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further cleanup of single process multi-GPU code (#4810)

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* use subspan in gpu predictor instead of copying
* Revise `HostDeviceVector`
This commit is contained in:
Rong Ou
2019-08-30 02:27:23 -07:00
committed by Jiaming Yuan
parent 0184eb5d02
commit 733ed24dd9
12 changed files with 289 additions and 593 deletions
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40
src/predictor/gpu_predictor.cu
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@@ -231,12 +231,13 @@ class GPUPredictor : public xgboost::Predictor {
this->num_group_ = model.param.num_output_group;
}
void PredictInternal
(const SparsePage& batch, size_t num_features,
HostDeviceVector<bst_float>* predictions) {
void PredictInternal(const SparsePage& batch,
size_t num_features,
HostDeviceVector<bst_float>* predictions,
size_t batch_offset) {
dh::safe_cuda(cudaSetDevice(device_));
const int BLOCK_THREADS = 128;
size_t num_rows = batch.offset.DeviceSize() - 1;
size_t num_rows = batch.Size();
const int GRID_SIZE = static_cast<int>(common::DivRoundUp(num_rows, BLOCK_THREADS));
int shared_memory_bytes = static_cast<int>
@@ -249,10 +250,10 @@ class GPUPredictor : public xgboost::Predictor {
size_t entry_start = 0;
PredictKernel<BLOCK_THREADS><<<GRID_SIZE, BLOCK_THREADS, shared_memory_bytes>>>
(dh::ToSpan(nodes_), predictions->DeviceSpan(), dh::ToSpan(tree_segments_),
dh::ToSpan(tree_group_), batch.offset.DeviceSpan(),
batch.data.DeviceSpan(), this->tree_begin_, this->tree_end_, num_features,
num_rows, entry_start, use_shared, this->num_group_);
(dh::ToSpan(nodes_), predictions->DeviceSpan().subspan(batch_offset),
dh::ToSpan(tree_segments_), dh::ToSpan(tree_group_), batch.offset.DeviceSpan(),
batch.data.DeviceSpan(), this->tree_begin_, this->tree_end_, num_features, num_rows,
entry_start, use_shared, this->num_group_);
}
private:
@@ -297,28 +298,10 @@ class GPUPredictor : public xgboost::Predictor {
InitModel(model, tree_begin, tree_end);
size_t batch_offset = 0;
auto* preds = out_preds;
std::unique_ptr<HostDeviceVector<bst_float>> batch_preds{nullptr};
for (auto &batch : dmat->GetBatches<SparsePage>()) {
bool is_external_memory = batch.Size() < dmat->Info().num_row_;
if (is_external_memory) {
batch_preds.reset(new HostDeviceVector<bst_float>);
batch_preds->Resize(batch.Size() * model.param.num_output_group);
std::copy(out_preds->ConstHostVector().begin() + batch_offset,
out_preds->ConstHostVector().begin() + batch_offset + batch_preds->Size(),
batch_preds->HostVector().begin());
preds = batch_preds.get();
}
batch.offset.SetDevice(device_);
batch.data.SetDevice(device_);
preds->SetDevice(device_);
shard_.PredictInternal(batch, model.param.num_feature, preds);
if (is_external_memory) {
auto h_preds = preds->ConstHostVector();
std::copy(h_preds.begin(), h_preds.end(), out_preds->HostVector().begin() + batch_offset);
}
shard_.PredictInternal(batch, model.param.num_feature, out_preds, batch_offset);
batch_offset += batch.Size() * model.param.num_output_group;
}
@@ -356,6 +339,7 @@ class GPUPredictor : public xgboost::Predictor {
size_t n_classes = model.param.num_output_group;
size_t n = n_classes * info.num_row_;
const HostDeviceVector<bst_float>& base_margin = info.base_margin_;
out_preds->SetDevice(device_);
out_preds->Resize(n);
if (base_margin.Size() != 0) {
CHECK_EQ(base_margin.Size(), n);
@@ -454,7 +438,7 @@ class GPUPredictor : public xgboost::Predictor {
}
private:
/*! \brief Re configure shards when GPUSet is changed. */
/*! \brief Reconfigure the shard when GPU is changed. */
void ConfigureShard(int device) {
if (device_ == device) return;