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xgboost/src/common/algorithm.cuh
Hui Liu 2d7ffbdf3d merge latest changes
2023-12-13 21:06:28 -08:00

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/**
* Copyright 2022-2023 by XGBoost Contributors
*/
#ifndef XGBOOST_COMMON_ALGORITHM_CUH_
#define XGBOOST_COMMON_ALGORITHM_CUH_
#include <thrust/copy.h> // copy
#include <thrust/sort.h> // stable_sort_by_key
#include <thrust/tuple.h> // tuple,get
#include <cstddef> // size_t
#include <cstdint> // int32_t
#if defined(XGBOOST_USE_CUDA)
#include <cub/cub.cuh> // DispatchSegmentedRadixSort,NullType,DoubleBuffer
#elif defined(XGBOOST_USE_HIP)
#include <hipcub/hipcub.hpp>
#endif
#include <iterator> // distance
#include <limits> // numeric_limits
#include <type_traits> // conditional_t,remove_const_t
#include "common.h" // safe_cuda
#include "cuda_context.cuh" // CUDAContext
#include "device_helpers.cuh" // TemporaryArray,SegmentId,LaunchN,Iota,device_vector
#include "xgboost/base.h" // XGBOOST_DEVICE
#include "xgboost/context.h" // Context
#include "xgboost/logging.h" // CHECK
#include "xgboost/span.h" // Span,byte
namespace xgboost::common {
namespace detail {
// Wrapper around cub sort to define is_decending
template <bool IS_DESCENDING, typename KeyT, typename BeginOffsetIteratorT,
typename EndOffsetIteratorT>
static void DeviceSegmentedRadixSortKeys(CUDAContext const *ctx, void *d_temp_storage,
std::size_t &temp_storage_bytes, // NOLINT
const KeyT *d_keys_in, KeyT *d_keys_out, int num_items,
int num_segments, BeginOffsetIteratorT d_begin_offsets,
EndOffsetIteratorT d_end_offsets, int begin_bit = 0,
int end_bit = sizeof(KeyT) * 8,
bool debug_synchronous = false) {
using OffsetT = int;
// Null value type
#if defined(XGBOOST_USE_CUDA)
cub::DoubleBuffer<KeyT> d_keys(const_cast<KeyT *>(d_keys_in), d_keys_out);
cub::DoubleBuffer<cub::NullType> d_values;
dh::safe_cuda((cub::DispatchSegmentedRadixSort<
IS_DESCENDING, KeyT, cub::NullType, BeginOffsetIteratorT, EndOffsetIteratorT,
OffsetT>::Dispatch(d_temp_storage, temp_storage_bytes, d_keys, d_values, num_items,
num_segments, d_begin_offsets, d_end_offsets, begin_bit,
end_bit, false, ctx->Stream(), debug_synchronous)));
#elif defined(XGBOOST_USE_HIP)
if (IS_DESCENDING) {
rocprim::segmented_radix_sort_pairs_desc<KeyT, cub::NullType, BeginOffsetIteratorT>(d_temp_storage,
temp_storage_bytes, d_keys_in, d_keys_out, nullptr, nullptr, num_items,
num_segments, d_begin_offsets, d_end_offsets,
begin_bit, end_bit, ctx->Stream(), debug_synchronous);
}
else {
rocprim::segmented_radix_sort_pairs<KeyT, cub::NullType, BeginOffsetIteratorT>(d_temp_storage,
temp_storage_bytes, d_keys_in, d_keys_out, nullptr, nullptr, num_items,
num_segments, d_begin_offsets, d_end_offsets,
begin_bit, end_bit, ctx->Stream(), debug_synchronous);
}
#endif
}
// Wrapper around cub sort for easier `descending` sort.
