334 lines
12 KiB
C++
334 lines
12 KiB
C++
/*!
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* \file
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* \brief Distributed sort implementation header
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*
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* \author
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* Christos Choutouridis AEM:8997
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* <cchoutou@ece.auth.gr>
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*/
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#ifndef DISTBITONIC_H_
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#define DISTBITONIC_H_
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#include <vector>
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#include <algorithm>
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//#include <parallel/algorithm>
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#include <cmath>
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#include <cstdint>
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#if !defined DEBUG
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#define NDEBUG
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#endif
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#include <cassert>
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#include "utils.hpp"
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extern Timing TfullSort, Texchange, Tminmax, TelbowSort;
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/*!
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* Enumerator for the different versions of the sorting method
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*/
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enum class SortMode {
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Bubbletonic, //!< The v0.5 of the algorithm where we use a bubble-sort like approach
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Bitonic //!< The v1.0 of the algorithm where we use the bitonic data-exchange approach
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};
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/*
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* ============================== Sort utilities ==============================
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*/
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/*!
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* The primary function template of ascending(). It is DISABLED since , it is explicitly specialized
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* for each of the \c SortMode
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*/
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template <SortMode Mode> inline bool ascending(mpi_id_t, [[maybe_unused]] size_t) noexcept = delete;
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/*!
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* Returns the ascending or descending configuration of the node's sequence based on
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* the current node (MPI process) and the depth of the sorting network
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*
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* @param node [mpi_id_t] The current node (MPI process)
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* @return [bool] True if we need ascending configuration, false otherwise
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*/
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template <> inline
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bool ascending<SortMode::Bubbletonic>(mpi_id_t node, [[maybe_unused]] size_t depth) noexcept {
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return (node % 2) == 0;
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}
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/*!
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* Returns the ascending or descending configuration of the node's sequence based on
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* the current node (MPI process) and the depth of the sorting network
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*
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* @param node [mpi_id_t] The current node (MPI process)
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* @param depth [size_t] The total depth of the sorting network (same for each step for a given network)
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* @return [bool] True if we need ascending configuration, false otherwise
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*/
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template <> inline
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bool ascending<SortMode::Bitonic>(mpi_id_t node, size_t depth) noexcept {
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return !(node & (1 << depth));
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}
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/*!
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* The primary function template of partner(). It is DISABLED since , it is explicitly specialized
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* for each of the \c SortMode
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*/
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template <SortMode Mode> inline mpi_id_t partner(mpi_id_t, size_t) noexcept = delete;
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/*!
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* Returns the node's partner for data exchange during the sorting network iterations
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* of Bubbletonic
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*
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* @param node [mpi_id_t] The current node
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* @param step [size_t] The step of the sorting network
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* @return [mpi_id_t] The node id of the partner for data exchange
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*/
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template <> inline
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mpi_id_t partner<SortMode::Bubbletonic>(mpi_id_t node, size_t step) noexcept {
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//return (node % 2 == step % 2) ? node + 1 : node - 1;
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return (((node+step) % 2) == 0) ? node + 1 : node - 1;
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}
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/*!
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* Returns the node's partner for data exchange during the sorting network iterations
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* of Bitonic
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*
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* @param node [mpi_id_t] The current node
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* @param step [size_t] The step of the sorting network
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* @return [mpi_id_t] The node id of the partner for data exchange
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*/
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template <> inline
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mpi_id_t partner<SortMode::Bitonic>(mpi_id_t node, size_t step) noexcept {
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return (node ^ (1 << step));
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}
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/*!
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* The primary function template of keepSmall(). It is DISABLED since , it is explicitly specialized
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* for each of the \c SortMode
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*/
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template<SortMode Mode> inline bool keepSmall(mpi_id_t, mpi_id_t, [[maybe_unused]] size_t) = delete;
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/*!
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* Predicate to check if a node keeps the small numbers during the bubbletonic sort network exchange.
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*
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* @param node [mpi_id_t] The node for which we check
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* @param partner [mpi_id_t] The partner of the data exchange
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* @return [bool] True if the node should keep the small values, false otherwise
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*/
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template <> inline
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bool keepSmall<SortMode::Bubbletonic>(mpi_id_t node, mpi_id_t partner, [[maybe_unused]] size_t depth) {
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if (node == partner)
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throw std::runtime_error("(keepSmall) Node and Partner can not be the same\n");
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return (node < partner);
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}
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/*!
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* Predicate to check if a node keeps the small numbers during the bitonic sort network exchange.
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*
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* @param node [mpi_id_t] The node for which we check
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* @param partner [mpi_id_t] The partner of the data exchange
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* @param depth [size_t] The total depth of the sorting network (same for each step for a given network)
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* @return [bool] True if the node should keep the small values, false otherwise
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*/
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template <> inline
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bool keepSmall<SortMode::Bitonic>(mpi_id_t node, mpi_id_t partner, size_t depth) {
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if (node == partner)
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throw std::runtime_error("(keepSmall) Node and Partner can not be the same\n");
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return ascending<SortMode::Bitonic>(node, depth) == (node < partner);
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}
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/*!
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* Predicate to check if the node is active in the current iteration of the bubbletonic
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* sort exchange.
