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Merge pull request PaddlePaddle#5 from Thunderbrook/gpugraph_deepwalk
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[GpuGraph] deepwalk
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Thunderbrook committed May 24, 2022
2 parents 676a92c + ed569b4 commit 63e501d
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Showing 9 changed files with 542 additions and 75 deletions.
39 changes: 34 additions & 5 deletions paddle/fluid/framework/data_feed.cc
Original file line number Diff line number Diff line change
Expand Up @@ -52,17 +52,46 @@ void GraphDataGenerator::AllocResource(const paddle::platform::Place& place,
device_key_size_ = h_device_keys_->size();
d_device_keys_ =
memory::AllocShared(place_, device_key_size_ * sizeof(int64_t));
for (size_t i = 0; i < h_device_keys_->size(); i++) {
VLOG(2) << "h_device_keys_[" << i << "] = " << (*h_device_keys_)[i];
}
CUDA_CHECK(cudaMemcpyAsync(d_device_keys_->ptr(), h_device_keys_->data(),
device_key_size_ * sizeof(int64_t),
cudaMemcpyHostToDevice, stream_));
d_prefix_sum_ =
memory::AllocShared(place_, (sample_key_size_ + 1) * sizeof(int64_t));
size_t once_max_sample_keynum = walk_degree_ * once_sample_startid_len_;
d_prefix_sum_ = memory::AllocShared(
place_, (once_max_sample_keynum + 1) * sizeof(int64_t));
int64_t* d_prefix_sum_ptr = reinterpret_cast<int64_t*>(d_prefix_sum_->ptr());
cudaMemsetAsync(d_prefix_sum_ptr, 0, (sample_key_size_ + 1) * sizeof(int64_t),
stream_);
cudaMemsetAsync(d_prefix_sum_ptr, 0,
(once_max_sample_keynum + 1) * sizeof(int64_t), stream_);
cursor_ = 0;
jump_rows_ = 0;
device_keys_ = reinterpret_cast<int64_t*>(d_device_keys_->ptr());
;
VLOG(2) << "device_keys_ = " << (uint64_t)device_keys_;
d_walk_ = memory::AllocShared(place_, buf_size_ * sizeof(int64_t));
cudaMemsetAsync(d_walk_->ptr(), 0, buf_size_ * sizeof(int64_t), stream_);
d_sample_keys_ =
memory::AllocShared(place_, once_max_sample_keynum * sizeof(int64_t));

d_sampleidx2rows_.push_back(
memory::AllocShared(place_, once_max_sample_keynum * sizeof(int)));
d_sampleidx2rows_.push_back(
memory::AllocShared(place_, once_max_sample_keynum * sizeof(int)));
cur_sampleidx2row_ = 0;

d_len_per_row_ =
memory::AllocShared(place_, once_max_sample_keynum * sizeof(int));
for (int i = -window_; i < 0; i++) {
window_step_.push_back(i);
}
for (int i = 0; i < window_; i++) {
window_step_.push_back(i + 1);
}
buf_state_.Init(batch_size_, walk_len_, &window_step_);
d_random_row_ = memory::AllocShared(
place_,
(once_sample_startid_len_ * walk_degree_ * repeat_time_) * sizeof(int));
shuffle_seed_ = 0;
cudaStreamSynchronize(stream_);
}

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