From 952c2aafc50cffbd8993c53bfa823e9bab35bb8e Mon Sep 17 00:00:00 2001 From: egor Date: Wed, 25 Dec 2019 02:03:29 +0300 Subject: [PATCH] Optimized BuildHist function --- src/common/hist_util.cc | 134 ++++++------- src/common/hist_util.h | 229 +++++++++++++++++++-- src/common/threading_utils.h | 19 +- src/tree/updater_quantile_hist.cc | 242 ++++++++++++++++------- src/tree/updater_quantile_hist.h | 44 +++-- tests/cpp/common/test_hist_util.cc | 117 +++++++++++ tests/cpp/common/test_threading_utils.cc | 4 +- tests/cpp/tree/test_quantile_hist.cc | 7 +- 8 files changed, 611 insertions(+), 185 deletions(-) diff --git a/src/common/hist_util.cc b/src/common/hist_util.cc index e4747ea749b4..5dc9049c4ff5 100644 --- a/src/common/hist_util.cc +++ b/src/common/hist_util.cc @@ -659,13 +659,59 @@ void GHistIndexBlockMatrix::Init(const GHistIndexMatrix& gmat, } } +/*! + * \brief fill a histogram by zeroes + */ +void InitilizeHistByZeroes(GHistRow hist, size_t begin, size_t end) { + memset(hist.data() + begin, '\0', (end-begin)*sizeof(tree::GradStats)); +} + +/*! + * \brief Increment hist as dst += add in range [begin, end) + */ +void IncrementHist(GHistRow dst, const GHistRow add, size_t begin, size_t end) { + using FPType = decltype(tree::GradStats::sum_grad); + FPType* pdst = reinterpret_cast(dst.data()); + const FPType* padd = reinterpret_cast(add.data()); + + for (size_t i = 2 * begin; i < 2 * end; ++i) { + pdst[i] += padd[i]; + } +} + +/*! + * \brief Copy hist from src to dst in range [begin, end) + */ +void CopyHist(GHistRow dst, const GHistRow src, size_t begin, size_t end) { + using FPType = decltype(tree::GradStats::sum_grad); + FPType* pdst = reinterpret_cast(dst.data()); + const FPType* psrc = reinterpret_cast(src.data()); + + for (size_t i = 2 * begin; i < 2 * end; ++i) { + pdst[i] = psrc[i]; + } +} + +/*! + * \brief Compute Subtraction: dst = src1 - src2 in range [begin, end) + */ +void SubtractionHist(GHistRow dst, const GHistRow src1, const GHistRow src2, + size_t begin, size_t end) { + using FPType = decltype(tree::GradStats::sum_grad); + FPType* pdst = reinterpret_cast(dst.data()); + const FPType* psrc1 = reinterpret_cast(src1.data()); + const FPType* psrc2 = reinterpret_cast(src2.data()); + + for (size_t i = 2 * begin; i < 2 * end; ++i) { + pdst[i] = psrc1[i] - psrc2[i]; + } +} + + void GHistBuilder::BuildHist(const std::vector& gpair, const RowSetCollection::Elem row_indices, const GHistIndexMatrix& gmat, GHistRow hist) { - const size_t nthread = static_cast(this->nthread_); - data_.resize(nbins_ * nthread_); - const size_t* rid = row_indices.begin; const size_t nrows = row_indices.Size(); const uint32_t* index = gmat.index.data(); @@ -673,79 +719,27 @@ void GHistBuilder::BuildHist(const std::vector& gpair, const float* pgh = reinterpret_cast(gpair.data()); double* hist_data = reinterpret_cast(hist.data()); - double* data = reinterpret_cast(data_.data()); - - const size_t block_size = 512; - size_t n_blocks = nrows/block_size; - n_blocks += !!(nrows - n_blocks*block_size); - - const size_t nthread_to_process = std::min(nthread, n_blocks); - memset(thread_init_.data(), '\0', nthread_to_process*sizeof(size_t)); const size_t cache_line_size = 64; const size_t prefetch_offset = 10; size_t no_prefetch_size = prefetch_offset + cache_line_size/sizeof(*rid); no_prefetch_size = no_prefetch_size > nrows ? nrows : no_prefetch_size; -#pragma omp parallel for num_threads(nthread_to_process) schedule(guided) - for (bst_omp_uint iblock = 0; iblock < n_blocks; iblock++) { - dmlc::omp_uint tid = omp_get_thread_num(); - double* data_local_hist = ((nthread_to_process == 1) ? hist_data : - reinterpret_cast(data_.data() + tid * nbins_)); + for (size_t i = 0; i < nrows; ++i) { + const size_t icol_start = row_ptr[rid[i]]; + const size_t icol_end = row_ptr[rid[i]+1]; - if (!thread_init_[tid]) { - memset(data_local_hist, '\0', 2*nbins_*sizeof(double)); - thread_init_[tid] = true; + if (i < nrows - no_prefetch_size) { + PREFETCH_READ_T0(row_ptr + rid[i + prefetch_offset]); + PREFETCH_READ_T0(pgh + 2*rid[i + prefetch_offset]); } - const size_t istart = iblock*block_size; - const size_t iend = (((iblock+1)*block_size > nrows) ? nrows : istart + block_size); - for (size_t i = istart; i < iend; ++i) { - const size_t icol_start = row_ptr[rid[i]]; - const size_t icol_end = row_ptr[rid[i]+1]; - - if (i < nrows - no_prefetch_size) { - PREFETCH_READ_T0(row_ptr + rid[i + prefetch_offset]); - PREFETCH_READ_T0(pgh + 2*rid[i + prefetch_offset]); - } + for (size_t j = icol_start; j < icol_end; ++j) { + const uint32_t idx_bin = 2*index[j]; + const size_t idx_gh = 2*rid[i]; - for (size_t j = icol_start; j < icol_end; ++j) { - const uint32_t idx_bin = 2*index[j]; - const size_t idx_gh = 2*rid[i]; - - data_local_hist[idx_bin] += pgh[idx_gh]; - data_local_hist[idx_bin+1] += pgh[idx_gh+1]; - } - } - } - - if (nthread_to_process > 1) { - const size_t size = (2*nbins_); - const size_t block_size = 1024; - size_t n_blocks = size/block_size; - n_blocks += !!