decouple bagging with num_threads (#2804)

* fix bagging

* fixed cpplint issues

* updated docs
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

docs/FAQ.rst

+.. role:: raw-html(raw)
+    :format: html
+
 LightGBM FAQ
 ############
 
@@ -82,8 +85,13 @@ You may also use the CPU version.
 6. Bagging is not reproducible when changing the number of threads.
 -------------------------------------------------------------------
 
+:raw-html:`<strike>`
 LightGBM bagging is multithreaded, so its output depends on the number of threads used.
 There is `no workaround currently <https://github.com/microsoft/LightGBM/issues/632>`__.
+:raw-html:`</strike>`
+
+Starting from `#2804 <https://github.com/microsoft/LightGBM/pull/2804>`__ bagging result doesn't depend on the number of threads.
+So this issue should be solved in the latest version.
 
 7. I tried to use Random Forest mode, and LightGBM crashes!
 -----------------------------------------------------------

docs/Parameters.rst

@@ -566,7 +566,7 @@ Dataset Parameters
 
 -  ``data_random_seed`` :raw-html:`<a id="data_random_seed" title="Permalink to this parameter" href="#data_random_seed">&#x1F517;&#xFE0E;</a>`, default = ``1``, type = int, aliases: ``data_seed``
 
-   -  random seed for data partition in parallel learning (excluding the ``feature_parallel`` mode)
+   -  random seed for sampling data to construct histogram bins
 
 -  ``is_enable_sparse`` :raw-html:`<a id="is_enable_sparse" title="Permalink to this parameter" href="#is_enable_sparse">&#x1F517;&#xFE0E;</a>`, default = ``true``, type = bool, aliases: ``is_sparse``, ``enable_sparse``, ``sparse``
 

include/LightGBM/config.h

@@ -529,7 +529,7 @@ struct Config {
   int bin_construct_sample_cnt = 200000;
 
   // alias = data_seed
-  // desc = random seed for data partition in parallel learning (excluding the ``feature_parallel`` mode)
+  // desc = random seed for sampling data to construct histogram bins
   int data_random_seed = 1;
 
   // alias = is_sparse, enable_sparse, sparse

include/LightGBM/utils/threading.h

 /*!
  * Copyright (c) 2016 Microsoft Corporation. All rights reserved.
- * Licensed under the MIT License. See LICENSE file in the project root for license information.
+ * Licensed under the MIT License. See LICENSE file in the project root for
+ * license information.
  */
 #ifndef LIGHTGBM_UTILS_THREADING_H_
 #define LIGHTGBM_UTILS_THREADING_H_
 
+#include <LightGBM/meta.h>
+#include <LightGBM/utils/common.h>
 #include <LightGBM/utils/openmp_wrapper.h>
 
+#include <algorithm>
 #include <functional>
 #include <vector>
 
@@ -37,6 +41,23 @@ class Threading {
       *block_size = cnt;
     }
   }
+  template <typename INDEX_T>
+  static inline void BlockInfoForceSize(int num_threads, INDEX_T cnt,
+                                        INDEX_T min_cnt_per_block,
+                                        int* out_nblock, INDEX_T* block_size) {
+    *out_nblock = std::min<int>(
+        num_threads,
+        static_cast<int>((cnt + min_cnt_per_block - 1) / min_cnt_per_block));
+    if (*out_nblock > 1) {
+      *block_size = (cnt + (*out_nblock) - 1) / (*out_nblock);
+      // force the block size to the times of min_cnt_per_block
+      *block_size = (*block_size + min_cnt_per_block - 1) / min_cnt_per_block *
+                    min_cnt_per_block;
+    } else {
+      *block_size = cnt;
+    }
+  }
+
   template <typename INDEX_T>
   static inline int For(
       INDEX_T start, INDEX_T end, INDEX_T min_block_size,
@@ -58,6 +79,116 @@ class Threading {
   }
 };
 
