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Support multiple batches in gpu_hist (#5014)

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* Initial external memory training support for GPU Hist tree method.
This commit is contained in:
Rong Ou
2019-11-15 22:50:20 -08:00
committed by Jiaming Yuan
parent 97abcc7ee2
commit 0afcc55d98
15 changed files with 559 additions and 134 deletions
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46
src/data/ellpack_page.cu
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@@ -69,6 +69,8 @@ EllpackPageImpl::EllpackPageImpl(DMatrix* dmat, const BatchParam& param) {
monitor_.Init("ellpack_page");
dh::safe_cuda(cudaSetDevice(param.gpu_id));
matrix.n_rows = dmat->Info().num_row_;
monitor_.StartCuda("Quantiles");
// Create the quantile sketches for the dmatrix and initialize HistogramCuts.
common::HistogramCuts hmat;
@@ -206,7 +208,7 @@ void EllpackPageImpl::CreateHistIndices(int device,
// Return the number of rows contained in this page.
size_t EllpackPageImpl::Size() const {
return n_rows;
return matrix.n_rows;
}
// Clear the current page.
@@ -214,44 +216,50 @@ void EllpackPageImpl::Clear() {
ba_.Clear();
gidx_buffer = {};
idx_buffer.clear();
n_rows = 0;
sparse_page_.Clear();
matrix.base_rowid = 0;
matrix.n_rows = 0;
device_initialized_ = false;
}
// Push a CSR page to the current page.
//
// First compress the CSR page into ELLPACK, then the compressed buffer is copied to host and
// appended to the existing host vector.
// The CSR pages are accumulated in memory until they reach a certain size, then written out as
// compressed ELLPACK.
void EllpackPageImpl::Push(int device, const SparsePage& batch) {
sparse_page_.Push(batch);
matrix.n_rows += batch.Size();
}
// Compress the accumulated SparsePage.
void EllpackPageImpl::CompressSparsePage(int device) {
monitor_.StartCuda("InitCompressedData");
InitCompressedData(device, batch.Size());
InitCompressedData(device, matrix.n_rows);
monitor_.StopCuda("InitCompressedData");
monitor_.StartCuda("BinningCompression");
DeviceHistogramBuilderState hist_builder_row_state(batch.Size());
hist_builder_row_state.BeginBatch(batch);
CreateHistIndices(device, batch, hist_builder_row_state.GetRowStateOnDevice());
DeviceHistogramBuilderState hist_builder_row_state(matrix.n_rows);
hist_builder_row_state.BeginBatch(sparse_page_);
CreateHistIndices(device, sparse_page_, hist_builder_row_state.GetRowStateOnDevice());
hist_builder_row_state.EndBatch();
monitor_.StopCuda("BinningCompression");
monitor_.StartCuda("CopyDeviceToHost");
std::vector<common::CompressedByteT> buffer(gidx_buffer.size());
dh::CopyDeviceSpanToVector(&buffer, gidx_buffer);
int offset = 0;
if (!idx_buffer.empty()) {
offset = ::xgboost::common::detail::kPadding;
}
idx_buffer.reserve(idx_buffer.size() + buffer.size() - offset);
idx_buffer.insert(idx_buffer.end(), buffer.begin() + offset, buffer.end());
idx_buffer.resize(gidx_buffer.size());
dh::CopyDeviceSpanToVector(&idx_buffer, gidx_buffer);
ba_.Clear();
gidx_buffer = {};
monitor_.StopCuda("CopyDeviceToHost");
n_rows += batch.Size();
}
// Return the memory cost for storing the compressed features.
size_t EllpackPageImpl::MemCostBytes() const {
return idx_buffer.size() * sizeof(common::CompressedByteT);
size_t num_symbols = matrix.info.n_bins + 1;
// Required buffer size for storing data matrix in ELLPack format.
size_t compressed_size_bytes = common::CompressedBufferWriter::CalculateBufferSize(
matrix.info.row_stride * matrix.n_rows, num_symbols);
return compressed_size_bytes;
}
// Copy the compressed features to GPU.