template <bool descending, typename KeyT, typename ValueT, typename BeginOffsetIteratorT,
typename EndOffsetIteratorT>
void DeviceSegmentedRadixSortPair(void *d_temp_storage,
std::size_t &temp_storage_bytes, // NOLINT
const KeyT *d_keys_in, KeyT *d_keys_out,
const ValueT *d_values_in, ValueT *d_values_out,
std::size_t num_items, std::size_t num_segments,
BeginOffsetIteratorT d_begin_offsets,
EndOffsetIteratorT d_end_offsets, dh::CUDAStreamView stream,
int begin_bit = 0, int end_bit = sizeof(KeyT) * 8) {
#if defined(XGBOOST_USE_CUDA)
cub::DoubleBuffer<KeyT> d_keys(const_cast<KeyT *>(d_keys_in), d_keys_out);
cub::DoubleBuffer<ValueT> d_values(const_cast<ValueT *>(d_values_in), d_values_out);
#endif
// In old version of cub, num_items in dispatch is also int32_t, no way to change.
using OffsetT = std::conditional_t<dh::BuildWithCUDACub() && dh::HasThrustMinorVer<13>(),
std::size_t, std::int32_t>;
CHECK_LE(num_items, std::numeric_limits<OffsetT>::max());
// For Thrust >= 1.12 or CUDA >= 11.4, we require system cub installation
#if defined(XGBOOST_USE_CUDA)
#if THRUST_MAJOR_VERSION >= 2
dh::safe_cuda((cub::DispatchSegmentedRadixSort<
descending, KeyT, ValueT, BeginOffsetIteratorT, EndOffsetIteratorT,
OffsetT>::Dispatch(d_temp_storage, temp_storage_bytes, d_keys, d_values, num_items,
num_segments, d_begin_offsets, d_end_offsets, begin_bit,
end_bit, false, stream)));
#elif (THRUST_MAJOR_VERSION == 1 && THRUST_MINOR_VERSION >= 13)
dh::safe_cuda((cub::DispatchSegmentedRadixSort<
descending, KeyT, ValueT, BeginOffsetIteratorT, EndOffsetIteratorT,
OffsetT>::Dispatch(d_temp_storage, temp_storage_bytes, d_keys, d_values, num_items,
num_segments, d_begin_offsets, d_end_offsets, begin_bit,
end_bit, false, stream, false)));
#else
dh::safe_cuda(
(cub::DispatchSegmentedRadixSort<descending, KeyT, ValueT, BeginOffsetIteratorT,
OffsetT>::Dispatch(d_temp_storage, temp_storage_bytes,
d_keys, d_values, num_items, num_segments,
d_begin_offsets, d_end_offsets, begin_bit,
end_bit, false, stream, false)));
#endif
#elif defined(XGBOOST_USE_HIP)
if (descending) {
rocprim::segmented_radix_sort_pairs_desc(d_temp_storage, temp_storage_bytes, d_keys_in, d_keys_out,
d_values_in, d_values_out, num_items, num_segments,
d_begin_offsets, d_end_offsets, begin_bit, end_bit, stream, false);
}
else {
rocprim::segmented_radix_sort_pairs(d_temp_storage, temp_storage_bytes, d_keys_in, d_keys_out,
d_values_in, d_values_out, num_items, num_segments, d_begin_offsets, d_end_offsets,
begin_bit, end_bit, stream, false);
}
#endif
}
} // namespace detail
template <typename U, typename V>
void SegmentedSequence(Context const *ctx, Span<U> d_offset_ptr, Span<V> out_sequence) {
dh::LaunchN(out_sequence.size(), ctx->CUDACtx()->Stream(),
[out_sequence, d_offset_ptr] __device__(std::size_t idx) {
auto group = dh::SegmentId(d_offset_ptr, idx);
out_sequence[idx] = idx - d_offset_ptr[group];
});
}
template <bool descending, typename U, typename V>
inline void SegmentedSortKeys(Context const *ctx, Span<V const> group_ptr,
Span<U> out_sorted_values) {
CHECK_GE(group_ptr.size(), 1ul);
std::size_t n_groups = group_ptr.size() - 1;
std::size_t bytes = 0;
auto const *cuctx = ctx->CUDACtx();
CHECK(cuctx);
detail::DeviceSegmentedRadixSortKeys<descending>(
cuctx, nullptr, bytes, out_sorted_values.data(), out_sorted_values.data(),
out_sorted_values.size(), n_groups, group_ptr.data(), group_ptr.data() + 1);
dh::TemporaryArray<byte> temp_storage(bytes);
detail::DeviceSegmentedRadixSortKeys<descending>(
cuctx, temp_storage.data().get(), bytes, out_sorted_values.data(), out_sorted_values.data(),
out_sorted_values.size(), n_groups, group_ptr.data(), group_ptr.data() + 1);
}
/**
* \brief Create sorted index for data with multiple segments.
