wehub-resource-sync
132 lines
4.5 KiB
C++
132 lines
4.5 KiB
C++
// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include "paddle/phi/backends/all_context.h"
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#include "paddle/phi/backends/device_manager.h"
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#include "paddle/phi/core/distributed/collective/process_group.h"
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#include "paddle/phi/core/distributed/comm_context_manager.h"
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#include "paddle/phi/core/distributed/xccl_comm_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/core/tensor_utils.h"
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#ifdef PADDLE_WITH_CUSTOM_DEVICE
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namespace phi {
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template <typename T, typename Context, phi::ccl::CCLReduceOp red_type>
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void CAllReduceKernel(const Context& dev_ctx,
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const DenseTensor& x_in,
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int ring_id,
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bool use_calc_stream,
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bool use_model_parallel,
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DenseTensor* out) {
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auto in = &x_in;
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int rid = ring_id;
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auto place = dev_ctx.GetPlace();
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auto dtype = in->dtype();
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int64_t numel = in->numel();
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const void* sendbuff = in->data<T>();
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out->Resize(in->dims());
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void* recvbuff = dev_ctx.template Alloc<T>(out);
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auto map = phi::distributed::ProcessGroupMapFromGid::getInstance();
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if (map->has(rid)) {
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// Use ProcessGroup
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phi::distributed::ProcessGroup* pg = map->get(rid);
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std::vector<DenseTensor> in_tensor;
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std::vector<DenseTensor> out_tensor;
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in_tensor.push_back(*in);
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out_tensor.push_back(*out);
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phi::distributed::AllreduceOptions opts;
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switch (red_type) {
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case phi::ccl::CCLReduceOp::SUM:
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opts.reduce_op = phi::distributed::ReduceOp::SUM;
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break;
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case phi::ccl::CCLReduceOp::MAX:
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opts.reduce_op = phi::distributed::ReduceOp::MAX;
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break;
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case phi::ccl::CCLReduceOp::MIN:
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opts.reduce_op = phi::distributed::ReduceOp::MIN;
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break;
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case phi::ccl::CCLReduceOp::PRODUCT:
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opts.reduce_op = phi::distributed::ReduceOp::PRODUCT;
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break;
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default:
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PADDLE_THROW(common::errors::InvalidArgument("Invalid reduce type: %d",
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red_type));
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}
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auto task =
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pg->AllReduce(in_tensor, out_tensor, opts, use_calc_stream, false);
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task->Wait();
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return;
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}
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auto comm = reinterpret_cast<phi::distributed::XCCLCommContext*>(
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phi::distributed::CommContextManager::GetInstance().Get(
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std::to_string(rid)));
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std::shared_ptr<phi::stream::Stream> stream;
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if (use_calc_stream) {
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stream = dev_ctx.GetStream();
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} else {
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stream = comm->GetStream();
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}
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phi::DeviceManager::CCLAllReduce(place.GetDeviceType(),
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const_cast<void*>(sendbuff),
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recvbuff,
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numel,
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dtype,
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red_type,
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comm->GetXcclComm(),
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stream->raw_stream());
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}
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template <typename T, typename Context, phi::ccl::CCLReduceOp red_type>
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void AllReduceKernel(const Context& dev_ctx,
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const DenseTensor& x_in,
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DenseTensor* out) {
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auto in = &x_in;
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auto place = dev_ctx.GetPlace();
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auto dtype = in->dtype();
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int64_t numel = in->numel();
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const void* sendbuff = in->data<T>();
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out->Resize(in->dims());
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void* recvbuff = dev_ctx.template Alloc<T>(out);
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auto comm = reinterpret_cast<phi::distributed::XCCLCommContext*>(
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dev_ctx.GetCommContext());
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std::shared_ptr<phi::stream::Stream> stream;
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stream = comm->GetStream();
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phi::DeviceManager::CCLAllReduce(place.GetDeviceType(),
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const_cast<void*>(sendbuff),
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recvbuff,
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numel,
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dtype,
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red_type,
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comm->GetXcclComm(),
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stream->raw_stream());
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}
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} // namespace phi
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#endif
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