+template <typename INDEX_T, bool TWO_BUFFER>
+class ParallelPartitionRunner {
+ public:
+  ParallelPartitionRunner(INDEX_T num_data, INDEX_T min_block_size)
+      : min_block_size_(min_block_size) {
+    num_threads_ = 1;
+#pragma omp parallel
+#pragma omp master
+    { num_threads_ = omp_get_num_threads(); }
+    left_.resize(num_data);
+    if (TWO_BUFFER) {
+      right_.resize(num_data);
+    }
+    offsets_.resize(num_threads_);
+    left_cnts_.resize(num_threads_);
+    right_cnts_.resize(num_threads_);
+    left_write_pos_.resize(num_threads_);
+    right_write_pos_.resize(num_threads_);
+  }
+
+  ~ParallelPartitionRunner() {}
+
+  void ReSize(INDEX_T num_data) {
+    left_.resize(num_data);
+    if (TWO_BUFFER) {
+      right_.resize(num_data);
+    }
+  }
+
+  template<bool FORCE_SIZE>
+  INDEX_T Run(
+      INDEX_T cnt,
+      const std::function<INDEX_T(int, INDEX_T, INDEX_T, INDEX_T*, INDEX_T*)>& func,
+      INDEX_T* out) {
+    int nblock = 1;
+    INDEX_T inner_size = cnt;
+    if (FORCE_SIZE) {
+      Threading::BlockInfoForceSize<INDEX_T>(num_threads_, cnt, min_block_size_,
+                                             &nblock, &inner_size);
+    } else {
+      Threading::BlockInfo<INDEX_T>(num_threads_, cnt, min_block_size_, &nblock,
+                                    &inner_size);
+    }
+
+    OMP_INIT_EX();
+#pragma omp parallel for schedule(static, 1)
+    for (int i = 0; i < nblock; ++i) {
+      OMP_LOOP_EX_BEGIN();
+      INDEX_T cur_start = i * inner_size;
+      INDEX_T cur_cnt = std::min(inner_size, cnt - cur_start);
+      offsets_[i] = cur_start;
+      if (cur_cnt <= 0) {
+        left_cnts_[i] = 0;
+        right_cnts_[i] = 0;
+        continue;
+      }
+      auto left_ptr = left_.data() + cur_start;
+      INDEX_T* right_ptr = nullptr;
+      if (TWO_BUFFER) {
+        right_ptr = right_.data() + cur_start;
+      }
+      // split data inner, reduce the times of function called
+      INDEX_T cur_left_count =
+          func(i, cur_start, cur_cnt, left_ptr, right_ptr);
+      if (!TWO_BUFFER) {
+        // reverse for one buffer
+        std::reverse(left_ptr + cur_left_count, left_ptr + cur_cnt);
+      }
+      left_cnts_[i] = cur_left_count;
+      right_cnts_[i] = cur_cnt - cur_left_count;
+      OMP_LOOP_EX_END();
+    }
+    OMP_THROW_EX();
+
+    left_write_pos_[0] = 0;
+    right_write_pos_[0] = 0;
+    for (int i = 1; i < nblock; ++i) {
+      left_write_pos_[i] = left_write_pos_[i - 1] + left_cnts_[i - 1];
+      right_write_pos_[i] = right_write_pos_[i - 1] + right_cnts_[i - 1];
+    }
+    data_size_t left_cnt = left_write_pos_[nblock - 1] + left_cnts_[nblock - 1];
+
+    auto right_start = out + left_cnt;
+#pragma omp parallel for schedule(static)
+    for (int i = 0; i < nblock; ++i) {
+      std::copy_n(left_.data() + offsets_[i], left_cnts_[i],
+                  out + left_write_pos_[i]);
+      if (TWO_BUFFER) {
+        std::copy_n(right_.data() + offsets_[i], right_cnts_[i],
+                    right_start + right_write_pos_[i]);
+      } else {
+        std::copy_n(left_.data() + offsets_[i] + left_cnts_[i], right_cnts_[i],
+                    right_start + right_write_pos_[i]);
+      }
+    }
+    return left_cnt;
+  }
+
+ private:
+  int num_threads_;
+  INDEX_T min_block_size_;
+  std::vector<INDEX_T> left_;
+  std::vector<INDEX_T> right_;
+  std::vector<INDEX_T> offsets_;
+  std::vector<INDEX_T> left_cnts_;
+  std::vector<INDEX_T> right_cnts_;
+  std::vector<INDEX_T> left_write_pos_;
+  std::vector<INDEX_T> right_write_pos_;
+};
+
 }  // namespace LightGBM
 
