Performance optimizations for Intel CPUs (#3957)
* Initial performance optimizations for xgboost * remove includes * revert float->double * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * fix for CI * Check existence of _mm_prefetch and __builtin_prefetch * Fix lint
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@ -91,3 +91,4 @@ lib/
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metastore_db
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metastore_db
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plugin/updater_gpu/test/cpp/data
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plugin/updater_gpu/test/cpp/data
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/include/xgboost/build_config.h
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@ -49,6 +49,26 @@ if(WIN32 AND MINGW)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -static-libstdc++")
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -static-libstdc++")
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endif()
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endif()
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# Check existence of software pre-fetching
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include(CheckCXXSourceCompiles)
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check_cxx_source_compiles("
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#include <xmmintrin.h>
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int main() {
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char data = 0;
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const char* address = &data;
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_mm_prefetch(address, _MM_HINT_NTA);
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return 0;
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}
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" XGBOOST_MM_PREFETCH_PRESENT)
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check_cxx_source_compiles("
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int main() {
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char data = 0;
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const char* address = &data;
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__builtin_prefetch(address, 0, 0);
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return 0;
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}
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" XGBOOST_BUILTIN_PREFETCH_PRESENT)
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# Sanitizer
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# Sanitizer
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if(USE_SANITIZER)
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if(USE_SANITIZER)
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include(cmake/Sanitizer.cmake)
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include(cmake/Sanitizer.cmake)
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@ -82,6 +102,12 @@ include_directories (
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${PROJECT_SOURCE_DIR}/rabit/include
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${PROJECT_SOURCE_DIR}/rabit/include
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)
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)
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# Generate configurable header
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set(CMAKE_LOCAL "${PROJECT_SOURCE_DIR}/cmake")
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set(INCLUDE_ROOT "${PROJECT_SOURCE_DIR}/include")
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message(STATUS "${CMAKE_LOCAL}/build_config.h.in -> ${INCLUDE_ROOT}/xgboost/build_config.h")
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configure_file("${CMAKE_LOCAL}/build_config.h.in" "${INCLUDE_ROOT}/xgboost/build_config.h")
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file(GLOB_RECURSE SOURCES
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file(GLOB_RECURSE SOURCES
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src/*.cc
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src/*.cc
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src/*.h
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src/*.h
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7
cmake/build_config.h.in
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7
cmake/build_config.h.in
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@ -0,0 +1,7 @@
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#ifndef XGBOOST_BUILD_CONFIG_H_
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#define XGBOOST_BUILD_CONFIG_H_
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#cmakedefine XGBOOST_MM_PREFETCH_PRESENT
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#cmakedefine XGBOOST_BUILTIN_PREFETCH_PRESENT
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#endif // XGBOOST_BUILD_CONFIG_H_
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@ -218,4 +218,8 @@ using bst_omp_uint = dmlc::omp_uint; // NOLINT
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#endif
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#endif
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#endif
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#endif
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} // namespace xgboost
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} // namespace xgboost
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/* Always keep this #include at the bottom of xgboost/base.h */
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#include <xgboost/build_config.h>
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#endif // XGBOOST_BASE_H_
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#endif // XGBOOST_BASE_H_
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20
include/xgboost/build_config.h
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20
include/xgboost/build_config.h
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@ -0,0 +1,20 @@
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/*!
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* Copyright (c) 2018 by Contributors
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* \file build_config.h
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* \brief Fall-back logic for platform-specific feature detection.
