* Extract Sketch Entry from hist maker. * Add a new sketch container for sorted inputs. * Optimize bin search.
293 lines
11 KiB
C++
293 lines
11 KiB
C++
/*!
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* Copyright 2017-2020 by Contributors
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* \file hist_util.cc
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*/
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#include <dmlc/timer.h>
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#include <dmlc/omp.h>
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#include <rabit/rabit.h>
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#include <numeric>
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#include <vector>
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#include "xgboost/base.h"
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#include "../common/common.h"
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#include "hist_util.h"
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#include "random.h"
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#include "column_matrix.h"
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#include "quantile.h"
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#include "../data/gradient_index.h"
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#if defined(XGBOOST_MM_PREFETCH_PRESENT)
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#include <xmmintrin.h>
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#define PREFETCH_READ_T0(addr) _mm_prefetch(reinterpret_cast<const char*>(addr), _MM_HINT_T0)
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#elif defined(XGBOOST_BUILTIN_PREFETCH_PRESENT)
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#define PREFETCH_READ_T0(addr) __builtin_prefetch(reinterpret_cast<const char*>(addr), 0, 3)
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#else // no SW pre-fetching available; PREFETCH_READ_T0 is no-op
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#define PREFETCH_READ_T0(addr) do {} while (0)
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#endif // defined(XGBOOST_MM_PREFETCH_PRESENT)
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namespace xgboost {
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namespace common {
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HistogramCuts::HistogramCuts() {
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cut_ptrs_.HostVector().emplace_back(0);
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}
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/*!
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* \brief fill a histogram by zeros in range [begin, end)
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*/
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template<typename GradientSumT>
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void InitilizeHistByZeroes(GHistRow<GradientSumT> hist, size_t begin, size_t end) {
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#if defined(XGBOOST_STRICT_R_MODE) && XGBOOST_STRICT_R_MODE == 1
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std::fill(hist.begin() + begin, hist.begin() + end,
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xgboost::detail::GradientPairInternal<GradientSumT>());
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#else // defined(XGBOOST_STRICT_R_MODE) && XGBOOST_STRICT_R_MODE == 1
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memset(hist.data() + begin, '\0', (end-begin)*
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sizeof(xgboost::detail::GradientPairInternal<GradientSumT>));
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#endif // defined(XGBOOST_STRICT_R_MODE) && XGBOOST_STRICT_R_MODE == 1
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}
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template void InitilizeHistByZeroes(GHistRow<float> hist, size_t begin,
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size_t end);
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template void InitilizeHistByZeroes(GHistRow<double> hist, size_t begin,
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size_t end);
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/*!
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* \brief Increment hist as dst += add in range [begin, end)
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*/
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template<typename GradientSumT>
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void IncrementHist(GHistRow<GradientSumT> dst, const GHistRow<GradientSumT> add,
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size_t begin, size_t end) {
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GradientSumT* pdst = reinterpret_cast<GradientSumT*>(dst.data());
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const GradientSumT* padd = reinterpret_cast<const GradientSumT*>(add.data());
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for (size_t i = 2 * begin; i < 2 * end; ++i) {
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pdst[i] += padd[i];
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}
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}
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template void IncrementHist(GHistRow<float> dst, const GHistRow<float> add,
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size_t begin, size_t end);
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template void IncrementHist(GHistRow<double> dst, const GHistRow<double> add,
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size_t begin, size_t end);
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/*!
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* \brief Copy hist from src to dst in range [begin, end)
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*/
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template<typename GradientSumT>
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void CopyHist(GHistRow<GradientSumT> dst, const GHistRow<GradientSumT> src,
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size_t begin, size_t end) {
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GradientSumT* pdst = reinterpret_cast<GradientSumT*>(dst.data());
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const GradientSumT* psrc = reinterpret_cast<const GradientSumT*>(src.data());
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for (size_t i = 2 * begin; i < 2 * end; ++i) {
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pdst[i] = psrc[i];
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}
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}
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template void CopyHist(GHistRow<float> dst, const GHistRow<float> src,
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size_t begin, size_t end);
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template void CopyHist(GHistRow<double> dst, const GHistRow<double> src,
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size_t begin, size_t end);
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/*!
