kdtree_omp.hpp

Go to the documentation of this file.

// SPDX-FileCopyrightText: Copyright 2024 Kenji Koide
// SPDX-License-Identifier: MIT
#pragma once
 
#include <atomic>
#include <small_gicp/ann/kdtree.hpp>
 
#ifdef _MSC_VER
#pragma message("warning: Task-based OpenMP parallelism causes run-time memory errors with Eigen matrices.")
#pragma message("warning: Thus, OpenMP-based multi-threading for KdTree construction is disabled on MSVC.")
#endif
 
namespace small_gicp {
 
struct KdTreeBuilderOMP {
public:
  KdTreeBuilderOMP(int num_threads = 4) : num_threads(num_threads), max_leaf_size(20) {}
 
  template <typename KdTree, typename PointCloud>
  void build_tree(KdTree& kdtree, const PointCloud& points) const {
    kdtree.indices.resize(traits::size(points));
    std::iota(kdtree.indices.begin(), kdtree.indices.end(), 0);
 
    std::atomic_uint64_t node_count = 0;
    kdtree.nodes.resize(traits::size(points));
 
#ifndef _MSC_VER
#pragma omp parallel num_threads(num_threads)
    {
#pragma omp single nowait
      { kdtree.root = create_node(kdtree, node_count, points, kdtree.indices.begin(), kdtree.indices.begin(), kdtree.indices.end()); }
    }
#else
    kdtree.root = create_node(kdtree, node_count, points, kdtree.indices.begin(), kdtree.indices.begin(), kdtree.indices.end());
#endif
 
    kdtree.nodes.resize(node_count);
  }
 
  template <typename PointCloud, typename KdTree, typename IndexConstIterator>
  NodeIndexType create_node(
    KdTree& kdtree,
    std::atomic_uint64_t& node_count,
    const PointCloud& points,
    IndexConstIterator global_first,
    IndexConstIterator first,
    IndexConstIterator last) const {
    const size_t N = std::distance(first, last);
    const NodeIndexType node_index = node_count++;
    auto& node = kdtree.nodes[node_index];
 
    // Create a leaf node.
    if (N <= max_leaf_size) {
      // std::sort(first, last);
      node.node_type.lr.first = std::distance(global_first, first);
      node.node_type.lr.last = std::distance(global_first, last);
 
      return node_index;
    }
 
    // Find the best axis to split the input points.
    using Projection = typename KdTree::Projection;
    const auto proj = Projection::find_axis(points, first, last, projection_setting);
    const auto median_itr = first + N / 2;
    std::nth_element(first, median_itr, last, [&](size_t i, size_t j) { return proj(traits::point(points, i)) < proj(traits::point(points, j)); });
 
    // Create a non-leaf node.
    node.node_type.sub.proj = proj;
    node.node_type.sub.thresh = proj(traits::point(points, *median_itr));
 
    // Create left and right child nodes.
#ifndef _MSC_VER
#pragma omp task default(shared) if (N > 512)
    node.left = create_node(kdtree, node_count, points, global_first, first, median_itr);
#pragma omp task default(shared) if (N > 512)
    node.right = create_node(kdtree, node_count, points, global_first, median_itr, last);
#pragma omp taskwait
#else
    node.left = create_node(kdtree, node_count, points, global_first, first, median_itr);
    node.right = create_node(kdtree, node_count, points, global_first, median_itr, last);
#endif
 
    return node_index;
  }
 
public:
  int num_threads;                       
  int max_leaf_size;                     
  ProjectionSetting projection_setting;  
};
 
}  // namespace small_gicp