(size - n_blocks*block_size); - - size_t n_worked_bins = 0; - for (size_t i = 0; i < nthread_to_process; ++i) { - if (thread_init_[i]) { - thread_init_[n_worked_bins++] = i; - } - } - -#pragma omp parallel for num_threads(std::min(nthread, n_blocks)) schedule(guided) - for (bst_omp_uint iblock = 0; iblock < n_blocks; iblock++) { - const size_t istart = iblock * block_size; - const size_t iend = (((iblock + 1) * block_size > size) ? size : istart + block_size); - - const size_t bin = 2 * thread_init_[0] * nbins_; - memcpy(hist_data + istart, (data + bin + istart), sizeof(double) * (iend - istart)); - - for (size_t i_bin_part = 1; i_bin_part < n_worked_bins; ++i_bin_part) { - const size_t bin = 2 * thread_init_[i_bin_part] * nbins_; - for (size_t i = istart; i < iend; i++) { - hist_data[i] += data[bin + i]; - } - } + hist_data[idx_bin] += pgh[idx_gh]; + hist_data[idx_bin+1] += pgh[idx_gh+1]; } } } @@ -801,10 +795,6 @@ void GHistBuilder::BuildBlockHist(const std::vector& gpair, } void GHistBuilder::SubtractionTrick(GHistRow self, GHistRow sibling, GHistRow parent) { - tree::GradStats* p_self = self.data(); - tree::GradStats* p_sibling = sibling.data(); - tree::GradStats* p_parent = parent.data(); - const size_t size = self.size(); CHECK_EQ(sibling.size(), size); CHECK_EQ(parent.size(), size); @@ -816,9 +806,7 @@ void GHistBuilder::SubtractionTrick(GHistRow self, GHistRow sibling, GHistRow pa for (omp_ulong iblock = 0; iblock < n_blocks; ++iblock) { const size_t ibegin = iblock*block_size; const size_t iend = (((iblock+1)*block_size > size) ? size : ibegin + block_size); - for (bst_omp_uint bin_id = ibegin; bin_id < iend; bin_id++) { - p_self[bin_id].SetSubstract(p_parent[bin_id], p_sibling[bin_id]); - } + SubtractionHist(self, parent, sibling, ibegin, iend); } } diff --git a/src/common/hist_util.h b/src/common/hist_util.h index 2edafcbe1b1b..115bae32c268 100644 --- a/src/common/hist_util.h +++ b/src/common/hist_util.h @@ -14,8 +14,10 @@ #include #include #include +#include #include "row_set.h" +#include "threading_utils.h" #include "../tree/param.h" #include "./quantile.h" #include "./timer.h" @@ -254,7 +256,7 @@ class DenseCuts : public CutsBuilder { // FIXME(trivialfis): Merge this into generic cut builder. /*! \brief Builds the cut matrix on the GPU. - * + * * \return The row stride across the entire dataset. */ size_t DeviceSketch(int device, @@ -343,13 +345,34 @@ class GHistIndexBlockMatrix { }; /*! - * \brief histogram of graident statistics for a single node. - * Consists of multiple GradStats, each entry showing total graident statistics + * \brief histogram of gradient statistics for a single node. + * Consists of multiple GradStats, each entry showing total gradient statistics * for that particular bin * Uses global bin id so as to represent all features simultaneously */ using GHistRow = Span; +/*! + * \brief fill a histogram by zeros + */ +void InitilizeHistByZeroes(GHistRow hist, size_t begin, size_t end); + +/*! + * \brief Increment hist as dst += add in range [begin, end) + */ +void IncrementHist(GHistRow dst, const GHistRow add, size_t begin, size_t end); + +/*! + * \brief Copy hist from src to dst in range [begin, end) + */ +void CopyHist(GHistRow dst, const GHistRow src, size_t begin, size_t end); + +/*! + * \brief Compute Subtraction: dst = src1 - src2 in range [begin, end) + */ +void SubtractionHist(GHistRow dst, const GHistRow src1, const GHistRow src2, + size_t begin, size_t end); + /*! * \brief histogram of gradient statistics for multiple nodes */ @@ -372,9 +395,13 @@ class HistCollection { // initialize histogram collection void Init(uint32_t nbins) { - nbins_ = nbins; + if (nbins_ != nbins) { + nbins_ = nbins; + // quite expensive operation, so let's do this only once + data_.clear(); + } row_ptr_.clear(); - data_.clear(); + n_nodes_added_ = 0; } // create an empty histogram for i-th node @@ -385,20 +412,201 @@ class HistCollection { } CHECK_EQ(row_ptr_[nid], kMax); - row_ptr_[nid] = data_.size(); - data_.resize(data_.size() + nbins_); + if (data_.size() < nbins_ * (nid + 1)) { + data_.resize(nbins_ * (nid + 1)); + } + + row_ptr_[nid] = nbins_ * n_nodes_added_; + n_nodes_added_++; } private: /*! \brief number of all bins over all features */ - uint32_t nbins_; + uint32_t nbins_ = 0; + /*! \brief amount of active nodes in hist collection */ + uint32_t n_nodes_added_ = 0; std::vector data_; - /*! \brief row_ptr_[nid] locates bin for historgram of node nid */ + /*! \brief row_ptr_[nid] locates bin for histogram of node nid */ std::vector row_ptr_; }; +/*! + * \brief Stores temporary histograms to compute them in parallel + * Supports processing multiple tree-nodes for nested parallelism + * Able to reduce histograms across threads in efficient way + */ +class ParallelGHistBuilder { + public: + void Init(size_t nbins) { + if (nbins != nbins_) { + hist_buffer_.Init(nbins); + nbins_ = nbins; + } + } + + // Add new elements if needed, mark all hists as unused + // targeted_hists - already allocated hists which should contain final results after Reduce() call + void Reset(size_t nthreads, size_t nodes, const BlockedSpace2d& space, + const