid/operators/collective/partial_recv_op.h"
+#include <string>
+
+namespace paddle {
+namespace operators {
+
+class PartialRecvOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "PartialRecv");
+    int peer = ctx->Attrs().Get<int>("peer");
+    int ring_id = ctx->Attrs().Get<int>("ring_id");
+    int num = ctx->Attrs().Get<int>("num");
+    int id = ctx->Attrs().Get<int>("id");
+    auto out_shape = ctx->Attrs().Get<std::vector<int>>("out_shape");
+
+    PADDLE_ENFORCE_GE(
+        peer, 0,
+        platform::errors::InvalidArgument(
+            "The peer (%d) for partial_recv op must be non-negative.", peer));
+    PADDLE_ENFORCE_GE(
+        ring_id, 0,
+        platform::errors::InvalidArgument(
+            "The ring_id (%d) for partial_recv op must be non-negative.",
+            ring_id));
+    PADDLE_ENFORCE_GE(num, 1,
+                      platform::errors::InvalidArgument(
+                          "The num (%d) for partial_send op must >=1", num));
+    PADDLE_ENFORCE_EQ(
+        (id >= 0 && id < num), true,
+        platform::errors::InvalidArgument(
+            "The id (%d) for partial_send op must >=0 and <num (%d)", id, num));
+    PADDLE_ENFORCE_GE(out_shape.size(), 1,
+                      platform::errors::InvalidArgument(
+                          "The size of the output shape must be greater than 0 "
+                          "but the value given is %d.",
+                          out_shape.size()));
+
+    for (size_t i = 0; i < out_shape.size(); ++i) {
+      PADDLE_ENFORCE_GE(out_shape[i], 1,
+                        platform::errors::InvalidArgument(
+                            "The shape attribute for partial_recv must be set "
+                            "explicitly, but the %dth element is %d which "
+                            "is less than 1.",
+                            i, out_shape[i]));
+    }
+    auto out_dims = framework::make_ddim(out_shape);
+    int numel = framework::product(out_dims);
+    PADDLE_ENFORCE_EQ(
+        (numel % num), 0,
+        platform::errors::InvalidArgument(
+            "The output numel (%d) must be divisible by num(%d)", numel, num));
+
+    ctx->SetOutputDim("Out", framework::make_ddim(out_shape));
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override {
+    int dtype = ctx.Attr<int>("dtype");
+    framework::proto::VarType::Type type =
+        framework::proto::VarType::Type(dtype);
+    return framework::OpKernelType(type, ctx.GetPlace());
+  }
+};
+
+class PartialRecvOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() {
+    AddOutput("Out", "(Tensor) tensor to receive.");
+    AddAttr<int>("ring_id", "(int default 0) nccl communication ring id.")
+        .SetDefault(0);
+    AddAttr<int>("peer", "(int default 0) rank id for sender.").SetDefault(0);
+    AddAttr<int>("dtype", "(int default 5('float32')) data type of tensor.")
+        .SetDefault(5);
+#if defined(PADDLE_WITH_ASCEND_CL)
+    AddAttr<std::string>("tag", "(string default tag) tag for broadcasting.")
+        .SetDefault("tag");
+    AddAttr<int>("srTag", "(string default tag) tag for broadcasting.")
+        .SetDefault(0);
+#endif
+    AddAttr<std::vector<int>>("out_shape", "shape of the output tensor.")
+        .SetDefault(std::vector<int>());
+    AddAttr<bool>(
+        "use_calc_stream",
+        "(bool default false) eject CUDA operations to calculation stream.")
+        .SetDefault(false);
+    AddAttr<int>("num", "(int default 1) The number of Output to be cut.")
+        .SetDefault(1);
+    AddAttr<int>("id",
+                 "(int default 0) ID of the part to be recv after Output cut.")
+        .SetDefault(0);
+    AddComment(R"DOC(
+Recv Operator.
+Divide the Output into num copies and only recv the id part.
+
+Reference: https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/p2p.html#sendrecv
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+namespace plat = paddle::platform;
+
+REGISTER_OP_WITHOUT_GRADIENT(partial_recv, ops::PartialRecvOp,
+                             ops::PartialRecvOpMaker);
+
+REGISTER_OP_CPU_KERNEL(partial_recv, ops::PartialRecvOpCPUKernel<float>,
+                       ops::PartialRecvOpCPUKernel<double>,
+                       ops::PartialRecvOpCPUKernel<int>,
+                       ops::PartialRecvOpCPUKernel<int64_t>,
+                       ops::PartialRecvOpCPUKernel<plat::float16>);