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Retire DVec class in favour of c++20 style span for device memory. (#4293)

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This commit is contained in:
Rory Mitchell
2019-03-28 13:59:58 +13:00
committed by GitHub
parent c85181dd8a
commit 3f312e30db
7 changed files with 288 additions and 369 deletions
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36
src/linear/updater_gpu_coordinate.cu
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@@ -19,18 +19,18 @@ namespace linear {
DMLC_REGISTRY_FILE_TAG(updater_gpu_coordinate);
void RescaleIndices(size_t ridx_begin, dh::DVec<xgboost::Entry> *data) {
auto d_data = data->GetSpan();
dh::LaunchN(data->DeviceIdx(), data->Size(),
[=] __device__(size_t idx) { d_data[idx].index -= ridx_begin; });
void RescaleIndices(int device_idx, size_t ridx_begin,
common::Span<xgboost::Entry> data) {
dh::LaunchN(device_idx, data.size(),
[=] __device__(size_t idx) { data[idx].index -= ridx_begin; });
}
class DeviceShard {
int device_id_;
dh::BulkAllocator<dh::MemoryType::kDevice> ba_;
dh::BulkAllocator ba_;
std::vector<size_t> row_ptr_;
dh::DVec<xgboost::Entry> data_;
dh::DVec<GradientPair> gpair_;
common::Span<xgboost::Entry> data_;
common::Span<GradientPair> gpair_;
dh::CubMemory temp_;
size_t ridx_begin_;
size_t ridx_end_;
@@ -73,12 +73,12 @@ class DeviceShard {
auto col = batch[fidx];
auto seg = column_segments[fidx];
dh::safe_cuda(cudaMemcpy(
data_.GetSpan().subspan(row_ptr_[fidx]).data(),
data_.subspan(row_ptr_[fidx]).data(),
col.data() + seg.first,
sizeof(Entry) * (seg.second - seg.first), cudaMemcpyHostToDevice));
}
// Rescale indices with respect to current shard
RescaleIndices(ridx_begin_, &data_);
RescaleIndices(device_id_, ridx_begin_, data_);
}
bool IsEmpty() {
@@ -87,8 +87,10 @@ class DeviceShard {
void UpdateGpair(const std::vector<GradientPair> &host_gpair,
const gbm::GBLinearModelParam &model_param) {
gpair_.copy(host_gpair.begin() + ridx_begin_ * model_param.num_output_group,
host_gpair.begin() + ridx_end_ * model_param.num_output_group);
dh::safe_cuda(cudaMemcpyAsync(
gpair_.data(),
host_gpair.data() + ridx_begin_ * model_param.num_output_group,
gpair_.size() * sizeof(GradientPair), cudaMemcpyHostToDevice));
}
GradientPair GetBiasGradient(int group_idx, int num_group) {
@@ -99,14 +101,14 @@ class DeviceShard {
}; // NOLINT
thrust::transform_iterator<decltype(f), decltype(counting), size_t> skip(
counting, f);
auto perm = thrust::make_permutation_iterator(gpair_.tbegin(), skip);
auto perm = thrust::make_permutation_iterator(gpair_.data(), skip);
return dh::SumReduction(temp_, perm, ridx_end_ - ridx_begin_);
}
void UpdateBiasResidual(float dbias, int group_idx, int num_groups) {
if (dbias == 0.0f) return;
auto d_gpair = gpair_.GetSpan();
auto d_gpair = gpair_;
dh::LaunchN(device_id_, ridx_end_ - ridx_begin_, [=] __device__(size_t idx) {
auto &g = d_gpair[idx * num_groups + group_idx];
g += GradientPair(g.GetHess() * dbias, 0);
@@ -115,9 +117,9 @@ class DeviceShard {
GradientPair GetGradient(int group_idx, int num_group, int fidx) {
dh::safe_cuda(cudaSetDevice(device_id_));
common::Span<xgboost::Entry> d_col = data_.GetSpan().subspan(row_ptr_[fidx]);
common::Span<xgboost::Entry> d_col = data_.subspan(row_ptr_[fidx]);
size_t col_size = row_ptr_[fidx + 1] - row_ptr_[fidx];
common::Span<GradientPair> d_gpair = gpair_.GetSpan();
common::Span<GradientPair> d_gpair = gpair_;
auto counting = thrust::make_counting_iterator(0ull);
auto f = [=] __device__(size_t idx) {
auto entry = d_col[idx];
@@ -131,8 +133,8 @@ class DeviceShard {
}
void UpdateResidual(float dw, int group_idx, int num_groups, int fidx) {
common::Span<GradientPair> d_gpair = gpair_.GetSpan();
common::Span<Entry> d_col = data_.GetSpan().subspan(row_ptr_[fidx]);
common::Span<GradientPair> d_gpair = gpair_;
common::Span<Entry> d_col = data_.subspan(row_ptr_[fidx]);
size_t col_size = row_ptr_[fidx + 1] - row_ptr_[fidx];
dh::LaunchN(device_id_, col_size, [=] __device__(size_t idx) {
auto entry = d_col[idx];