std::vector& targeted_hists) { + hist_buffer_.Init(nbins_); + tid_nid_to_hist_.clear(); + hist_memory_.clear(); + threads_to_nids_map_.clear(); + + targeted_hists_ = targeted_hists; + + CHECK_EQ(nodes, targeted_hists.size()); + + nodes_ = nodes; + nthreads_ = nthreads; + + MatchThreadsToNodes(space); + AllocateAdditionalHistograms(); + MatchNodeNidPairToHist(); + + hist_was_used_.resize(nthreads * nodes_); + std::fill(hist_was_used_.begin(), hist_was_used_.end(), static_cast(false)); + } + + // Get specified hist, initialize hist by zeros if it wasn't used before + GHistRow GetInitializedHist(size_t tid, size_t nid) { + CHECK_LT(nid, nodes_); + CHECK_LT(tid, nthreads_); + + size_t idx = tid_nid_to_hist_.at({tid, nid}); + GHistRow hist = hist_memory_[idx]; + + if (!hist_was_used_[tid * nodes_ + nid]) { + InitilizeHistByZeroes(hist, 0, hist.size()); + hist_was_used_[tid * nodes_ + nid] = static_cast(true); + } + + return hist; + } + + // Reduce following bins (begin, end] for nid-node in dst across threads + void ReduceHist(size_t nid, size_t begin, size_t end) { + CHECK_GT(end, begin); + CHECK_LT(nid, nodes_); + + GHistRow dst = targeted_hists_[nid]; + + bool is_updated = false; + for (size_t tid = 0; tid < nthreads_; ++tid) { + if (hist_was_used_[tid * nodes_ + nid]) { + is_updated = true; + const size_t idx = tid_nid_to_hist_.at({tid, nid}); + GHistRow src = hist_memory_[idx]; + + if (dst.data() != src.data()) { + IncrementHist(dst, src, begin, end); + } + } + } + if (!is_updated) { + // In distributed mode - some tree nodes can be empty on local machines, + // So we need just set local hist by zeros in this case + InitilizeHistByZeroes(dst, begin, end); + } + } + + protected: + void MatchThreadsToNodes(const BlockedSpace2d& space) { + const size_t space_size = space.Size(); + const size_t chunck_size = space_size / nthreads_ + !!(space_size % nthreads_); + + threads_to_nids_map_.resize(nthreads_ * nodes_, false); + + for (size_t tid = 0; tid < nthreads_; ++tid) { + size_t begin = chunck_size * tid; + size_t end = std::min(begin + chunck_size, space_size); + + if (begin < space_size) { + size_t nid_begin = space.GetFirstDimension(begin); + size_t nid_end = space.GetFirstDimension(end-1); + + for (size_t nid = nid_begin; nid <= nid_end; ++nid) { + // true - means thread 'tid' will work to compute partial hist for node 'nid' + threads_to_nids_map_[tid * nodes_ + nid] = true; + } + } + } + } + + void AllocateAdditionalHistograms() { + size_t hist_allocated_additionally = 0; + + for (size_t nid = 0; nid < nodes_; ++nid) { + int nthreads_for_nid = 0; + + for (size_t tid = 0; tid < nthreads_; ++tid) { + if (threads_to_nids_map_[tid * nodes_ + nid]) { + nthreads_for_nid++; + } + } + + // In distributed mode - some tree nodes can be empty on local machines, + // set nthreads_for_nid to 0 in this case. + // In another case - allocate additional (nthreads_for_nid - 1) histograms, + // because one is already allocated externally (will store final result for the node). + hist_allocated_additionally += std::max(0, nthreads_for_nid - 1); + } + + for (size_t i = 0; i < hist_allocated_additionally; ++i) { + hist_buffer_.AddHistRow(i); + } + } + + void MatchNodeNidPairToHist() { + size_t hist_total = 0; + size_t hist_allocated_additionally = 0; + + for (size_t nid = 0; nid < nodes_; ++nid) { + bool first_hist = true; + for (size_t tid = 0; tid < nthreads_; ++tid) { + if (threads_to_nids_map_[tid * nodes_ + nid]) { + if (first_hist) { + hist_memory_.push_back(targeted_hists_[nid]); + first_hist = false; + } else { + hist_memory_.push_back(hist_buffer_[hist_allocated_additionally]); + hist_allocated_additionally++; + } + // map pair {tid, nid} to index of allocated histogram from hist_memory_ + tid_nid_to_hist_[{tid, nid}] = hist_total++; + CHECK_EQ(hist_total, hist_memory_.size()); + } + } + } + } + + /*! \brief number of bins in each histogram */ + size_t nbins_ = 0; + /*! \brief number of threads for parallel computation */ + size_t nthreads_ = 0; + /*! \brief number of nodes which will be processed in parallel */ + size_t nodes_ = 0; + /*! \brief Buffer for additional histograms for Parallel processing */ + HistCollection hist_buffer_; + /*! + * \brief Marks which hists were used, it means that they should be merged. + * Contains only {true or false} values + * but 'int' is used instead of 'bool', because std::vector isn't thread safe + */ + std::vector hist_was_used_; + + /*! \brief Buffer for additional histograms for Parallel processing */ + std::vector threads_to_nids_map_; + /*! \brief Contains histograms for final results */ + std::vector targeted_hists_; + /*! \brief Allocated memory for histograms used for construction */ + std::vector hist_memory_; + /*! \brief map pair {tid, nid} to index of allocated histogram from hist_memory_ */ + std::map, size_t> tid_nid_to_hist_; +}; + /*! * \brief builder for histograms of gradient statistics */ @@ -408,7 +616,6 @@ class GHistBuilder { inline void Init(size_t nthread, uint32_t nbins) { nthread_ = nthread; nbins_ = nbins; - thread_init_.resize(nthread_); } // construct a histogram via histogram aggregation @@ -433,8 +640,6 @@ class GHistBuilder { size_t nthread_; /*! \brief number of all bins over all features */ uint32_t nbins_; - std::vector thread_init_; - std::vector data_; }; diff --git a/src/common/threading_utils.h b/src/common/threading_utils.h index 34e363c00244..ff7c4667636c 100755 --- a/src/common/threading_utils.h +++ b/src/common/threading_utils.h @@ -108,12 +108,19 @@ class BlockedSpace2d { // Wrapper to implement nested parallelism with simple omp parallel for template -void ParallelFor2d(const BlockedSpace2d& space, Func func) { - const int num_blocks_in_space = static_cast(space.Size()); - - #pragma omp parallel for - for (auto i = 0; i < num_blocks_in_space; i++) { - func(space.GetFirstDimension(i), space.GetRange(i)); +void ParallelFor2d(const BlockedSpace2d& space, const int nthreads, Func func) { + const size_t num_blocks_in_space = space.Size(); + + #pragma omp parallel num_threads(nthreads) + { + size_t tid = omp_get_thread_num(); + size_t chunck_size = num_blocks_in_space / nthreads + !!(num_blocks_in_space % nthreads); + + size_t begin = chunck_size * tid; + size_t end = std::min(begin + chunck_size, num_blocks_in_space); + for (auto i = begin; i < end; i++) { + func(space.GetFirstDimension(i), space.GetRange(i)); + } } } diff --git a/src/tree/updater_quantile_hist.cc b/src/tree/updater_quantile_hist.cc index b28c2f9707da..d1d206587c0b 100644 --- a/src/tree/updater_quantile_hist.cc +++ b/src/tree/updater_quantile_hist.cc @@ -2,7 +2,7 @@ * Copyright 2017-2018 by Contributors * \file updater_quantile_hist.cc * \brief use quantized feature values to construct a tree - * \author Philip Cho, Tianqi Checn + * \author Philip Cho, Tianqi Checn, Egor Smirnov */ #include #include @@ -44,7 +44,7 @@ void QuantileHistMaker::Configure(const Args& args) { pruner_->Configure(args); param_.UpdateAllowUnknown(args); - // initialise the split evaluator + // initialize the split evaluator if (!spliteval_) { spliteval_.reset(SplitEvaluator::Create(param_.split_evaluator)); } @@ -100,66 +100,121 @@ void QuantileHistMaker::Builder::SyncHistograms( int sync_count, RegTree *p_tree) { builder_monitor_.Start("SyncHistograms"); - this->histred_.Allreduce(hist_[starting_index].data(), hist_builder_.GetNumBins() * sync_count); - // use Subtraction Trick - for (auto const& node_pair : nodes_for_subtraction_trick_) { - hist_.AddHistRow(node_pair.first); - SubtractionTrick(hist_[node_pair.first], hist_[node_pair.second], - hist_[(*p_tree)[node_pair.first].Parent()]); + + const bool isDistributed = rabit::IsDistributed(); + + const size_t nbins = hist_builder_.GetNumBins(); + common::BlockedSpace2d space(nodes_for_explicit_hist_build_.size(), [&](size_t node) { + return nbins; + }, 1024); + + common::ParallelFor2d(space, this->nthread_, [&](size_t node, common::Range1d r) { + const auto entry = nodes_for_explicit_hist_build_[node]; + auto this_hist = hist_[entry.nid]; + // Merging histograms from each thread into once + hist_buffer_.ReduceHist(node, r.begin(), r.end()); + + if (!(*p_tree)[entry.nid].IsRoot() && entry.sibling_nid > -1 && !isDistributed) { + auto parent_hist = hist_[(*p_tree)[entry.nid].Parent()]; + auto sibling_hist = hist_[entry.sibling_nid]; + + SubtractionHist(sibling_hist, parent_hist, this_hist, r.begin(), r.end()); + } + }); + + if (isDistributed) { + this->histred_.Allreduce(hist_[starting_index].data(), hist_builder_.GetNumBins() * sync_count); + // use Subtraction Trick + for (auto const& node : nodes_for_subtraction_trick_) { + SubtractionTrick(hist_[node.nid], hist_[node.sibling_nid], + hist_[(*p_tree)[node.nid].Parent()]); + } } + builder_monitor_.Stop("SyncHistograms"); } +void QuantileHistMaker::Builder::BuildHistogramsLossGuide( + ExpandEntry entry, + const GHistIndexMatrix &gmat, + const GHistIndexBlockMatrix &gmatb, + RegTree *p_tree, + const std::vector &gpair_h) { + nodes_for_explicit_hist_build_.clear(); + nodes_for_subtraction_trick_.clear(); + nodes_for_explicit_hist_build_.push_back(entry); + + if (entry.sibling_nid > -1) { + nodes_for_subtraction_trick_.emplace_back(entry.sibling_nid, entry.nid, + p_tree->GetDepth(entry.sibling_nid), 0.0f, 0); + } + + int starting_index = std::numeric_limits::max(); + int sync_count = 0; + + AddHistRows(&starting_index, &sync_count); + BuildLocalHistograms(gmat, gmatb, p_tree, gpair_h); + SyncHistograms(starting_index, sync_count, p_tree); +} + + +void QuantileHistMaker::Builder::AddHistRows(int *starting_index, int *sync_count) { + builder_monitor_.Start("AddHistRows"); + + for (auto const& entry : nodes_for_explicit_hist_build_) { + int nid = entry.nid; + hist_.AddHistRow(nid); + (*starting_index) = std::min(nid, (*starting_index)); + } + (*sync_count) = nodes_for_explicit_hist_build_.size(); + + for (auto const& node : nodes_for_subtraction_trick_) { + hist_.AddHistRow(node.nid); + } + + builder_monitor_.Stop("AddHistRows"); +} + + void QuantileHistMaker::Builder::BuildLocalHistograms( - int *starting_index, - int *sync_count, const