*
* \tparam accending sorted in non-decreasing order.
* \tparam per_seg_index Index starts from 0 for each segment if true, otherwise the
* the index span the whole data.
*/
template <bool accending, bool per_seg_index, typename U, typename V, typename IdxT>
void SegmentedArgSort(Context const *ctx, Span<U> values, Span<V> group_ptr,
Span<IdxT> sorted_idx) {
auto cuctx = ctx->CUDACtx();
CHECK_GE(group_ptr.size(), 1ul);
std::size_t n_groups = group_ptr.size() - 1;
std::size_t bytes = 0;
if (per_seg_index) {
SegmentedSequence(ctx, group_ptr, sorted_idx);
} else {
dh::Iota(sorted_idx, cuctx->Stream());
}
dh::TemporaryArray<std::remove_const_t<U>> values_out(values.size());
dh::TemporaryArray<std::remove_const_t<IdxT>> sorted_idx_out(sorted_idx.size());
detail::DeviceSegmentedRadixSortPair<!accending>(
nullptr, bytes, values.data(), values_out.data().get(), sorted_idx.data(),
sorted_idx_out.data().get(), sorted_idx.size(), n_groups, group_ptr.data(),
group_ptr.data() + 1, cuctx->Stream());
dh::TemporaryArray<byte> temp_storage(bytes);
detail::DeviceSegmentedRadixSortPair<!accending>(
temp_storage.data().get(), bytes, values.data(), values_out.data().get(), sorted_idx.data(),
sorted_idx_out.data().get(), sorted_idx.size(), n_groups, group_ptr.data(),
group_ptr.data() + 1, cuctx->Stream());
dh::safe_cuda(cudaMemcpyAsync(sorted_idx.data(), sorted_idx_out.data().get(),
sorted_idx.size_bytes(), cudaMemcpyDeviceToDevice,
cuctx->Stream()));
}
/**
* \brief Different from the radix-sort-based argsort, this one can handle cases where
* segment doesn't start from 0, but as a result it uses comparison sort.
*/
template <typename SegIt, typename ValIt>
void SegmentedArgMergeSort(Context const *ctx, SegIt seg_begin, SegIt seg_end, ValIt val_begin,
ValIt val_end, dh::device_vector<std::size_t> *p_sorted_idx) {
auto cuctx = ctx->CUDACtx();
using Tup = thrust::tuple<std::int32_t, float>;
auto &sorted_idx = *p_sorted_idx;
std::size_t n = std::distance(val_begin, val_end);
sorted_idx.resize(n);
dh::Iota(dh::ToSpan(sorted_idx), cuctx->Stream());
dh::device_vector<Tup> keys(sorted_idx.size());
auto key_it = dh::MakeTransformIterator<Tup>(thrust::make_counting_iterator(0ul),
[=] XGBOOST_DEVICE(std::size_t i) -> Tup {
std::int32_t seg_idx;
if (i < *seg_begin) {
seg_idx = -1;
} else {
seg_idx = dh::SegmentId(seg_begin, seg_end, i);
}
auto residue = val_begin[i];
return thrust::make_tuple(seg_idx, residue);
});
thrust::copy(ctx->CUDACtx()->CTP(), key_it, key_it + keys.size(), keys.begin());
thrust::stable_sort_by_key(cuctx->TP(), keys.begin(), keys.end(), sorted_idx.begin(),
[=] XGBOOST_DEVICE(Tup const &l, Tup const &r) {
if (thrust::get<0>(l) != thrust::get<0>(r)) {
return thrust::get<0>(l) < thrust::get<0>(r); // segment index
}
return thrust::get<1>(l) < thrust::get<1>(r); // residue
});
}
template <bool accending, typename IdxT, typename U>
void ArgSort(xgboost::Context const *ctx, xgboost::common::Span<U> keys,