 #endif  // LightGBM_UTILS_THREADING_H_

src/boosting/gbdt.cpp

@@ -18,24 +18,21 @@
 
 namespace LightGBM {
 
-GBDT::GBDT() : iter_(0),
-train_data_(nullptr),
-objective_function_(nullptr),
-early_stopping_round_(0),
-es_first_metric_only_(false),
-max_feature_idx_(0),
-num_tree_per_iteration_(1),
-num_class_(1),
-num_iteration_for_pred_(0),
-shrinkage_rate_(0.1f),
-num_init_iteration_(0),
-need_re_bagging_(false),
-balanced_bagging_(false) {
-  #pragma omp parallel
-  #pragma omp master
-  {
-    num_threads_ = omp_get_num_threads();
-  }
+GBDT::GBDT()
+    : iter_(0),
+      train_data_(nullptr),
+      objective_function_(nullptr),
+      early_stopping_round_(0),
+      es_first_metric_only_(false),
+      max_feature_idx_(0),
+      num_tree_per_iteration_(1),
+      num_class_(1),
+      num_iteration_for_pred_(0),
+      shrinkage_rate_(0.1f),
+      num_init_iteration_(0),
+      need_re_bagging_(false),
+      balanced_bagging_(false),
+      bagging_runner_(0, bagging_rand_block_) {
   average_output_ = false;
   tree_learner_ = nullptr;
 }
@@ -164,53 +161,50 @@ void GBDT::Boosting() {
     GetGradients(GetTrainingScore(&num_score), gradients_.data(), hessians_.data());
 }
 
-data_size_t GBDT::BaggingHelper(Random* cur_rand, data_size_t start, data_size_t cnt, data_size_t* buffer) {
+data_size_t GBDT::BaggingHelper(data_size_t start, data_size_t cnt, data_size_t* buffer) {
   if (cnt <= 0) {
     return 0;
   }
-  data_size_t bag_data_cnt = static_cast<data_size_t>(config_->bagging_fraction * cnt);
   data_size_t cur_left_cnt = 0;
-  data_size_t cur_right_cnt = 0;
-  auto right_buffer = buffer + bag_data_cnt;
+  data_size_t cur_right_pos = cnt;
   // random bagging, minimal unit is one record
   for (data_size_t i = 0; i < cnt; ++i) {
-    float prob = (bag_data_cnt - cur_left_cnt) / static_cast<float>(cnt - i);
-    if (cur_rand->NextFloat() < prob) {
-      buffer[cur_left_cnt++] = start + i;
+    auto cur_idx = start + i;
+    if (bagging_rands_[cur_idx / bagging_rand_block_].NextFloat() < config_->bagging_fraction) {
+      buffer[cur_left_cnt++] = cur_idx;
     } else {
-      right_buffer[cur_right_cnt++] = start + i;
+      buffer[--cur_right_pos] = cur_idx;
     }
   }
-  CHECK(cur_left_cnt == bag_data_cnt);
   return cur_left_cnt;
 }
 