GHistIndexMatrix &gmat, const GHistIndexBlockMatrix &gmatb, RegTree *p_tree, const std::vector &gpair_h) { builder_monitor_.Start("BuildLocalHistograms"); - for (auto const& entry : qexpand_depth_wise_) { - int nid = entry.nid; - RegTree::Node &node = (*p_tree)[nid]; - if (rabit::IsDistributed()) { - if (node.IsRoot() || node.IsLeftChild()) { - hist_.AddHistRow(nid); - // in distributed setting, we always calculate from left child or root node - BuildHist(gpair_h, row_set_collection_[nid], gmat, gmatb, hist_[nid], false); - if (!node.IsRoot()) { - nodes_for_subtraction_trick_[(*p_tree)[node.Parent()].RightChild()] = nid; - } - (*sync_count)++; - (*starting_index) = std::min((*starting_index), nid); - } - } else { - if (!node.IsRoot() && node.IsLeftChild() && - (row_set_collection_[nid].Size() < - row_set_collection_[(*p_tree)[node.Parent()].RightChild()].Size())) { - hist_.AddHistRow(nid); - BuildHist(gpair_h, row_set_collection_[nid], gmat, gmatb, hist_[nid], false); - nodes_for_subtraction_trick_[(*p_tree)[node.Parent()].RightChild()] = nid; - (*sync_count)++; - (*starting_index) = std::min((*starting_index), nid); - } else if (!node.IsRoot() && !node.IsLeftChild() && - (row_set_collection_[nid].Size() <= - row_set_collection_[(*p_tree)[node.Parent()].LeftChild()].Size())) { - hist_.AddHistRow(nid); - BuildHist(gpair_h, row_set_collection_[nid], gmat, gmatb, hist_[nid], false); - nodes_for_subtraction_trick_[(*p_tree)[node.Parent()].LeftChild()] = nid; - (*sync_count)++; - (*starting_index) = std::min((*starting_index), nid); - } else if (node.IsRoot()) { - hist_.AddHistRow(nid); - BuildHist(gpair_h, row_set_collection_[nid], gmat, gmatb, hist_[nid], false); - (*sync_count)++; - (*starting_index) = std::min((*starting_index), nid); - } - } + + const size_t n_nodes = nodes_for_explicit_hist_build_.size(); + + // create space of size (# rows in each node) + common::BlockedSpace2d space(n_nodes, [&](size_t node) { + const int32_t nid = nodes_for_explicit_hist_build_[node].nid; + return row_set_collection_[nid].Size(); + }, 256); + + std::vector target_hists(n_nodes); + for (size_t i = 0; i < n_nodes; ++i) { + const int32_t nid = nodes_for_explicit_hist_build_[i].nid; + target_hists[i] = hist_[nid]; } + + hist_buffer_.Reset(this->nthread_, n_nodes, space, target_hists); + + // Parallel processing by nodes and data in each node + common::ParallelFor2d(space, this->nthread_, [&](size_t nid_in_set, common::Range1d r) { + const auto tid = static_cast(omp_get_thread_num()); + const int32_t nid = nodes_for_explicit_hist_build_[nid_in_set].nid; + + auto start_of_row_set = row_set_collection_[nid].begin; + auto rid_set = RowSetCollection::Elem(start_of_row_set + r.begin(), + start_of_row_set + r.end(), + nid); + BuildHist(gpair_h, rid_set, gmat, gmatb, hist_buffer_.GetInitializedHist(tid, nid_in_set)); + }); + builder_monitor_.Stop("BuildLocalHistograms"); } + void QuantileHistMaker::Builder::BuildNodeStats( const GHistIndexMatrix &gmat, DMatrix *p_fmat, @@ -193,7 +248,7 @@ void QuantileHistMaker::Builder::EvaluateSplits( int depth, unsigned *timestamp, std::vector *temp_qexpand_depth) { - this->EvaluateSplit(qexpand_depth_wise_, gmat, hist_, *p_fmat, *p_tree); + EvaluateSplit(qexpand_depth_wise_, gmat, hist_, *p_fmat, *p_tree); for (auto const& entry : qexpand_depth_wise_) { int nid = entry.nid; @@ -206,9 +261,9 @@ void QuantileHistMaker::Builder::EvaluateSplits( this->ApplySplit(nid, gmat, column_matrix, hist_, *p_fmat, p_tree); int left_id = (*p_tree)[nid].LeftChild(); int right_id = (*p_tree)[nid].RightChild(); - temp_qexpand_depth->push_back(ExpandEntry(left_id, + temp_qexpand_depth->push_back(ExpandEntry(left_id, right_id, p_tree->GetDepth(left_id), 0.0, (*timestamp)++)); - temp_qexpand_depth->push_back(ExpandEntry(right_id, + temp_qexpand_depth->push_back(ExpandEntry(right_id, left_id, p_tree->GetDepth(right_id), 0.0, (*timestamp)++)); // - 1 parent + 2 new children (*num_leaves)++; @@ -216,6 +271,43 @@ void QuantileHistMaker::Builder::EvaluateSplits( } } +// Split nodes to 2 sets depending on amount of rows in each node +// Histograms for small nodes will be built explicitly +// Histograms for big nodes will be built by 'Subtraction Trick' +// Exception: in distributed setting, we always build the histogram for the left child node +// and use 'Subtraction Trick' to built the histogram for the right child node. +// This ensures that the workers operate on the same set of tree nodes. +void QuantileHistMaker::Builder::SplitSiblings(const std::vector& nodes, + std::vector* small_siblings, + std::vector* big_siblings, + RegTree *p_tree) { + for (auto const& entry : nodes) { + int nid = entry.nid; + RegTree::Node &node = (*p_tree)[nid]; + if (rabit::IsDistributed()) { + if (node.IsRoot() || node.IsLeftChild()) { + small_siblings->push_back(entry); + } else { + big_siblings->push_back(entry); + } + } else { + if (!node.IsRoot() && node.IsLeftChild() && + (row_set_collection_[nid].Size() < + row_set_collection_[(*p_tree)[node.Parent()].RightChild()].Size())) { + small_siblings->push_back(entry); + } else