xgboost::common::Span<IdxT> sorted_idx) {
std::size_t bytes = 0;
auto cuctx = ctx->CUDACtx();
dh::Iota(sorted_idx, cuctx->Stream());
using KeyT = typename decltype(keys)::value_type;
using ValueT = std::remove_const_t<IdxT>;
dh::TemporaryArray<KeyT> out(keys.size());
cub::DoubleBuffer<KeyT> d_keys(const_cast<KeyT *>(keys.data()), out.data().get());
dh::TemporaryArray<IdxT> sorted_idx_out(sorted_idx.size());
cub::DoubleBuffer<ValueT> d_values(const_cast<ValueT *>(sorted_idx.data()),
sorted_idx_out.data().get());
// track https://github.com/NVIDIA/cub/pull/340 for 64bit length support
using OffsetT = std::conditional_t<!dh::BuildWithCUDACub(), std::ptrdiff_t, int32_t>;
CHECK_LE(sorted_idx.size(), std::numeric_limits<OffsetT>::max());
if (accending) {
void *d_temp_storage = nullptr;
#if THRUST_MAJOR_VERSION >= 2
dh::safe_cuda((cub::DispatchRadixSort<false, KeyT, ValueT, OffsetT>::Dispatch(
d_temp_storage, bytes, d_keys, d_values, sorted_idx.size(), 0, sizeof(KeyT) * 8, false,
cuctx->Stream())));
#else
dh::safe_cuda((cub::DispatchRadixSort<false, KeyT, ValueT, OffsetT>::Dispatch(
d_temp_storage, bytes, d_keys, d_values, sorted_idx.size(), 0, sizeof(KeyT) * 8, false,
nullptr, false)));
#endif
dh::TemporaryArray<char> storage(bytes);
d_temp_storage = storage.data().get();
#if THRUST_MAJOR_VERSION >= 2
dh::safe_cuda((cub::DispatchRadixSort<false, KeyT, ValueT, OffsetT>::Dispatch(
d_temp_storage, bytes, d_keys, d_values, sorted_idx.size(), 0, sizeof(KeyT) * 8, false,
cuctx->Stream())));
#else
dh::safe_cuda((cub::DispatchRadixSort<false, KeyT, ValueT, OffsetT>::Dispatch(
d_temp_storage, bytes, d_keys, d_values, sorted_idx.size(), 0, sizeof(KeyT) * 8, false,
nullptr, false)));
#endif
} else {
void *d_temp_storage = nullptr;
#if THRUST_MAJOR_VERSION >= 2
dh::safe_cuda((cub::DispatchRadixSort<true, KeyT, ValueT, OffsetT>::Dispatch(
d_temp_storage, bytes, d_keys, d_values, sorted_idx.size(), 0, sizeof(KeyT) * 8, false,
cuctx->Stream())));
#else
dh::safe_cuda((cub::DispatchRadixSort<true, KeyT, ValueT, OffsetT>::Dispatch(
d_temp_storage, bytes, d_keys, d_values, sorted_idx.size(), 0, sizeof(KeyT) * 8, false,
nullptr, false)));
#endif
dh::TemporaryArray<char> storage(bytes);
d_temp_storage = storage.data().get();
#if THRUST_MAJOR_VERSION >= 2
dh::safe_cuda((cub::DispatchRadixSort<true, KeyT, ValueT, OffsetT>::Dispatch(
d_temp_storage, bytes, d_keys, d_values, sorted_idx.size(), 0, sizeof(KeyT) * 8, false,
cuctx->Stream())));
#else
dh::safe_cuda((cub::DispatchRadixSort<true, KeyT, ValueT, OffsetT>::Dispatch(
d_temp_storage, bytes, d_keys, d_values, sorted_idx.size(), 0, sizeof(KeyT) * 8, false,
nullptr, false)));
#endif
}
dh::safe_cuda(cudaMemcpyAsync(sorted_idx.data(), sorted_idx_out.data().get(),
sorted_idx.size_bytes(), cudaMemcpyDeviceToDevice,
cuctx->Stream()));
}
} // namespace xgboost::common
#endif // XGBOOST_COMMON_ALGORITHM_CUH_
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