-data_size_t GBDT::BalancedBaggingHelper(Random* cur_rand, data_size_t start, data_size_t cnt, data_size_t* buffer) {
+data_size_t GBDT::BalancedBaggingHelper(data_size_t start, data_size_t cnt,
+                                        data_size_t* buffer) {
   if (cnt <= 0) {
     return 0;
   }
   auto label_ptr = train_data_->metadata().label();
   data_size_t cur_left_cnt = 0;
-  data_size_t cur_right_pos = cnt - 1;
-  // from right to left
-  auto right_buffer = buffer;
+  data_size_t cur_right_pos = cnt;
   // random bagging, minimal unit is one record
   for (data_size_t i = 0; i < cnt; ++i) {
+    auto cur_idx = start + i;
     bool is_pos = label_ptr[start + i] > 0;
     bool is_in_bag = false;
     if (is_pos) {
-      is_in_bag = cur_rand->NextFloat() < config_->pos_bagging_fraction;
+      is_in_bag = bagging_rands_[cur_idx / bagging_rand_block_].NextFloat() <
+                  config_->pos_bagging_fraction;
     } else {
-      is_in_bag = cur_rand->NextFloat() < config_->neg_bagging_fraction;
+      is_in_bag = bagging_rands_[cur_idx / bagging_rand_block_].NextFloat() <
+                  config_->neg_bagging_fraction;
     }
     if (is_in_bag) {
-      buffer[cur_left_cnt++] = start + i;
+      buffer[cur_left_cnt++] = cur_idx;
     } else {
-      right_buffer[cur_right_pos--] = start + i;
+      buffer[--cur_right_pos] = cur_idx;
     }
   }
-  // reverse right buffer
-  std::reverse(buffer + cur_left_cnt, buffer + cnt);
   return cur_left_cnt;
 }
 
@@ -220,54 +214,20 @@ void GBDT::Bagging(int iter) {
   if ((bag_data_cnt_ < num_data_ && iter % config_->bagging_freq == 0) ||
       need_re_bagging_) {
     need_re_bagging_ = false;
-    int n_block = Threading::For<data_size_t>(
-        0, num_data_, 1024,
-        [this, iter](int i, data_size_t cur_start, data_size_t cur_end) {
-          data_size_t cur_cnt = cur_end - cur_start;
-          if (cur_cnt <= 0) {
-            left_cnts_buf_[i] = 0;
-            right_cnts_buf_[i] = 0;
-          } else {
-            Random cur_rand(config_->bagging_seed + iter * num_threads_ + i);
+    auto left_cnt = bagging_runner_.Run<true>(
+        num_data_,
+        [=](int, data_size_t cur_start, data_size_t cur_cnt, data_size_t* left,
+            data_size_t*) {
           data_size_t cur_left_count = 0;
           if (balanced_bagging_) {
             cur_left_count =
-                  BalancedBaggingHelper(&cur_rand, cur_start, cur_cnt,
-                                        tmp_indices_.data() + cur_start);
+                BalancedBaggingHelper(cur_start, cur_cnt, left);
           } else {
-              cur_left_count = BaggingHelper(&cur_rand, cur_start, cur_cnt,
-                                             tmp_indices_.data() + cur_start);
-            }
-            offsets_buf_[i] = cur_start;
-            left_cnts_buf_[i] = cur_left_count;
-            right_cnts_buf_[i] = cur_cnt - cur_left_count;
-          }
-        });
-    data_size_t left_cnt = 0;
-    left_write_pos_buf_[0] = 0;
-    right_write_pos_buf_[0] = 0;
-    for (int i = 1; i < n_block; ++i) {
-      left_write_pos_buf_[i] =
-          left_write_pos_buf_[i - 1] + left_cnts_buf_[i - 1];
-      right_write_pos_buf_[i] =
-          right_write_pos_buf_[i - 1] + right_cnts_buf_[i - 1];
-    }
-    left_cnt = left_write_pos_buf_[n_block - 1] + left_cnts_buf_[n_block - 1];
-
-#pragma omp parallel for schedule(static, 1)
-    for (int i = 0; i < n_block; ++i) {
-      if (left_cnts_buf_[i] > 0) {
-        std::memcpy(bag_data_indices_.data() + left_write_pos_buf_[i],
-                    tmp_indices_.data() + offsets_buf_[i],
-                    left_cnts_buf_[i] * sizeof(data_size_t));
-      }
-      if (right_cnts_buf_[i] > 0) {
-        std::memcpy(
-            bag_data_indices_.data() + left_cnt + right_write_pos_buf_[i],
-            tmp_indices_.data() + offsets_buf_[i] + left_cnts_buf_[i],
-            right_cnts_buf_[i] * sizeof(data_size_t));
-      }
+            cur_left_count = BaggingHelper(cur_start, cur_cnt, left);
           }
+          return cur_left_count;
+        },
+        bag_data_indices_.data());
     bag_data_cnt_ = left_cnt;
     Log::Debug("Re-bagging, using %d data to train", bag_data_cnt_);
     // set bagging data to tree learner
@@ -780,15 +740,15 @@ void GBDT::ResetBaggingConfig(const Config* config, bool is_change_dataset) {
       bag_data_cnt_ = static_cast<data_size_t>(config->bagging_fraction * num_data_);
     }
     bag_data_indices_.resize(num_data_);
-    tmp_indices_.resize(num_data_);
-
-    offsets_buf_.resize(num_threads_);
-    left_cnts_buf_.resize(num_threads_);
-    right_cnts_buf_.resize(num_threads_);
-    left_write_pos_buf_.resize(num_threads_);
-    right_write_pos_buf_.resize(num_threads_);
+    bagging_runner_.ReSize(num_data_);
+    bagging_rands_.clear();
+    for (int i = 0;
+         i < (num_data_ + bagging_rand_block_ - 1) / bagging_rand_block_; ++i) {
+      bagging_rands_.emplace_back(config_->bagging_seed + i);
+    }
 