if (!node.IsRoot() && !node.IsLeftChild() && + (row_set_collection_[nid].Size() <= + row_set_collection_[(*p_tree)[node.Parent()].LeftChild()].Size())) { + small_siblings->push_back(entry); + } else if (node.IsRoot()) { + small_siblings->push_back(entry); + } else { + big_siblings->push_back(entry); + } + } + } +} + void QuantileHistMaker::Builder::ExpandWithDepthWise( const GHistIndexMatrix &gmat, const GHistIndexBlockMatrix &gmatb, @@ -227,21 +319,28 @@ void QuantileHistMaker::Builder::ExpandWithDepthWise( int num_leaves = 0; // in depth_wise growing, we feed loss_chg with 0.0 since it is not used anyway - qexpand_depth_wise_.emplace_back(ExpandEntry(ExpandEntry::kRootNid, + qexpand_depth_wise_.emplace_back(ExpandEntry(ExpandEntry::kRootNid, ExpandEntry::kEmptyNid, p_tree->GetDepth(ExpandEntry::kRootNid), 0.0, timestamp++)); ++num_leaves; for (int depth = 0; depth < param_.max_depth + 1; depth++) { int starting_index = std::numeric_limits::max(); int sync_count = 0; std::vector temp_qexpand_depth; - BuildLocalHistograms(&starting_index, &sync_count, gmat, gmatb, p_tree, gpair_h); + + SplitSiblings(qexpand_depth_wise_, &nodes_for_explicit_hist_build_, + &nodes_for_subtraction_trick_, p_tree); + AddHistRows(&starting_index, &sync_count); + + BuildLocalHistograms(gmat, gmatb, p_tree, gpair_h); SyncHistograms(starting_index, sync_count, p_tree); + BuildNodeStats(gmat, p_fmat, p_tree, gpair_h); EvaluateSplits(gmat, column_matrix, p_fmat, p_tree, &num_leaves, depth, ×tamp, &temp_qexpand_depth); // clean up qexpand_depth_wise_.clear(); nodes_for_subtraction_trick_.clear(); + nodes_for_explicit_hist_build_.clear(); if (temp_qexpand_depth.empty()) { break; } else { @@ -262,14 +361,12 @@ void QuantileHistMaker::Builder::ExpandWithLossGuide( unsigned timestamp = 0; int num_leaves = 0; - hist_.AddHistRow(ExpandEntry::kRootNid); - BuildHist(gpair_h, row_set_collection_[ExpandEntry::kRootNid], gmat, gmatb, - hist_[ExpandEntry::kRootNid], true); + ExpandEntry node(ExpandEntry::kRootNid, ExpandEntry::kEmptyNid, + p_tree->GetDepth(0), 0.0f, timestamp++); + BuildHistogramsLossGuide(node, gmat, gmatb, p_tree, gpair_h); this->InitNewNode(ExpandEntry::kRootNid, gmat, gpair_h, *p_fmat, *p_tree); - ExpandEntry node(ExpandEntry::kRootNid, p_tree->GetDepth(ExpandEntry::kRootNid), - snode_[ExpandEntry::kRootNid].best.loss_chg, timestamp++); this->EvaluateSplit({node}, gmat, hist_, *p_fmat, *p_tree); node.loss_chg = snode_[ExpandEntry::kRootNid].best.loss_chg; @@ -289,20 +386,20 @@ void QuantileHistMaker::Builder::ExpandWithLossGuide( const int cleft = (*p_tree)[nid].LeftChild(); const int cright = (*p_tree)[nid].RightChild(); - hist_.AddHistRow(cleft); - hist_.AddHistRow(cright); + + ExpandEntry left_node(cleft, cright, p_tree->GetDepth(cleft), + 0.0f, timestamp++); + ExpandEntry right_node(cright, cleft, p_tree->GetDepth(cright), + 0.0f, timestamp++); if (rabit::IsDistributed()) { // in distributed mode, we need to keep consistent across workers - BuildHist(gpair_h, row_set_collection_[cleft], gmat, gmatb, hist_[cleft], true); - SubtractionTrick(hist_[cright], hist_[cleft], hist_[nid]); + BuildHistogramsLossGuide(left_node, gmat, gmatb, p_tree, gpair_h); } else { if (row_set_collection_[cleft].Size() < row_set_collection_[cright].Size()) { - BuildHist(gpair_h, row_set_collection_[cleft], gmat, gmatb, hist_[cleft], true); - SubtractionTrick(hist_[cright], hist_[cleft], hist_[nid]); + BuildHistogramsLossGuide(left_node, gmat, gmatb, p_tree, gpair_h); } else { - BuildHist(gpair_h, row_set_collection_[cright], gmat, gmatb, hist_[cright], true); - SubtractionTrick(hist_[cleft], hist_[cright], hist_[nid]); + BuildHistogramsLossGuide(right_node, gmat, gmatb, p_tree, gpair_h); } } @@ -313,11 +410,6 @@ void QuantileHistMaker::Builder::ExpandWithLossGuide( snode_[cleft].weight, snode_[cright].weight); interaction_constraints_.Split(nid, featureid, cleft, cright); - ExpandEntry left_node(cleft, p_tree->GetDepth(cleft), - snode_[cleft].best.loss_chg, timestamp++); - ExpandEntry right_node(cright, p_tree->GetDepth(cright), - snode_[cright].best.loss_chg, timestamp++); - this->EvaluateSplit({left_node, right_node}, gmat, hist_, *p_fmat, *p_tree); left_node.loss_chg = snode_[cleft].best.loss_chg; right_node.loss_chg = snode_[cright].best.loss_chg; @@ -427,6 +519,7 @@ void QuantileHistMaker::Builder::InitData(const GHistIndexMatrix& gmat, // initialize histogram collection uint32_t nbins = gmat.cut.Ptrs().back(); hist_.Init(nbins); + hist_buffer_.Init(nbins); // initialize histogram builder #pragma omp parallel @@ -586,7 +679,7 @@ void QuantileHistMaker::Builder::EvaluateSplit(const std::vector& n builder_monitor_.Start("EvaluateSplit"); const size_t n_nodes_in_set = nodes_set.size(); - const auto nthread = static_cast(this->nthread_); + const size_t nthread = std::max(1, this->nthread_); using FeatureSetType = std::shared_ptr>; std::vector features_sets(n_nodes_in_set); @@ -604,12 +697,13 @@ void QuantileHistMaker::Builder::EvaluateSplit(const std::vector& n // Create 2D space (# of nodes to