xgboost/src/tree/gpu_hist/row_partitioner.cu

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/*!
* Copyright 2017-2019 XGBoost contributors
*/
#include <thrust/iterator/discard_iterator.h>
#include <thrust/iterator/transform_output_iterator.h>
#include <thrust/sequence.h>
#include <vector>
#include "../../common/device_helpers.cuh"
#include "row_partitioner.cuh"
namespace xgboost {
namespace tree {
struct IndicateLeftTransform {
bst_node_t left_nidx;
explicit IndicateLeftTransform(bst_node_t left_nidx) : left_nidx(left_nidx) {}
__host__ __device__ __forceinline__ size_t
operator()(const bst_node_t& x) const {
return x == left_nidx ? 1 : 0;
}
};
struct IndexFlagTuple {
size_t idx;
size_t flag;
};
struct IndexFlagOp {
__device__ IndexFlagTuple operator()(const IndexFlagTuple& a,
const IndexFlagTuple& b) const {
return {b.idx, a.flag + b.flag};
}
};
struct WriteResultsFunctor {
bst_node_t left_nidx;
common::Span<bst_node_t> position_in;
common::Span<bst_node_t> position_out;
common::Span<RowPartitioner::RowIndexT> ridx_in;
common::Span<RowPartitioner::RowIndexT> ridx_out;
int64_t* d_left_count;
__device__ int operator()(const IndexFlagTuple& x) {
// the ex_scan_result represents how many rows have been assigned to left
// node so far during scan.
int scatter_address;
if (position_in[x.idx] == left_nidx) {
scatter_address = x.flag - 1; // -1 because inclusive scan
} else {
// current number of rows belong to right node + total number of rows
// belong to left node
scatter_address = (x.idx - x.flag) + *d_left_count;
}
// copy the node id to output
position_out[scatter_address] = position_in[x.idx];
ridx_out[scatter_address] = ridx_in[x.idx];
// Discard
return 0;
}
};
void RowPartitioner::SortPosition(common::Span<bst_node_t> position,
common::Span<bst_node_t> position_out,
common::Span<RowIndexT> ridx,
common::Span<RowIndexT> ridx_out,
bst_node_t left_nidx, bst_node_t right_nidx,
int64_t* d_left_count, cudaStream_t stream) {
WriteResultsFunctor write_results{left_nidx, position, position_out,
ridx, ridx_out, d_left_count};
auto discard_write_iterator = thrust::make_transform_output_iterator(
thrust::discard_iterator<int>(), write_results);
auto input_iterator = dh::MakeTransformIterator<IndexFlagTuple>(
thrust::make_counting_iterator(0llu), [=] __device__(size_t idx) {
return IndexFlagTuple{idx, position[idx] == left_nidx};
});
dh::XGBCachingDeviceAllocator<char> alloc;
thrust::inclusive_scan(thrust::cuda::par(alloc).on(stream), input_iterator,
input_iterator + position.size(),
discard_write_iterator,
[=] __device__(IndexFlagTuple a, IndexFlagTuple b) {
return IndexFlagTuple{b.idx, a.flag + b.flag};
});
}
RowPartitioner::RowPartitioner(int device_idx, size_t num_rows)
: device_idx_(device_idx) {
dh::safe_cuda(cudaSetDevice(device_idx_));
ridx_a_.resize(num_rows);
ridx_b_.resize(num_rows);
position_a_.resize(num_rows);
position_b_.resize(num_rows);
ridx_ = dh::DoubleBuffer<RowIndexT>{&ridx_a_, &ridx_b_};
position_ = dh::DoubleBuffer<bst_node_t>{&position_a_, &position_b_};
ridx_segments_.emplace_back(Segment(0, num_rows));
thrust::sequence(
thrust::device_pointer_cast(ridx_.CurrentSpan().data()),
thrust::device_pointer_cast(ridx_.CurrentSpan().data() + ridx_.Size()));
thrust::fill(
thrust::device_pointer_cast(position_.Current()),
thrust::device_pointer_cast(position_.Current() + position_.Size()), 0);
left_counts_.resize(256);
thrust::fill(left_counts_.begin(), left_counts_.end(), 0);
streams_.resize(2);
for (auto& stream : streams_) {
dh::safe_cuda(cudaStreamCreate(&stream));
}
}
RowPartitioner::~RowPartitioner() {
dh::safe_cuda(cudaSetDevice(device_idx_));
for (auto& stream : streams_) {
dh::safe_cuda(cudaStreamDestroy(stream));
}
}
common::Span<const RowPartitioner::RowIndexT> RowPartitioner::GetRows(
bst_node_t nidx) {
auto segment = ridx_segments_.at(nidx);
// Return empty span here as a valid result
// Will error if we try to construct a span from a pointer with size 0
if (segment.Size() == 0) {
return common::Span<const RowPartitioner::RowIndexT>();
}
return ridx_.CurrentSpan().subspan(segment.begin, segment.Size());
}
common::Span<const RowPartitioner::RowIndexT> RowPartitioner::GetRows() {
return ridx_.CurrentSpan();
}
common::Span<const bst_node_t> RowPartitioner::GetPosition() {
return position_.CurrentSpan();
}
std::vector<RowPartitioner::RowIndexT> RowPartitioner::GetRowsHost(
bst_node_t nidx) {
auto span = GetRows(nidx);
std::vector<RowIndexT> rows(span.size());
dh::CopyDeviceSpanToVector(&rows, span);
return rows;
}
std::vector<bst_node_t> RowPartitioner::GetPositionHost() {
auto span = GetPosition();
std::vector<bst_node_t> position(span.size());
dh::CopyDeviceSpanToVector(&position, span);
return position;
}
void RowPartitioner::SortPositionAndCopy(const Segment& segment,
bst_node_t left_nidx,
bst_node_t right_nidx,
int64_t* d_left_count,
cudaStream_t stream) {
SortPosition(
// position_in
common::Span<bst_node_t>(position_.Current() + segment.begin,
segment.Size()),
// position_out
common::Span<bst_node_t>(position_.Other() + segment.begin,
segment.Size()),
// row index in
common::Span<RowIndexT>(ridx_.Current() + segment.begin, segment.Size()),
// row index out
common::Span<RowIndexT>(ridx_.Other() + segment.begin, segment.Size()),
left_nidx, right_nidx, d_left_count, stream);
// Copy back key/value
const auto d_position_current = position_.Current() + segment.begin;
const auto d_position_other = position_.Other() + segment.begin;
const auto d_ridx_current = ridx_.Current() + segment.begin;
const auto d_ridx_other = ridx_.Other() + segment.begin;
dh::LaunchN(device_idx_, segment.Size(), stream, [=] __device__(size_t idx) {
d_position_current[idx] = d_position_other[idx];
d_ridx_current[idx] = d_ridx_other[idx];
});
}
}; // namespace tree
}; // namespace xgboost