Optimized ApplySplit, BuildHist and UpdatePredictCache functions on CPU (#5244)

* Split up sparse and dense build hist kernels.
* Add `PartitionBuilder`.
This commit is contained in:
Egor Smirnov
2020-02-29 11:11:42 +03:00
committed by GitHub
parent b81f8cbbc0
commit 1b97eaf7a7
9 changed files with 694 additions and 387 deletions

View File

@@ -10,6 +10,7 @@
#include <xgboost/data.h>
#include <algorithm>
#include <vector>
#include <utility>
namespace xgboost {
namespace common {
@@ -29,7 +30,7 @@ class RowSetCollection {
= default;
Elem(const size_t* begin,
const size_t* end,
int node_id)
int node_id = -1)
: begin(begin), end(end), node_id(node_id) {}
inline size_t Size() const {
@@ -57,6 +58,13 @@ class RowSetCollection {
<< "access element that is not in the set";
return e;
}
/*! \brief return corresponding element set given the node_id */
inline Elem& operator[](unsigned node_id) {
Elem& e = elem_of_each_node_[node_id];
return e;
}
// clear up things
inline void Clear() {
elem_of_each_node_.clear();
@@ -83,25 +91,18 @@ class RowSetCollection {
}
// split rowset into two
inline void AddSplit(unsigned node_id,
const std::vector<Split>& row_split_tloc,
unsigned left_node_id,
unsigned right_node_id) {
unsigned right_node_id,
size_t n_left,
size_t n_right) {
const Elem e = elem_of_each_node_[node_id];
const auto nthread = static_cast<bst_omp_uint>(row_split_tloc.size());
CHECK(e.begin != nullptr);
size_t* all_begin = dmlc::BeginPtr(row_indices_);
size_t* begin = all_begin + (e.begin - all_begin);
size_t* it = begin;
for (bst_omp_uint tid = 0; tid < nthread; ++tid) {
std::copy(row_split_tloc[tid].left.begin(), row_split_tloc[tid].left.end(), it);
it += row_split_tloc[tid].left.size();
}
size_t* split_pt = it;
for (bst_omp_uint tid = 0; tid < nthread; ++tid) {
std::copy(row_split_tloc[tid].right.begin(), row_split_tloc[tid].right.end(), it);
it += row_split_tloc[tid].right.size();
}
CHECK_EQ(n_left + n_right, e.Size());
CHECK_LE(begin + n_left, e.end);
CHECK_EQ(begin + n_left + n_right, e.end);
if (left_node_id >= elem_of_each_node_.size()) {
elem_of_each_node_.resize(left_node_id + 1, Elem(nullptr, nullptr, -1));
@@ -110,12 +111,12 @@ class RowSetCollection {
elem_of_each_node_.resize(right_node_id + 1, Elem(nullptr, nullptr, -1));
}
elem_of_each_node_[left_node_id] = Elem(begin, split_pt, left_node_id);
elem_of_each_node_[right_node_id] = Elem(split_pt, e.end, right_node_id);
elem_of_each_node_[left_node_id] = Elem(begin, begin + n_left, left_node_id);
elem_of_each_node_[right_node_id] = Elem(begin + n_left, e.end, right_node_id);
elem_of_each_node_[node_id] = Elem(nullptr, nullptr, -1);
}
// stores the row indices in the set
// stores the row indexes in the set
std::vector<size_t> row_indices_;
private:
@@ -123,6 +124,121 @@ class RowSetCollection {
std::vector<Elem> elem_of_each_node_;
};
// The builder is required for samples partition to left and rights children for set of nodes
// Responsible for:
// 1) Effective memory allocation for intermediate results for multi-thread work
// 2) Merging partial results produced by threads into original row set (row_set_collection_)
// BlockSize is template to enable memory alignment easily with C++11 'alignas()' feature
template<size_t BlockSize>
class PartitionBuilder {
public:
template<typename Func>
void Init(const size_t n_tasks, size_t n_nodes, Func funcNTaks) {
left_right_nodes_sizes_.resize(n_nodes);
blocks_offsets_.resize(n_nodes+1);
blocks_offsets_[0] = 0;
for (size_t i = 1; i < n_nodes+1; ++i) {
blocks_offsets_[i] = blocks_offsets_[i-1] + funcNTaks(i-1);
}
if (n_tasks > max_n_tasks_) {
mem_blocks_.resize(n_tasks);
max_n_tasks_ = n_tasks;
}
}
common::Span<size_t> GetLeftBuffer(int nid, size_t begin, size_t end) {
const size_t task_idx = GetTaskIdx(nid, begin);
return { mem_blocks_.at(task_idx).left(), end - begin };
}
common::Span<size_t> GetRightBuffer(int nid, size_t begin, size_t end) {
const size_t task_idx = GetTaskIdx(nid, begin);
return { mem_blocks_.at(task_idx).right(), end - begin };
}
void SetNLeftElems(int nid, size_t begin, size_t end, size_t n_left) {
size_t task_idx = GetTaskIdx(nid, begin);
mem_blocks_.at(task_idx).n_left = n_left;
}
void SetNRightElems(int nid, size_t begin, size_t end, size_t n_right) {
size_t task_idx = GetTaskIdx(nid, begin);
mem_blocks_.at(task_idx).n_right = n_right;
}
size_t GetNLeftElems(int nid) const {
return left_right_nodes_sizes_[nid].first;
}
size_t GetNRightElems(int nid) const {
return left_right_nodes_sizes_[nid].second;
}
// Each thread has partial results for some set of tree-nodes
// The function decides order of merging partial results into final row set
void CalculateRowOffsets() {
for (size_t i = 0; i < blocks_offsets_.size()-1; ++i) {
size_t n_left = 0;
for (size_t j = blocks_offsets_[i]; j < blocks_offsets_[i+1]; ++j) {
mem_blocks_[j].n_offset_left = n_left;
n_left += mem_blocks_[j].n_left;
}
size_t n_right = 0;
for (size_t j = blocks_offsets_[i]; j < blocks_offsets_[i+1]; ++j) {
mem_blocks_[j].n_offset_right = n_left + n_right;
n_right += mem_blocks_[j].n_right;
}
left_right_nodes_sizes_[i] = {n_left, n_right};
}
}
void MergeToArray(int nid, size_t begin, size_t* rows_indexes) {
size_t task_idx = GetTaskIdx(nid, begin);
size_t* left_result = rows_indexes + mem_blocks_[task_idx].n_offset_left;
size_t* right_result = rows_indexes + mem_blocks_[task_idx].n_offset_right;
const size_t* left = mem_blocks_[task_idx].left();
const size_t* right = mem_blocks_[task_idx].right();
std::copy_n(left, mem_blocks_[task_idx].n_left, left_result);
std::copy_n(right, mem_blocks_[task_idx].n_right, right_result);
}
protected:
size_t GetTaskIdx(int nid, size_t begin) {
return blocks_offsets_[nid] + begin / BlockSize;
}
struct BlockInfo{
size_t n_left;
size_t n_right;
size_t n_offset_left;
size_t n_offset_right;
size_t* left() {
return &left_data_[0];
}
size_t* right() {
return &right_data_[0];
}
private:
alignas(128) size_t left_data_[BlockSize];
alignas(128) size_t right_data_[BlockSize];
};
std::vector<std::pair<size_t, size_t>> left_right_nodes_sizes_;
std::vector<size_t> blocks_offsets_;
std::vector<BlockInfo> mem_blocks_;
size_t max_n_tasks_ = 0;
};
} // namespace common
} // namespace xgboost