process x # of features to process) // to process them in parallel + const size_t grain_size = std::max(1, features_sets[0]->Size() / nthread); common::BlockedSpace2d space(n_nodes_in_set, [&](size_t nid_in_set) { return features_sets[nid_in_set]->Size(); - }, 1); + }, grain_size); // Start parallel enumeration for all tree nodes in the set and all features - common::ParallelFor2d(space, [&](size_t nid_in_set, common::Range1d r) { + common::ParallelFor2d(space, this->nthread_, [&](size_t nid_in_set, common::Range1d r) { const int32_t nid = nodes_set[nid_in_set].nid; const auto tid = static_cast(omp_get_thread_num()); GHistRow node_hist = hist[nid]; diff --git a/src/tree/updater_quantile_hist.h b/src/tree/updater_quantile_hist.h index 3e3ab9a745f8..18dd4ef1baa7 100644 --- a/src/tree/updater_quantile_hist.h +++ b/src/tree/updater_quantile_hist.h @@ -2,7 +2,7 @@ * Copyright 2017-2018 by Contributors * \file updater_quantile_hist.h * \brief use quantized feature values to construct a tree - * \author Philip Cho, Tianqi Chen + * \author Philip Cho, Tianqi Chen, Egor Smirnov */ #ifndef XGBOOST_TREE_UPDATER_QUANTILE_HIST_H_ #define XGBOOST_TREE_UPDATER_QUANTILE_HIST_H_ @@ -157,18 +157,12 @@ class QuantileHistMaker: public TreeUpdater { const RowSetCollection::Elem row_indices, const GHistIndexMatrix& gmat, const GHistIndexBlockMatrix& gmatb, - GHistRow hist, - bool sync_hist) { - builder_monitor_.Start("BuildHist"); + GHistRow hist) { if (param_.enable_feature_grouping > 0) { hist_builder_.BuildBlockHist(gpair, row_indices, gmatb, hist); } else { hist_builder_.BuildHist(gpair, row_indices, gmat, hist); } - if (sync_hist) { - this->histred_.Allreduce(hist.data(), hist_builder_.GetNumBins()); - } - builder_monitor_.Stop("BuildHist"); } inline void SubtractionTrick(GHistRow self, GHistRow sibling, GHistRow parent) { @@ -183,13 +177,15 @@ class QuantileHistMaker: public TreeUpdater { protected: /* tree growing policies */ struct ExpandEntry { - static const int kRootNid = 0; + static const int kRootNid = 0; + static const int kEmptyNid = -1; int nid; + int sibling_nid; int depth; bst_float loss_chg; unsigned timestamp; - ExpandEntry(int nid, int depth, bst_float loss_chg, unsigned tstmp) - : nid(nid), depth(depth), loss_chg(loss_chg), timestamp(tstmp) {} + ExpandEntry(int nid, int sibling_nid, int depth, bst_float loss_chg, unsigned tstmp): + nid(nid), sibling_nid(sibling_nid), depth(depth), loss_chg(loss_chg), timestamp(tstmp) {} }; // initialize temp data structure @@ -259,13 +255,28 @@ class QuantileHistMaker: public TreeUpdater { RegTree *p_tree, const std::vector &gpair_h); - void BuildLocalHistograms(int *starting_index, - int *sync_count, - const GHistIndexMatrix &gmat, + void BuildLocalHistograms(const GHistIndexMatrix &gmat, const GHistIndexBlockMatrix &gmatb, RegTree *p_tree, const std::vector &gpair_h); + void AddHistRows(int *starting_index, int *sync_count); + + void BuildHistogramsLossGuide( + ExpandEntry entry, + const GHistIndexMatrix &gmat, + const GHistIndexBlockMatrix &gmatb, + RegTree *p_tree, + const std::vector &gpair_h); + + // Split nodes to 2 sets depending on amount of rows in each node + // Histograms for small nodes will be built explicitly + // Histograms for big nodes will be built by 'Subtraction Trick' + void SplitSiblings(const std::vector& nodes, + std::vector* small_siblings, + std::vector* big_siblings, + RegTree *p_tree); + void SyncHistograms(int starting_index, int sync_count, RegTree *p_tree); @@ -336,12 +347,15 @@ class QuantileHistMaker: public TreeUpdater { std::vector qexpand_depth_wise_; // key is the node id which should be calculated by Subtraction Trick, value is the node which // provides the evidence for substracts - std::unordered_map nodes_for_subtraction_trick_; + std::vector nodes_for_subtraction_trick_; + // list of nodes whose histograms would be built explicitly. + std::vector nodes_for_explicit_hist_build_; enum DataLayout { kDenseDataZeroBased, kDenseDataOneBased, kSparseData }; DataLayout data_layout_; common::Monitor builder_monitor_; + common::ParallelGHistBuilder hist_buffer_; rabit::Reducer histred_; }; diff --git a/tests/cpp/common/test_hist_util.cc b/tests/cpp/common/test_hist_util.cc index 4d502370751e..4eb7cb68a104 100644 --- a/tests/cpp/common/test_hist_util.cc +++ b/tests/cpp/common/test_hist_util.cc @@ -9,6 +9,123 @@ namespace xgboost { namespace common { +size_t GetNThreads() { + size_t nthreads; + #pragma omp parallel + { + #pragma omp master + nthreads = omp_get_num_threads(); + } + return nthreads; +} + + +TEST(ParallelGHistBuilder, Reset) { + constexpr size_t kBins = 10; + constexpr size_t kNodes = 5; + constexpr size_t kNodesExtended = 10; + constexpr size_t kTasksPerNode = 10; + constexpr double kValue = 1.0; + const size_t nthreads = GetNThreads(); + + HistCollection collection; + collection.Init(kBins); + + for(size_t inode = 0; inode < kNodesExtended; inode++) { + collection.AddHistRow(inode); + } + + ParallelGHistBuilder hist_builder; + hist_builder.Init(kBins); + std::vector target_hist(kNodes); + for(size_t