-    double average_bag_rate = (bag_data_cnt_ / num_data_) / config->bagging_freq;
+    double average_bag_rate =
+        (static_cast<double>(bag_data_cnt_) / num_data_) / config->bagging_freq;
     is_use_subset_ = false;
     const int group_threshold_usesubset = 100;
     if (tree_learner_->IsHistColWise() && average_bag_rate <= 0.5
@@ -813,7 +773,7 @@ void GBDT::ResetBaggingConfig(const Config* config, bool is_change_dataset) {
   } else {
     bag_data_cnt_ = num_data_;
     bag_data_indices_.clear();
-    tmp_indices_.clear();
+    bagging_runner_.ReSize(0);
     is_use_subset_ = false;
   }
 }

src/boosting/gbdt.h

@@ -8,6 +8,7 @@
 #include <LightGBM/boosting.h>
 #include <LightGBM/objective_function.h>
 #include <LightGBM/prediction_early_stop.h>
+#include <LightGBM/utils/threading.h>
 
 #include <string>
 #include <algorithm>
@@ -390,24 +391,11 @@ class GBDT : public GBDTBase {
   */
   virtual void Bagging(int iter);
 
-  /*!
-  * \brief Helper function for bagging, used for multi-threading optimization
-  * \param start start indice of bagging
-  * \param cnt count
-  * \param buffer output buffer
-  * \return count of left size
-  */
-  data_size_t BaggingHelper(Random* cur_rand, data_size_t start, data_size_t cnt, data_size_t* buffer);
+  virtual data_size_t BaggingHelper(data_size_t start, data_size_t cnt,
+                                    data_size_t* buffer);
 
-
-  /*!
-  * \brief Helper function for bagging, used for multi-threading optimization, balanced sampling
-  * \param start start indice of bagging
-  * \param cnt count
-  * \param buffer output buffer
-  * \return count of left size
-  */
-  data_size_t BalancedBaggingHelper(Random* cur_rand, data_size_t start, data_size_t cnt, data_size_t* buffer);
+  data_size_t BalancedBaggingHelper(data_size_t start, data_size_t cnt,
+                                    data_size_t* buffer);
 
