ps_gpu_wrapper.cu 8.8 KB
Newer Older
T
Thunderbrook 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
/* 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. */

#ifdef PADDLE_WITH_PSLIB
#include <algorithm>
#include <ctime>
#include <memory>
#include <numeric>
Y
yaoxuefeng 已提交
20
#include "paddle/fluid/framework/fleet/heter_ps/optimizer_conf.h"
T
Thunderbrook 已提交
21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180
#include "paddle/fluid/framework/fleet/ps_gpu_wrapper.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/platform/gpu_info.h"

namespace paddle {
namespace framework {

__global__ void PullCopy(float** dest, const FeatureValue* src,
                         const int64_t* len, int hidden, int slot_num,
                         int total_len, uint64_t** keys) {
  CUDA_KERNEL_LOOP(i, total_len) {
    int low = 0;
    int high = slot_num - 1;
    while (low < high) {
      int mid = (low + high) / 2;
      if (i < len[mid])
        high = mid;
      else
        low = mid + 1;
    }
    int x = low;
    int y = i - (x ? len[x - 1] : 0);
    if (*(keys[x] + y) == 0) {
      *(dest[x] + y * hidden) = 0;
      *(dest[x] + y * hidden + 1) = 0;
      *(dest[x] + y * hidden + 2) = 0;
    } else {
      *(dest[x] + y * hidden) = (src + i)->show;
      *(dest[x] + y * hidden + 1) = (src + i)->clk;
      *(dest[x] + y * hidden + 2) = (src + i)->lr;
    }
    if ((src + i)->mf_size == 0 || *(keys[x] + y) == 0) {
      for (int j = 0; j < 8; j++) {
        *(dest[x] + y * hidden + 3 + j) = 0;
      }
    } else {
      for (int j = 0; j < 8; j++) {
        *(dest[x] + y * hidden + 3 + j) = (src + i)->mf[1 + j];
      }
    }
  }
}

__global__ void CopyKeysKernel(uint64_t** src_keys, uint64_t* dest_total_keys,
                               const int64_t* len, int slot_num,
                               int total_len) {
  CUDA_KERNEL_LOOP(i, total_len) {
    int low = 0;
    int high = slot_num - 1;
    while (low < high) {
      int mid = (low + high) / 2;
      if (i < len[mid])
        high = mid;
      else
        low = mid + 1;
    }
    int x = low;
    int y = i - (x ? len[x - 1] : 0);
    dest_total_keys[i] = src_keys[x][y];
  }
}

__global__ void PushCopy(FeaturePushValue* dest, float** src, int64_t* len,
                         int hidden, int slot_num, int total_len, int bs,
                         int* slot_vector) {
  CUDA_KERNEL_LOOP(i, total_len) {
    int low = 0;
    int high = slot_num - 1;
    while (low < high) {
      int mid = (low + high) / 2;
      if (i < len[mid])
        high = mid;
      else
        low = mid + 1;
    }
    int x = low;
    int y = i - (x ? len[low - 1] : 0);
    (dest + i)->slot = slot_vector[x];
    (dest + i)->show = *(src[x] + y * hidden);
    (dest + i)->clk = *(src[x] + y * hidden + 1);
    (dest + i)->lr_g = *(src[x] + y * hidden + 2) * -1. * bs;
    for (int j = 0; j < 8; j++) {
      (dest + i)->mf_g[j] = *(src[x] + y * hidden + 3 + j) * -1. * bs;
    }
  }
}

void PSGPUWrapper::CopyForPull(const paddle::platform::Place& place,
                               uint64_t** gpu_keys,
                               const std::vector<float*>& values,
                               const FeatureValue* total_values_gpu,
                               const int64_t* gpu_len, const int slot_num,
                               const int hidden_size,
                               const int64_t total_length) {
  auto stream = dynamic_cast<platform::CUDADeviceContext*>(
                    platform::DeviceContextPool::Instance().Get(
                        BOOST_GET_CONST(platform::CUDAPlace, place)))
                    ->stream();
  auto buf_value = memory::AllocShared(place, values.size() * sizeof(float*));
  float** gpu_values = reinterpret_cast<float**>(buf_value->ptr());
  cudaMemcpy(gpu_values, values.data(), values.size() * sizeof(float*),
             cudaMemcpyHostToDevice);