i = 0; i < target_hist.size(); ++i) { + target_hist[i] = collection[i]; + } + + common::BlockedSpace2d space(kNodes, [&](size_t node) { return kTasksPerNode; }, 1); + hist_builder.Reset(nthreads, kNodes, space, target_hist); + + common::ParallelFor2d(space, nthreads, [&](size_t inode, common::Range1d r) { + const size_t itask = r.begin(); + const size_t tid = omp_get_thread_num(); + + GHistRow hist = hist_builder.GetInitializedHist(tid, inode); + // fill hist by some non-null values + for(size_t j = 0; j < kBins; ++j) { + hist[j].Add(kValue, kValue); + } + }); + + // reset and extend buffer + target_hist.resize(kNodesExtended); + for(size_t i = 0; i < target_hist.size(); ++i) { + target_hist[i] = collection[i]; + } + common::BlockedSpace2d space2(kNodesExtended, [&](size_t node) { return kTasksPerNode; }, 1); + hist_builder.Reset(nthreads, kNodesExtended, space2, target_hist); + + common::ParallelFor2d(space2, nthreads, [&](size_t inode, common::Range1d r) { + const size_t itask = r.begin(); + const size_t tid = omp_get_thread_num(); + + GHistRow hist = hist_builder.GetInitializedHist(tid, inode); + // fill hist by some non-null values + for(size_t j = 0; j < kBins; ++j) { + ASSERT_EQ(0.0, hist[j].GetGrad()); + ASSERT_EQ(0.0, hist[j].GetHess()); + } + }); +} + +TEST(ParallelGHistBuilder, ReduceHist) { + constexpr size_t kBins = 10; + constexpr size_t kNodes = 5; + constexpr size_t kNodesExtended = 10; + constexpr size_t kTasksPerNode = 10; + constexpr double kValue = 1.0; + const size_t nthreads = GetNThreads(); + + HistCollection collection; + collection.Init(kBins); + + for(size_t inode = 0; inode < kNodes; inode++) { + collection.AddHistRow(inode); + } + + ParallelGHistBuilder hist_builder; + hist_builder.Init(kBins); + std::vector target_hist(kNodes); + for(size_t i = 0; i < target_hist.size(); ++i) { + target_hist[i] = collection[i]; + } + + common::BlockedSpace2d space(kNodes, [&](size_t node) { return kTasksPerNode; }, 1); + hist_builder.Reset(nthreads, kNodes, space, target_hist); + + // Simple analog of BuildHist function, works in parallel for both tree-nodes and data in node + common::ParallelFor2d(space, nthreads, [&](size_t inode, common::Range1d r) { + const size_t itask = r.begin(); + const size_t tid = omp_get_thread_num(); + + GHistRow hist = hist_builder.GetInitializedHist(tid, inode); + for(size_t i = 0; i < kBins; ++i) { + hist[i].Add(kValue, kValue); + } + }); + + for(size_t inode = 0; inode < kNodes; inode++) { + hist_builder.ReduceHist(inode, 0, kBins); + + // We had kTasksPerNode tasks to add kValue to each bin for each node + // So, after reducing we expect to have (kValue * kTasksPerNode) in each node + for(size_t i = 0; i < kBins; ++i) { + ASSERT_EQ(kValue * kTasksPerNode, collection[inode][i].GetGrad()); + ASSERT_EQ(kValue * kTasksPerNode, collection[inode][i].GetHess()); + } + } +} + + TEST(CutsBuilder, SearchGroupInd) { size_t constexpr kNumGroups = 4; size_t constexpr kRows = 17; diff --git a/tests/cpp/common/test_threading_utils.cc b/tests/cpp/common/test_threading_utils.cc index f89d6bdb910e..0d49c490a050 100755 --- a/tests/cpp/common/test_threading_utils.cc +++ b/tests/cpp/common/test_threading_utils.cc @@ -37,7 +37,7 @@ TEST(ParallelFor2d, Test) { return kDim2; }, kGrainSize); - ParallelFor2d(space, [&](size_t i, Range1d r) { + ParallelFor2d(space, 4, [&](size_t i, Range1d r) { for (auto j = r.begin(); j < r.end(); ++j) { matrix[i*kDim2 + j] += 1; } @@ -65,7 +65,7 @@ TEST(ParallelFor2dNonUniform, Test) { working_space[i].resize(dim2[i], 0); } - ParallelFor2d(space, [&](size_t i, Range1d r) { + ParallelFor2d(space, 4, [&](size_t i, Range1d r) { for (auto j = r.begin(); j < r.end(); ++j) { working_space[i][j] += 1; } diff --git a/tests/cpp/tree/test_quantile_hist.cc b/tests/cpp/tree/test_quantile_hist.cc index db89d64869be..657f067997a2 100644 --- a/tests/cpp/tree/test_quantile_hist.cc +++ b/tests/cpp/tree/test_quantile_hist.cc @@ -107,7 +107,7 @@ class QuantileHistMock : public QuantileHistMaker { GHistIndexBlockMatrix dummy; hist_.AddHistRow(nid); BuildHist(gpair, row_set_collection_[nid], - gmat, dummy, hist_[nid], false); + gmat, dummy, hist_[nid]); // Check if number of histogram bins is correct ASSERT_EQ(hist_[nid].size(), gmat.cut.Ptrs().back()); @@ -149,7 +149,7 @@ class QuantileHistMock : public QuantileHistMaker { hist_.AddHistRow(0); BuildHist(row_gpairs, row_set_collection_[0], - gmat, quantile_index_block, hist_[0], false); + gmat, quantile_index_block, hist_[0]); RealImpl::InitNewNode(0, gmat, row_gpairs, *(*dmat), tree); @@ -211,7 +211,8 @@ class QuantileHistMock : public QuantileHistMaker { } /* Now compare against result given by EvaluateSplit() */ - ExpandEntry node(0, tree.GetDepth(0), snode_[0].best.loss_chg, 0); + ExpandEntry node(ExpandEntry::kRootNid, ExpandEntry::kEmptyNid, + tree.GetDepth(0), snode_[0].best.loss_chg, 0); RealImpl::EvaluateSplit({node}, gmat, hist_, *(*dmat), tree); ASSERT_EQ(snode_[0].best.SplitIndex(), best_split_feature); ASSERT_EQ(snode_[0].best.split_value, gmat.cut.Values()[best_split_threshold]);