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Purge device_helpers.cuh (#5534)

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* Simplifications with caching_device_vector

* Purge device helpers
This commit is contained in:
Rory Mitchell
2020-04-15 21:51:56 +12:00
committed by GitHub
parent a2f54963b6
commit ca4e05660e
9 changed files with 182 additions and 733 deletions
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24
src/linear/updater_gpu_coordinate.cu
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@@ -86,14 +86,13 @@ class GPUCoordinateUpdater : public LinearUpdater { // NOLINT
std::make_pair(column_begin - col.cbegin(), column_end - col.cbegin()));
row_ptr_.push_back(row_ptr_.back() + (column_end - column_begin));
}
ba_.Allocate(learner_param_->gpu_id, &data_, row_ptr_.back(), &gpair_,
num_row_ * model_param.num_output_group);
data_.resize(row_ptr_.back());
gpair_.resize(num_row_ * model_param.num_output_group);
for (size_t fidx = 0; fidx < batch.Size(); fidx++) {
auto col = batch[fidx];
auto seg = column_segments[fidx];
dh::safe_cuda(cudaMemcpy(
data_.subspan(row_ptr_[fidx]).data(),
data_.data().get() + row_ptr_[fidx],
col.data() + seg.first,
sizeof(Entry) * (seg.second - seg.first), cudaMemcpyHostToDevice));
}
@@ -192,7 +191,7 @@ class GPUCoordinateUpdater : public LinearUpdater { // NOLINT
// This needs to be public because of the __device__ lambda.
void UpdateBiasResidual(float dbias, int group_idx, int num_groups) {
if (dbias == 0.0f) return;
auto d_gpair = gpair_;
auto d_gpair = dh::ToSpan(gpair_);
dh::LaunchN(learner_param_->gpu_id, num_row_, [=] __device__(size_t idx) {
auto &g = d_gpair[idx * num_groups + group_idx];
g += GradientPair(g.GetHess() * dbias, 0);
@@ -202,9 +201,9 @@ class GPUCoordinateUpdater : public LinearUpdater { // NOLINT
// This needs to be public because of the __device__ lambda.
GradientPair GetGradient(int group_idx, int num_group, int fidx) {
dh::safe_cuda(cudaSetDevice(learner_param_->gpu_id));
common::Span<xgboost::Entry> d_col = data_.subspan(row_ptr_[fidx]);
common::Span<xgboost::Entry> d_col = dh::ToSpan(data_).subspan(row_ptr_[fidx]);
size_t col_size = row_ptr_[fidx + 1] - row_ptr_[fidx];
common::Span<GradientPair> d_gpair = gpair_;
common::Span<GradientPair> d_gpair = dh::ToSpan(gpair_);
auto counting = thrust::make_counting_iterator(0ull);
auto f = [=] __device__(size_t idx) {
auto entry = d_col[idx];
@@ -219,8 +218,8 @@ class GPUCoordinateUpdater : public LinearUpdater { // NOLINT
// This needs to be public because of the __device__ lambda.
void UpdateResidual(float dw, int group_idx, int num_groups, int fidx) {
common::Span<GradientPair> d_gpair = gpair_;
common::Span<Entry> d_col = data_.subspan(row_ptr_[fidx]);
common::Span<GradientPair> d_gpair = dh::ToSpan(gpair_);
common::Span<Entry> d_col = dh::ToSpan(data_).subspan(row_ptr_[fidx]);
size_t col_size = row_ptr_[fidx + 1] - row_ptr_[fidx];
dh::LaunchN(learner_param_->gpu_id, col_size, [=] __device__(size_t idx) {
auto entry = d_col[idx];
@@ -236,7 +235,7 @@ class GPUCoordinateUpdater : public LinearUpdater { // NOLINT
void UpdateGpair(const std::vector<GradientPair> &host_gpair) {
dh::safe_cuda(cudaMemcpyAsync(
gpair_.data(),
gpair_.data().get(),
host_gpair.data(),
gpair_.size() * sizeof(GradientPair), cudaMemcpyHostToDevice));
}
@@ -247,10 +246,9 @@ class GPUCoordinateUpdater : public LinearUpdater { // NOLINT
std::unique_ptr<FeatureSelector> selector_;
common::Monitor monitor_;
dh::BulkAllocator ba_;
std::vector<size_t> row_ptr_;
common::Span<xgboost::Entry> data_;
common::Span<GradientPair> gpair_;
dh::device_vector<xgboost::Entry> data_;
dh::caching_device_vector<GradientPair> gpair_;
dh::CubMemory temp_;
size_t num_row_;
};