   /*!
   * \brief calculate the object function
@@ -476,8 +464,6 @@ class GBDT : public GBDTBase {
   std::vector<data_size_t, Common::AlignmentAllocator<data_size_t, kAlignedSize>> bag_data_indices_;
   /*! \brief Number of in-bag data */
   data_size_t bag_data_cnt_;
-  /*! \brief Store the indices of in-bag data */
-  std::vector<data_size_t> tmp_indices_;
   /*! \brief Number of training data */
   data_size_t num_data_;
   /*! \brief Number of trees per iterations */
@@ -495,18 +481,6 @@ class GBDT : public GBDTBase {
   /*! \brief Feature names */
   std::vector<std::string> feature_names_;
   std::vector<std::string> feature_infos_;
-  /*! \brief number of threads */
-  int num_threads_;
-  /*! \brief Buffer for multi-threading bagging */
-  std::vector<data_size_t> offsets_buf_;
-  /*! \brief Buffer for multi-threading bagging */
-  std::vector<data_size_t> left_cnts_buf_;
-  /*! \brief Buffer for multi-threading bagging */
-  std::vector<data_size_t> right_cnts_buf_;
-  /*! \brief Buffer for multi-threading bagging */
-  std::vector<data_size_t> left_write_pos_buf_;
-  /*! \brief Buffer for multi-threading bagging */
-  std::vector<data_size_t> right_write_pos_buf_;
   std::unique_ptr<Dataset> tmp_subset_;
   bool is_use_subset_;
   std::vector<bool> class_need_train_;
@@ -517,7 +491,9 @@ class GBDT : public GBDTBase {
   bool balanced_bagging_;
   std::string loaded_parameter_;
   std::vector<int8_t> monotone_constraints_;
-
+  const int bagging_rand_block_ = 1024;
+  std::vector<Random> bagging_rands_;
+  ParallelPartitionRunner<data_size_t, false> bagging_runner_;
   Json forced_splits_json_;
 };
 

src/boosting/goss.hpp

@@ -57,15 +57,9 @@ class GOSS: public GBDT {
       Log::Fatal("Cannot use bagging in GOSS");
     }
     Log::Info("Using GOSS");
-
+    balanced_bagging_ = false;
     bag_data_indices_.resize(num_data_);
-    tmp_indices_.resize(num_data_);
-    tmp_indice_right_.resize(num_data_);
-    offsets_buf_.resize(num_threads_);
-    left_cnts_buf_.resize(num_threads_);
-    right_cnts_buf_.resize(num_threads_);
-    left_write_pos_buf_.resize(num_threads_);
-    right_write_pos_buf_.resize(num_threads_);
+    bagging_runner_.ReSize(num_data_);
 
     is_use_subset_ = false;
     if (config_->top_rate + config_->other_rate <= 0.5) {
@@ -79,7 +73,7 @@ class GOSS: public GBDT {
     bag_data_cnt_ = num_data_;
   }
 
-  data_size_t BaggingHelper(Random* cur_rand, data_size_t start, data_size_t cnt, data_size_t* buffer, data_size_t* buffer_right) {
+  data_size_t BaggingHelper(data_size_t start, data_size_t cnt, data_size_t* buffer) override {
     if (cnt <= 0) {
       return 0;
     }
@@ -98,31 +92,32 @@ class GOSS: public GBDT {
 
