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paddlepaddle--paddle/paddle/phi/kernels/custom/global_gather_kernel.cc
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2026-07-13 12:40:42 +08:00

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// Copyright (c) 2025 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/phi/api/backward/backward_api_base.h"
#include "paddle/phi/api/include/api.h"
#include "paddle/phi/backends/all_context.h"
#include "paddle/phi/backends/context_pool.h"
#include "paddle/phi/backends/device_manager.h"
#include "paddle/phi/core/distributed/collective/process_group.h"
#include "paddle/phi/core/distributed/comm_context_manager.h"
#include "paddle/phi/core/distributed/xccl_comm_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_utils.h"
#ifdef PADDLE_WITH_CUSTOM_DEVICE
namespace phi {
template <typename T, typename Context>
void GlobalGatherKernel(const Context& dev_ctx,
const DenseTensor& x_in,
const DenseTensor& local_count_in,
const DenseTensor& global_count_in,
DenseTensor* out) {
auto x = &x_in;
auto local_count = &local_count_in;
auto global_count = &global_count_in;
auto place = dev_ctx.GetPlace();
PADDLE_ENFORCE_EQ(
local_count->dtype(),
phi::DataType::INT64,
common::errors::InvalidArgument("Please use int64 type in local_count."));
PADDLE_ENFORCE_EQ(global_count->dtype(),
phi::DataType::INT64,
common::errors::InvalidArgument(
"Please use int64 type in global_count."));
const int64_t* cpu_local_count_data;
const int64_t* cpu_global_count_data;
auto local_count_len = 0;
DenseTensor cpu_local_count;
if (local_count->place().GetType() == phi::AllocationType::CPU) {
cpu_local_count_data = local_count->data<int64_t>();
local_count_len = local_count->numel();
} else {
phi::Copy(dev_ctx, *local_count, phi::CPUPlace(), true, &cpu_local_count);
cpu_local_count_data = cpu_local_count.data<int64_t>();
local_count_len = cpu_local_count.numel();
}
DenseTensor cpu_global_count;
if (global_count->place().GetType() == phi::AllocationType::CPU) {
cpu_global_count_data = global_count->data<int64_t>();
} else {
phi::Copy(dev_ctx, *global_count, phi::CPUPlace(), true, &cpu_global_count);
cpu_global_count_data = cpu_global_count.data<int64_t>();
}
auto comm = reinterpret_cast<phi::distributed::XCCLCommContext*>(
dev_ctx.GetCommContext());
std::shared_ptr<phi::stream::Stream> stream;
stream = comm->GetStream();
int nranks = comm->GetSize();
int rank = comm->GetRank();
auto in_feat = x->dims()[1];
auto n_expert = local_count->dims()[0] / nranks;
auto fwd_count = 0;
for (auto i = 0; i < local_count_len; ++i) {
fwd_count += cpu_local_count_data[i];
}
DDim out_dims = make_ddim({fwd_count, in_feat});
int64_t* expert_ptr = new int64_t[n_expert * nranks];
expert_ptr[0] = 0;
auto tot_experts = n_expert * nranks;
for (auto i = 1; i < tot_experts; ++i) {
expert_ptr[i] = expert_ptr[i - 1] + cpu_local_count_data[i - 1];
}
auto send_ptr = 0;
auto send_buf = x->data<T>();
out->Resize(out_dims);
auto recv_buf = dev_ctx.template Alloc<T>(out);
for (auto i = 0; i < n_expert; ++i) {
for (auto j = 0; j < rank + 1; ++j) {
int idx = i + j * n_expert;
if (cpu_local_count_data[idx]) {
phi::DeviceManager::CCLRecv(place.GetDeviceType(),
recv_buf + expert_ptr[idx] * in_feat,
cpu_local_count_data[idx] * in_feat,
x->dtype(),
j,
comm->GetXcclComm(),
stream->raw_stream());
}
}
for (auto j = 0; j < nranks; ++j) {
int idx = i + j * n_expert;
if (cpu_global_count_data[idx]) {
if (j != rank) {
phi::DeviceManager::CCLSend(
place.GetDeviceType(),
const_cast<void*>(
reinterpret_cast<const void*>(send_buf + send_ptr * in_feat)),
cpu_global_count_data[idx] * in_feat,
x->dtype(),
j,
comm->GetXcclComm(),
stream->raw_stream());
} else {
phi::DeviceManager::GetDeviceWithPlace(place)->MemoryCopyD2D(
reinterpret_cast<void*>(recv_buf + expert_ptr[idx] * in_feat),
reinterpret_cast<const void*>(send_buf + send_ptr * in_feat),
(cpu_global_count_data[idx] * in_feat) * phi::SizeOf(x->dtype()),
stream.get());
}
send_ptr += cpu_global_count_data[idx];
}
}
for (auto j = rank + 1; j < nranks; ++j) {
int idx = i + j * n_expert;
if (cpu_local_count_data[idx]) {
phi::DeviceManager::CCLRecv(place.GetDeviceType(),
recv_buf + expert_ptr[idx] * in_feat,
cpu_local_count_data[idx] * in_feat,
x->dtype(),
j,
comm->GetXcclComm(),
stream->raw_stream());
}
}
}
phi::DeviceManager::SynchronizeDevice(dev_ctx.GetPlace());
}
} // namespace phi
PD_REGISTER_KERNEL(global_gather,
Custom,
ALL_LAYOUT,
phi::GlobalGatherKernel,
float,
double,
int32_t,
int64_t,
phi::float16) {}
#endif