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* \brief Compute Subtraction: dst = src1 - src2 in range [begin, end)
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*/
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template<typename GradientSumT>
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void SubtractionHist(GHistRow<GradientSumT> dst, const GHistRow<GradientSumT> src1,
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const GHistRow<GradientSumT> src2,
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size_t begin, size_t end) {
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GradientSumT* pdst = reinterpret_cast<GradientSumT*>(dst.data());
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const GradientSumT* psrc1 = reinterpret_cast<const GradientSumT*>(src1.data());
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const GradientSumT* psrc2 = reinterpret_cast<const GradientSumT*>(src2.data());
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for (size_t i = 2 * begin; i < 2 * end; ++i) {
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pdst[i] = psrc1[i] - psrc2[i];
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}
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}
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template void SubtractionHist(GHistRow<float> dst, const GHistRow<float> src1,
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const GHistRow<float> src2,
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size_t begin, size_t end);
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template void SubtractionHist(GHistRow<double> dst, const GHistRow<double> src1,
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const GHistRow<double> src2,
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size_t begin, size_t end);
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struct Prefetch {
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public:
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static constexpr size_t kCacheLineSize = 64;
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static constexpr size_t kPrefetchOffset = 10;
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private:
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static constexpr size_t kNoPrefetchSize =
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kPrefetchOffset + kCacheLineSize /
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sizeof(decltype(GHistIndexMatrix::row_ptr)::value_type);
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public:
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static size_t NoPrefetchSize(size_t rows) {
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return std::min(rows, kNoPrefetchSize);
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}
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template <typename T>
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static constexpr size_t GetPrefetchStep() {
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return Prefetch::kCacheLineSize / sizeof(T);
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}
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};
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constexpr size_t Prefetch::kNoPrefetchSize;
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template <typename FPType, bool do_prefetch, typename BinIdxType,
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bool first_page, bool any_missing = true>
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void BuildHistKernel(const std::vector<GradientPair> &gpair,
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const RowSetCollection::Elem row_indices,
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const GHistIndexMatrix &gmat, GHistRow<FPType> hist) {
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const size_t size = row_indices.Size();
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const size_t *rid = row_indices.begin;
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auto const *pgh = reinterpret_cast<const float *>(gpair.data());
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const BinIdxType *gradient_index = gmat.index.data<BinIdxType>();
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auto const &row_ptr = gmat.row_ptr.data();
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auto base_rowid = gmat.base_rowid;
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const uint32_t *offsets = gmat.index.Offset();
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auto get_row_ptr = [&](size_t ridx) {
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return first_page ? row_ptr[ridx] : row_ptr[ridx - base_rowid];
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};
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auto get_rid = [&](size_t ridx) {
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return first_page ? ridx : (ridx - base_rowid);
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};
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const size_t n_features =
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get_row_ptr(row_indices.begin[0] + 1) - get_row_ptr(row_indices.begin[0]);
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auto hist_data = reinterpret_cast<FPType *>(hist.data());
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const uint32_t two{2}; // Each element from 'gpair' and 'hist' contains
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// 2 FP values: gradient and hessian.
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// So we need to multiply each row-index/bin-index by 2
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// to work with gradient pairs as a singe row FP array
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for (size_t i = 0; i < size; ++i) {
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const size_t icol_start =
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any_missing ? get_row_ptr(rid[i]) : get_rid(rid[i]) * n_features;
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const size_t icol_end =
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any_missing ? get_row_ptr(rid[i] + 1) : icol_start + n_features;
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const size_t row_size = icol_end - icol_start;
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const size_t idx_gh = two * rid[i];
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if (do_prefetch) {
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const size_t icol_start_prefetch =
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any_missing
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? get_row_ptr(rid[i + Prefetch::kPrefetchOffset])
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: get_rid(rid[i + Prefetch::kPrefetchOffset]) * n_features;
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const size_t icol_end_prefetch =
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any_missing ? get_row_ptr(rid[i + Prefetch::kPrefetchOffset] + 1)
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: icol_start_prefetch + n_features;
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PREFETCH_READ_T0(pgh + two * rid[i + Prefetch::kPrefetchOffset]);
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for (size_t j = icol_start_prefetch; j < icol_end_prefetch;
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j += Prefetch::GetPrefetchStep<uint32_t>()) {
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PREFETCH_READ_T0(gradient_index + j);
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}
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}
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const BinIdxType *gr_index_local = gradient_index + icol_start;
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for (size_t j = 0; j < row_size; ++j) {
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const uint32_t idx_bin = two * (static_cast<uint32_t>(gr_index_local[j]) +
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(any_missing ? 0 : offsets[j]));
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hist_data[idx_bin] += pgh[idx_gh];