     score_t multiply = static_cast<score_t>(cnt - top_k) / other_k;
     data_size_t cur_left_cnt = 0;
-    data_size_t cur_right_cnt = 0;
+    data_size_t cur_right_pos = cnt;
     data_size_t big_weight_cnt = 0;
     for (data_size_t i = 0; i < cnt; ++i) {
+      auto cur_idx = start + i;
       score_t grad = 0.0f;
       for (int cur_tree_id = 0; cur_tree_id < num_tree_per_iteration_; ++cur_tree_id) {
-        size_t idx = static_cast<size_t>(cur_tree_id) * num_data_ + start + i;
+        size_t idx = static_cast<size_t>(cur_tree_id) * num_data_ + cur_idx;
         grad += std::fabs(gradients_[idx] * hessians_[idx]);
       }
       if (grad >= threshold) {
-        buffer[cur_left_cnt++] = start + i;
+        buffer[cur_left_cnt++] = cur_idx;
         ++big_weight_cnt;
       } else {
         data_size_t sampled = cur_left_cnt - big_weight_cnt;
         data_size_t rest_need = other_k - sampled;
         data_size_t rest_all = (cnt - i) - (top_k - big_weight_cnt);
         double prob = (rest_need) / static_cast<double>(rest_all);
-        if (cur_rand->NextFloat() < prob) {
-          buffer[cur_left_cnt++] = start + i;
+        if (bagging_rands_[cur_idx / bagging_rand_block_].NextFloat() < prob) {
+          buffer[cur_left_cnt++] = cur_idx;
           for (int cur_tree_id = 0; cur_tree_id < num_tree_per_iteration_; ++cur_tree_id) {
-            size_t idx = static_cast<size_t>(cur_tree_id) * num_data_ + start + i;
+            size_t idx = static_cast<size_t>(cur_tree_id) * num_data_ + cur_idx;
             gradients_[idx] *= multiply;
             hessians_[idx] *= multiply;
           }
         } else {
-          buffer_right[cur_right_cnt++] = start + i;
+          buffer[--cur_right_pos] = cur_idx;
         }
       }
     }
@@ -135,9 +130,6 @@ class GOSS: public GBDT {
     if (iter < static_cast<int>(1.0f / config_->learning_rate)) { return; }
     GBDT::Bagging(iter);
   }
-
- private:
-  std::vector<data_size_t> tmp_indice_right_;
 };
 
 }  // namespace LightGBM

src/treelearner/data_partition.hpp

@@ -21,23 +21,11 @@ namespace LightGBM {
 class DataPartition {
  public:
   DataPartition(data_size_t num_data, int num_leaves)
-    :num_data_(num_data), num_leaves_(num_leaves) {
+      : num_data_(num_data), num_leaves_(num_leaves), runner_(num_data, 512) {
     leaf_begin_.resize(num_leaves_);
     leaf_count_.resize(num_leaves_);
     indices_.resize(num_data_);
-    temp_left_indices_.resize(num_data_);
-    temp_right_indices_.resize(num_data_);
     used_data_indices_ = nullptr;
-    #pragma omp parallel
-    #pragma omp master
-    {
-      num_threads_ = omp_get_num_threads();
-    }
-    offsets_buf_.resize(num_threads_);
-    left_cnts_buf_.resize(num_threads_);
-    right_cnts_buf_.resize(num_threads_);
-    left_write_pos_buf_.resize(num_threads_);
-    right_write_pos_buf_.resize(num_threads_);
   }
 
   void ResetLeaves(int num_leaves) {
@@ -49,8 +37,7 @@ class DataPartition {
   void ResetNumData(int num_data) {
     num_data_ = num_data;
     indices_.resize(num_data_);
-    temp_left_indices_.resize(num_data_);
-    temp_right_indices_.resize(num_data_);
+    runner_.ReSize(num_data_);
   }
 