  PullCopy<<<(total_length + 512 - 1) / 512, 512, 0, stream>>>(
      gpu_values, total_values_gpu, gpu_len, hidden_size, slot_num,
      total_length, gpu_keys);
  cudaStreamSynchronize(stream);
}

void PSGPUWrapper::CopyKeys(const paddle::platform::Place& place,
                            uint64_t** origin_keys, uint64_t* total_keys,
                            const int64_t* gpu_len, int slot_num,
                            int total_len) {
  auto stream = dynamic_cast<platform::CUDADeviceContext*>(
                    platform::DeviceContextPool::Instance().Get(
                        BOOST_GET_CONST(platform::CUDAPlace, place)))
                    ->stream();
  CopyKeysKernel<<<(total_len + 512 - 1) / 512, 512, 0, stream>>>(
      origin_keys, total_keys, gpu_len, slot_num, total_len);
  cudaStreamSynchronize(stream);
}

void PSGPUWrapper::CopyForPush(const paddle::platform::Place& place,
                               const std::vector<const float*>& grad_values,
                               FeaturePushValue* total_grad_values_gpu,
                               const std::vector<int64_t>& slot_lengths,
                               const int hidden_size,
                               const int64_t total_length,
                               const int batch_size) {
  auto stream = dynamic_cast<platform::CUDADeviceContext*>(
                    platform::DeviceContextPool::Instance().Get(
                        BOOST_GET_CONST(platform::CUDAPlace, place)))
                    ->stream();
  auto slot_lengths_lod = slot_lengths;
  for (int i = 1; i < slot_lengths_lod.size(); i++) {
    slot_lengths_lod[i] += slot_lengths_lod[i - 1];
  }
  auto buf_grad_value =
      memory::AllocShared(place, grad_values.size() * sizeof(float*));
  auto buf_length =
      memory::AllocShared(place, slot_lengths.size() * sizeof(int64_t));
  auto buf_slot_vector =
      memory::AllocShared(place, slot_lengths_lod.size() * sizeof(int));

  float** gpu_values = reinterpret_cast<float**>(buf_grad_value->ptr());
  int64_t* gpu_len = reinterpret_cast<int64_t*>(buf_length->ptr());
  int* d_slot_vector = reinterpret_cast<int*>(buf_slot_vector->ptr());

  cudaMemcpy(gpu_values, grad_values.data(),
             grad_values.size() * sizeof(float*), cudaMemcpyHostToDevice);
  cudaMemcpy(gpu_len, slot_lengths_lod.data(),
             slot_lengths.size() * sizeof(int64_t), cudaMemcpyHostToDevice);
  cudaMemcpy(d_slot_vector, slot_vector_.data(),
             slot_lengths_lod.size() * sizeof(int), cudaMemcpyHostToDevice);

  PushCopy<<<(total_length + 512 - 1) / 512, 512, 0, stream>>>(
      total_grad_values_gpu, gpu_values, gpu_len, hidden_size,
      slot_lengths.size(), total_length, batch_size, d_slot_vector);
  cudaStreamSynchronize(stream);
}
Y
yaoxuefeng 已提交
181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216

void PSGPUWrapper::SetSparseSGD(float nonclk_coeff, float clk_coeff,
                                float min_bound, float max_bound,
                                float learning_rate, float initial_g2sum,
                                float initial_range) {
  cudaMemcpyToSymbol(optimizer_config::nonclk_coeff, &nonclk_coeff,
                     sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::clk_coeff, &clk_coeff, sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::min_bound, &min_bound, sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::max_bound, &max_bound, sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::learning_rate, &learning_rate,
                     sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::initial_g2sum, &initial_g2sum,
                     sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::initial_range, &initial_range,
                     sizeof(float));
}

void PSGPUWrapper::SetEmbedxSGD(float mf_create_thresholds,
                                float mf_learning_rate, float mf_initial_g2sum,
                                float mf_initial_range, float mf_min_bound,
                                float mf_max_bound) {
  cudaMemcpyToSymbol(optimizer_config::mf_create_thresholds,
                     &mf_create_thresholds, sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::mf_learning_rate, &mf_learning_rate,
                     sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::mf_initial_g2sum, &mf_initial_g2sum,
                     sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::mf_initial_range, &mf_initial_range,
                     sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::mf_min_bound, &mf_min_bound,
                     sizeof(float));
  cudaMemcpyToSymbol(optimizer_config::mf_max_bound, &mf_max_bound,
                     sizeof(float));
}

T
Thunderbrook 已提交
217 218 219
}  // end namespace framework
}  // end namespace paddle
#endif