rollback to omp sum (#3493)

* rollback omp sum

* remove sum reduction

include/LightGBM/utils/threading.h

@@ -84,33 +84,6 @@ class Threading {
     OMP_THROW_EX();
     return n_block;
   }
-
-  template <typename INDEX_T, typename VAL1_T, typename VAL2_T>
-  static inline int SumReduction(
-      INDEX_T start, INDEX_T end, INDEX_T min_block_size,
-      const std::function<void(int, INDEX_T, INDEX_T, VAL1_T* res1,
-                               VAL2_T* res2)>& inner_fun,
-      VAL1_T* res1, VAL2_T* res2) {
-    int n_block = 1;
-    INDEX_T num_inner = end - start;
-    BlockInfoForceSize<INDEX_T>(num_inner, min_block_size, &n_block,
-                                &num_inner);
-    std::vector<VAL1_T> val_1s(n_block, static_cast<VAL1_T>(0));
-    std::vector<VAL2_T> val_2s(n_block, static_cast<VAL2_T>(0));
-#pragma omp parallel for schedule(static)
-    for (int i = 0; i < n_block; ++i) {
-      INDEX_T inner_start = start + num_inner * i;
-      INDEX_T inner_end = std::min(end, inner_start + num_inner);
-      inner_fun(i, inner_start, inner_end, &val_1s[i], &val_2s[i]);
-    }
-    *res1 = 0;
-    *res2 = 0;
-    for (int i = 0; i < n_block; ++i) {
-      *res1 += val_1s[i];
-      *res2 += val_2s[i];
-    }
-    return n_block;
-  }
 };
 
 template <typename INDEX_T, bool TWO_BUFFER>

src/treelearner/leaf_splits.hpp

@@ -68,24 +68,15 @@ class LeafSplits {
     num_data_in_leaf_ = num_data_;
     leaf_index_ = 0;
     data_indices_ = nullptr;
-    if (num_data_in_leaf_ < 4096) {
-      sum_gradients_ = 0.0f;
-      sum_hessians_ = 0.0f;
-      for (data_size_t i = 0; i < num_data_in_leaf_; ++i) {
-        sum_gradients_ += gradients[i];
-        sum_hessians_ += hessians[i];
-      }
-    } else {
-      Threading::SumReduction<data_size_t, double, double>(
-          0, num_data_in_leaf_, 2048,
-          [=](int, data_size_t start, data_size_t end, double* s1, double* s2) {
-            for (data_size_t i = start; i < end; ++i) {
-              *s1 += gradients[i];
-              *s2 += hessians[i];
-            }
-          },
-          &sum_gradients_, &sum_hessians_);
+    double tmp_sum_gradients = 0.0f;
+    double tmp_sum_hessians = 0.0f;
+#pragma omp parallel for schedule(static, 512) reduction(+:tmp_sum_gradients, tmp_sum_hessians) if (num_data_in_leaf_ >= 1024)
+    for (data_size_t i = 0; i < num_data_in_leaf_; ++i) {
+      tmp_sum_gradients += gradients[i];
+      tmp_sum_hessians += hessians[i];
     }
+    sum_gradients_ = tmp_sum_gradients;
+    sum_hessians_ = tmp_sum_hessians;
   }
 
   /*!
@@ -99,26 +90,16 @@ class LeafSplits {
             const score_t* gradients, const score_t* hessians) {
     leaf_index_ = leaf;
     data_indices_ = data_partition->GetIndexOnLeaf(leaf, &num_data_in_leaf_);
-    if (num_data_in_leaf_ < 4096) {
-      sum_gradients_ = 0.0f;
-      sum_hessians_ = 0.0f;
-      for (data_size_t i = 0; i < num_data_in_leaf_; ++i) {
-        const data_size_t idx = data_indices_[i];
-        sum_gradients_ += gradients[idx];
-        sum_hessians_ += hessians[idx];
-      }
-    } else {
-      Threading::SumReduction<data_size_t, double, double>(
-          0, num_data_in_leaf_, 2048,
-          [=](int, data_size_t start, data_size_t end, double* s1, double* s2) {
-            for (data_size_t i = start; i < end; ++i) {
-              const data_size_t idx = data_indices_[i];
-              *s1 += gradients[idx];
-              *s2 += hessians[idx];
-            }
-          },
-          &sum_gradients_, &sum_hessians_);
+    double tmp_sum_gradients = 0.0f;
+    double tmp_sum_hessians = 0.0f;
+#pragma omp parallel for schedule(static, 512) reduction(+:tmp_sum_gradients, tmp_sum_hessians) if (num_data_in_leaf_ >= 1024)
+    for (data_size_t i = 0; i < num_data_in_leaf_; ++i) {
+      const data_size_t idx = data_indices_[i];
+      tmp_sum_gradients += gradients[idx];
+      tmp_sum_hessians += hessians[idx];
     }
+    sum_gradients_ = tmp_sum_gradients;
+    sum_hessians_ = tmp_sum_hessians;
   }