   ~DataPartition() {
@@ -118,63 +105,18 @@ class DataPartition {
     // get leaf boundary
     const data_size_t begin = leaf_begin_[leaf];
     const data_size_t cnt = leaf_count_[leaf];
-
-    int nblock = 1;
-    data_size_t inner_size = cnt;
-    Threading::BlockInfo<data_size_t>(num_threads_, cnt, 512, &nblock,
-                                      &inner_size);
     auto left_start = indices_.data() + begin;
-    global_timer.Start("DataPartition::Split.MT");
-    // split data multi-threading
-    OMP_INIT_EX();
-#pragma omp parallel for schedule(static, 1)
-    for (int i = 0; i < nblock; ++i) {
-      OMP_LOOP_EX_BEGIN();
-      data_size_t cur_start = i * inner_size;
-      data_size_t cur_cnt = std::min(inner_size, cnt - cur_start);
-      if (cur_cnt <= 0) {
-        left_cnts_buf_[i] = 0;
-        right_cnts_buf_[i] = 0;
-        continue;
-      }
-      // split data inner, reduce the times of function called
-      data_size_t cur_left_count =
-          dataset->Split(feature, threshold, num_threshold, default_left,
-                         left_start + cur_start, cur_cnt,
-                         temp_left_indices_.data() + cur_start,
-                         temp_right_indices_.data() + cur_start);
-      offsets_buf_[i] = cur_start;
-      left_cnts_buf_[i] = cur_left_count;
-      right_cnts_buf_[i] = cur_cnt - cur_left_count;
-      OMP_LOOP_EX_END();
-    }
-    OMP_THROW_EX();
-    global_timer.Stop("DataPartition::Split.MT");
-    global_timer.Start("DataPartition::Split.Merge");
-    left_write_pos_buf_[0] = 0;
-    right_write_pos_buf_[0] = 0;
-    for (int i = 1; i < nblock; ++i) {
-      left_write_pos_buf_[i] =
-          left_write_pos_buf_[i - 1] + left_cnts_buf_[i - 1];
-      right_write_pos_buf_[i] =
-          right_write_pos_buf_[i - 1] + right_cnts_buf_[i - 1];
-    }
-    data_size_t left_cnt =
-        left_write_pos_buf_[nblock - 1] + left_cnts_buf_[nblock - 1];
-
-    auto right_start = left_start + left_cnt;
-#pragma omp parallel for schedule(static)
-    for (int i = 0; i < nblock; ++i) {
-      std::copy_n(temp_left_indices_.data() + offsets_buf_[i],
-                  left_cnts_buf_[i], left_start + left_write_pos_buf_[i]);
-      std::copy_n(temp_right_indices_.data() + offsets_buf_[i],
-                  right_cnts_buf_[i], right_start + right_write_pos_buf_[i]);
-    }
-    // update leaf boundary
+    auto left_cnt = runner_.Run<false>(
+        cnt,
+        [=](int, data_size_t cur_start, data_size_t cur_cnt, data_size_t* left,
+            data_size_t* right) {
+          return dataset->Split(feature, threshold, num_threshold, default_left,
+                                left_start + cur_start, cur_cnt, left, right);
+        },
+        left_start);
     leaf_count_[leaf] = left_cnt;
     leaf_begin_[right_leaf] = left_cnt + begin;
     leaf_count_[right_leaf] = cnt - left_cnt;
-    global_timer.Stop("DataPartition::Split.Merge");
   }
 
   /*!
@@ -217,26 +159,11 @@ class DataPartition {
   std::vector<data_size_t> leaf_count_;
   /*! \brief Store all data's indices, order by leaf[data_in_leaf0,..,data_leaf1,..] */
   std::vector<data_size_t, Common::AlignmentAllocator<data_size_t, kAlignedSize>> indices_;
-  /*! \brief team indices buffer for split */
-  std::vector<data_size_t, Common::AlignmentAllocator<data_size_t, kAlignedSize>> temp_left_indices_;
-  /*! \brief team indices buffer for split */
-  std::vector<data_size_t, Common::AlignmentAllocator<data_size_t, kAlignedSize>> temp_right_indices_;
   /*! \brief used data indices, used for bagging */
   const data_size_t* used_data_indices_;
   /*! \brief used data count, used for bagging */
   data_size_t used_data_count_;
-  /*! \brief number of threads */
-  int num_threads_;
-  /*! \brief Buffer for multi-threading data partition, used to store offset for different threads */
-  std::vector<data_size_t> offsets_buf_;
-  /*! \brief Buffer for multi-threading data partition, used to store left count after split for different threads */
-  std::vector<data_size_t> left_cnts_buf_;
-  /*! \brief Buffer for multi-threading data partition, used to store right count after split for different threads */
-  std::vector<data_size_t> right_cnts_buf_;
-  /*! \brief Buffer for multi-threading data partition, used to store write position of left leaf for different threads */
-  std::vector<data_size_t> left_write_pos_buf_;
-  /*! \brief Buffer for multi-threading data partition, used to store write position of right leaf for different threads */
-  std::vector<data_size_t> right_write_pos_buf_;
+  ParallelPartitionRunner<data_size_t, true> runner_;
 };
 
 }  // namespace LightGBM