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* \author Hyunsu Philip Cho
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*/
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#ifndef XGBOOST_BUILD_CONFIG_H_
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#define XGBOOST_BUILD_CONFIG_H_
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/* default logic for software pre-fetching */
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#if (defined(_MSC_VER) && (defined(_M_IX86) || defined(_M_AMD64))) || defined(__INTEL_COMPILER)
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// Enable _mm_prefetch for Intel compiler and MSVC+x86
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#define XGBOOST_MM_PREFETCH_PRESENT
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#define XGBOOST_BUILTIN_PREFETCH_PRESENT
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#elif defined(__GNUC__)
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// Enable __builtin_prefetch for GCC
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#define XGBOOST_BUILTIN_PREFETCH_PRESENT
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#endif
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#endif // XGBOOST_BUILD_CONFIG_H_
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@ -14,6 +14,15 @@
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#include "./hist_util.h"
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#include "./hist_util.h"
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#include "./quantile.h"
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#include "./quantile.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
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namespace xgboost {
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namespace xgboost {
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namespace common {
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namespace common {
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@ -399,56 +408,89 @@ void GHistBuilder::BuildHist(const std::vector<GradientPair>& gpair,
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const RowSetCollection::Elem row_indices,
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const RowSetCollection::Elem row_indices,
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const GHistIndexMatrix& gmat,
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const GHistIndexMatrix& gmat,
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GHistRow hist) {
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GHistRow hist) {
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data_.resize(nbins_ * nthread_, GHistEntry());
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const size_t nthread = static_cast<size_t>(this->nthread_);
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std::fill(data_.begin(), data_.end(), GHistEntry());
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data_.resize(nbins_ * nthread_);
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constexpr int kUnroll = 8; // loop unrolling factor
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const size_t* rid = row_indices.begin;
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const auto nthread = static_cast<bst_omp_uint>(this->nthread_);
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const size_t nrows = row_indices.Size();
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const size_t nrows = row_indices.end - row_indices.begin;
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const uint32_t* index = gmat.index.data();
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const size_t rest = nrows % kUnroll;
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const size_t* row_ptr = gmat.row_ptr.data();
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const float* pgh = reinterpret_cast<const float*>(gpair.data());
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#pragma omp parallel for num_threads(nthread) schedule(guided)
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double* hist_data = reinterpret_cast<double*>(hist.begin);
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for (bst_omp_uint i = 0; i < nrows - rest; i += kUnroll) {
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double* data = reinterpret_cast<double*>(data_.data());
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const bst_omp_uint tid = omp_get_thread_num();
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const size_t off = tid * nbins_;
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const size_t block_size = 512;
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size_t rid[kUnroll];
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size_t n_blocks = nrows/block_size;
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size_t ibegin[kUnroll];
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n_blocks += !!(nrows - n_blocks*block_size);
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size_t iend[kUnroll];
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GradientPair stat[kUnroll];
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const size_t nthread_to_process = std::min(nthread, n_blocks);
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for (int k = 0; k < kUnroll; ++k) {
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memset(thread_init_.data(), '\0', nthread_to_process*sizeof(size_t));
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rid[k] = row_indices.begin[i + k];
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const size_t cache_line_size = 64;
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const size_t prefetch_offset = 10;
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size_t no_prefetch_size = prefetch_offset + cache_line_size/sizeof(*rid);
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no_prefetch_size = no_prefetch_size > nrows ? nrows : no_prefetch_size;
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#pragma omp parallel for num_threads(nthread_to_process) schedule(guided)
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for (bst_omp_uint iblock = 0; iblock < n_blocks; iblock++) {
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dmlc::omp_uint tid = omp_get_thread_num();
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double* data_local_hist = ((nthread_to_process == 1) ? hist_data :
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reinterpret_cast<double*>(data_.data() + tid * nbins_));
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if (!thread_init_[tid]) {
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memset(data_local_hist, '\0', 2*nbins_*sizeof(double));
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thread_init_[tid] = true;
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}
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}
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for (int k = 0; k < kUnroll; ++k) {
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ibegin[k] = gmat.row_ptr[rid[k]];
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const size_t istart = iblock*block_size;
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iend[k] = gmat.row_ptr[rid[k] + 1];
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const size_t iend = (((iblock+1)*block_size > nrows) ? nrows : istart + block_size);
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}
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for (size_t i = istart; i < iend; ++i) {
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for (int k = 0; k < kUnroll; ++k) {