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hist_data[idx_bin + 1] += pgh[idx_gh + 1];
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}
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}
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}
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template <typename FPType, bool do_prefetch, bool any_missing>
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void BuildHistDispatch(const std::vector<GradientPair> &gpair,
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const RowSetCollection::Elem row_indices,
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const GHistIndexMatrix &gmat, GHistRow<FPType> hist) {
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auto first_page = gmat.base_rowid == 0;
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if (first_page) {
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switch (gmat.index.GetBinTypeSize()) {
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case kUint8BinsTypeSize:
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BuildHistKernel<FPType, do_prefetch, uint8_t, true, any_missing>(
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gpair, row_indices, gmat, hist);
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break;
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case kUint16BinsTypeSize:
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BuildHistKernel<FPType, do_prefetch, uint16_t, true, any_missing>(
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gpair, row_indices, gmat, hist);
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break;
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case kUint32BinsTypeSize:
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BuildHistKernel<FPType, do_prefetch, uint32_t, true, any_missing>(
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gpair, row_indices, gmat, hist);
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break;
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default:
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CHECK(false); // no default behavior
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}
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} else {
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switch (gmat.index.GetBinTypeSize()) {
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case kUint8BinsTypeSize:
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BuildHistKernel<FPType, do_prefetch, uint8_t, false, any_missing>(
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gpair, row_indices, gmat, hist);
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break;
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case kUint16BinsTypeSize:
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BuildHistKernel<FPType, do_prefetch, uint16_t, false, any_missing>(
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gpair, row_indices, gmat, hist);
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break;
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case kUint32BinsTypeSize:
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BuildHistKernel<FPType, do_prefetch, uint32_t, false, any_missing>(
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gpair, row_indices, gmat, hist);
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break;
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default:
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CHECK(false); // no default behavior
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}
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}
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}
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template <typename GradientSumT>
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template <bool any_missing>
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void GHistBuilder<GradientSumT>::BuildHist(
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const std::vector<GradientPair> &gpair,
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const RowSetCollection::Elem row_indices, const GHistIndexMatrix &gmat,
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GHistRowT hist) const {
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const size_t nrows = row_indices.Size();
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const size_t no_prefetch_size = Prefetch::NoPrefetchSize(nrows);
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// if need to work with all rows from bin-matrix (e.g. root node)
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const bool contiguousBlock =
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(row_indices.begin[nrows - 1] - row_indices.begin[0]) == (nrows - 1);
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if (contiguousBlock) {
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// contiguous memory access, built-in HW prefetching is enough
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BuildHistDispatch<GradientSumT, false, any_missing>(gpair, row_indices,
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gmat, hist);
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} else {
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const RowSetCollection::Elem span1(row_indices.begin,
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row_indices.end - no_prefetch_size);
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const RowSetCollection::Elem span2(row_indices.end - no_prefetch_size,
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row_indices.end);
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BuildHistDispatch<GradientSumT, true, any_missing>(gpair, span1, gmat,
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hist);
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// no prefetching to avoid loading extra memory
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BuildHistDispatch<GradientSumT, false, any_missing>(gpair, span2, gmat,
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hist);
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}
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}
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template void
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GHistBuilder<float>::BuildHist<true>(const std::vector<GradientPair> &gpair,
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const RowSetCollection::Elem row_indices,
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const GHistIndexMatrix &gmat,
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GHistRow<float> hist) const;
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template void
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GHistBuilder<float>::BuildHist<false>(const std::vector<GradientPair> &gpair,
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const RowSetCollection::Elem row_indices,
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const GHistIndexMatrix &gmat,
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GHistRow<float> hist) const;
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template void
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GHistBuilder<double>::BuildHist<true>(const std::vector<GradientPair> &gpair,
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const RowSetCollection::Elem row_indices,
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const GHistIndexMatrix &gmat,
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GHistRow<double> hist) const;
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template void
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GHistBuilder<double>::BuildHist<false>(const std::vector<GradientPair> &gpair,
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const RowSetCollection::Elem row_indices,
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const GHistIndexMatrix &gmat,
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GHistRow<double> hist) const;
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} // namespace common
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} // namespace xgboost
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