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const size_t icol_start = row_ptr[rid[i]];
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stat[k] = gpair[rid[k]];
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const size_t icol_end = row_ptr[rid[i]+1];
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}
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for (int k = 0; k < kUnroll; ++k) {
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if (i < nrows - no_prefetch_size) {
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for (size_t j = ibegin[k]; j < iend[k]; ++j) {
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PREFETCH_READ_T0(row_ptr + rid[i + prefetch_offset]);
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const uint32_t bin = gmat.index[j];
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PREFETCH_READ_T0(pgh + 2*rid[i + prefetch_offset]);
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data_[off + bin].Add(stat[k]);
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}
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for (size_t j = icol_start; j < icol_end; ++j) {
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const uint32_t idx_bin = 2*index[j];
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const size_t idx_gh = 2*rid[i];
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data_local_hist[idx_bin] += pgh[idx_gh];
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data_local_hist[idx_bin+1] += pgh[idx_gh+1];
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}
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}
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}
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}
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}
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}
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for (size_t i = nrows - rest; i < nrows; ++i) {
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const size_t rid = row_indices.begin[i];
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const size_t ibegin = gmat.row_ptr[rid];
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const size_t iend = gmat.row_ptr[rid + 1];
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const GradientPair stat = gpair[rid];
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for (size_t j = ibegin; j < iend; ++j) {
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const uint32_t bin = gmat.index[j];
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data_[bin].Add(stat);
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}
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}
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/* reduction */
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if (nthread_to_process > 1) {
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const uint32_t nbins = nbins_;
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const size_t size = (2*nbins_);
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#pragma omp parallel for num_threads(nthread) schedule(static)
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const size_t block_size = 1024;
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for (bst_omp_uint bin_id = 0; bin_id < bst_omp_uint(nbins); ++bin_id) {
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size_t n_blocks = size/block_size;
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for (bst_omp_uint tid = 0; tid < nthread; ++tid) {
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n_blocks += !!(size - n_blocks*block_size);
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hist.begin[bin_id].Add(data_[tid * nbins_ + bin_id]);
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size_t n_worked_bins = 0;
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for (size_t i = 0; i < nthread_to_process; ++i) {
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if (thread_init_[i]) {
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thread_init_[n_worked_bins++] = i;
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}
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}
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#pragma omp parallel for num_threads(std::min(nthread, n_blocks)) schedule(guided)
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for (bst_omp_uint iblock = 0; iblock < n_blocks; iblock++) {
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const size_t istart = iblock*block_size;
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const size_t iend = (((iblock+1)*block_size > size) ? size : istart + block_size);
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const size_t bin = 2*thread_init_[0]*nbins_;
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memcpy(hist_data + istart, (data + bin + istart), sizeof(double)*(iend - istart));
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for (size_t i_bin_part = 1; i_bin_part < n_worked_bins; ++i_bin_part) {
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const size_t bin = 2*thread_init_[i_bin_part]*nbins_;
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for (size_t i = istart; i < iend; i++) {
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hist_data[i] += data[bin + i];
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}
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}
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}
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}
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}
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}
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}
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}
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@ -238,6 +238,7 @@ class GHistBuilder {
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inline void Init(size_t nthread, uint32_t nbins) {
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inline void Init(size_t nthread, uint32_t nbins) {
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nthread_ = nthread;
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nthread_ = nthread;
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nbins_ = nbins;
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nbins_ = nbins;
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thread_init_.resize(nthread_);
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}
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}
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// construct a histogram via histogram aggregation
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// construct a histogram via histogram aggregation
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@ -259,6 +260,7 @@ class GHistBuilder {
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/*! \brief number of all bins over all features */
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/*! \brief number of all bins over all features */
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uint32_t nbins_;
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uint32_t nbins_;
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std::vector<GHistEntry> data_;
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std::vector<GHistEntry> data_;
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std::vector<size_t> thread_init_;
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};
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};
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