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*
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* @param node [mpi_id_t] The node to check
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* @param nodes [size_t] The total number of nodes
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* @return [bool] True if the node is active, false otherwise
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*/
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bool isActive(mpi_id_t node, size_t nodes);
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/*
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* ============================== Data utilities ==============================
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*/
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/*!
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* Sort a range using the build-in O(Nlog(N)) algorithm
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*
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* @tparam RangeT A range type with random access iterator
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*
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* @param data [RangeT] The data to be sorted
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* @param ascending [bool] Flag to indicate the sorting order
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*/
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template<typename RangeT>
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void fullSort(RangeT& data, bool ascending) noexcept {
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// Use introsort from stdlib++ here, unless ... __gnu_parallel
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if (ascending) {
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std::sort(data.begin(), data.end(), std::less<>());
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}
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else {
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std::sort(data.begin(), data.end(), std::greater<>());
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}
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}
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/*!
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* Core functionality of sort for shadowed buffer types using
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* the "elbow sort" algorithm.
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*
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* @note:
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* This algorithm can not work "in place".
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* We use the active buffer as source and the shadow as target.
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* At the end we switch which buffer is active and which is the shadow.
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* @note
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* This is the core functionality. Use the elbowSort() function instead
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*
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* @tparam ShadowedDataT A Shadowed buffer type with random access iterator.
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* @tparam CompT A Comparison type for binary operation comparisons
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*
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* @param data [ShadowedDataT] The data to sort
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* @param ascending [bool] Flag to indicate the sorting order
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* @param comp [CompT] The binary operator object
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*/
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template<typename ShadowedDataT, typename CompT>
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void elbowSortCore(ShadowedDataT& data, bool ascending, CompT comp) noexcept {
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auto& active = data.getActive(); // Get the source vector (the data to sort)
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auto& shadow = data.getShadow(); // Get the target vector (the sorted data)
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size_t N = data.size(); // The total size is the same or both vectors
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size_t left = std::distance(
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active.begin(),
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(ascending) ?
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std::min_element(active.begin(), active.end()) :
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std::max_element(active.begin(), active.end())
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); // start 'left' from elbow of the bitonic
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size_t right = (left == N-1) ? 0 : left + 1;
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// Walk in opposite directions from elbow and insert-sort to target vector
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for (size_t i = 0 ; i<N ; ++i) {
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if (comp(active[left], active[right])) {
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shadow[i] = active[left];
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left = (left == 0) ? N-1 : left -1; // cycle decrease
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}
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else {
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shadow[i] = active[right];
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right = (right + 1) % N; // cycle increase
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}
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}
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data.switch_active(); // Switch active-shadow buffers
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}
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/*!
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* Sort a shadowed buffer using the "elbow sort" algorithm.
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*
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* @tparam ShadowedDataT A Shadowed buffer type with random access iterator.
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*
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* @param data [ShadowedDataT] The data to sort
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* @param ascending [bool] Flag to indicate the sorting order
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*/
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template<typename ShadowedDataT>
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void elbowSort(ShadowedDataT& data, bool ascending) noexcept {
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if (ascending)
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elbowSortCore(data, ascending, std::less<>());
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else
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elbowSortCore(data, ascending, std::greater<>());
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}
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/*!
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* Takes two sorted sequences where one is in increasing and the other is in decreasing order
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* and selects either the larger or the smaller items in one-to-one comparison between them.
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* The result is a bitonic sequence.
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*
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* @tparam RangeT A range type with random access iterator
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*
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* @param local [RangeT] Reference to the local sequence
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* @param remote [const RangeT] Reference to the remote sequence (copied locally by MPI)
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* @param keepSmall [bool] Flag to indicate if we keep the small items in local sequence
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*/
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template<typename RangeT>
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void minmax(RangeT& local, const RangeT& remote, bool keepSmall) noexcept {
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using value_t = typename RangeT::value_type;
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std::transform(
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local.begin(), local.end(),
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remote.begin(),
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local.begin(),
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[&keepSmall](const value_t& a, const value_t& b){
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return (keepSmall) ? std::min(a, b) : std::max(a, b);
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});
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}
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/*
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* ============================== Sort algorithms ==============================
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*/
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/*!
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* A distributed version of the Bubbletonic sort algorithm.
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*
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* @note
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* Each MPI process should run an instance of this function.
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*
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* @tparam ShadowedDataT A Shadowed buffer type with random access iterator.
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*
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* @param data [ShadowedDataT] The local to MPI process data to sort
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* @param Processes [mpi_id_t] The total number of MPI processes
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* @param rank [mpi_id_t] The current process id
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*/
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template<typename ShadowedDataT>
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void distBubbletonic(ShadowedDataT& data, mpi_id_t Processes, mpi_id_t rank) {
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// Initially sort to create a half part of a bitonic sequence
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timeCall(TfullSort, fullSort, data, ascending<SortMode::Bubbletonic>(rank, 0));
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// Sort network (O(N) iterations)
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for (size_t step = 0; step < static_cast<size_t>(Processes); ++step) {
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// Find out exchange configuration
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auto part = partner<SortMode::Bubbletonic>(rank, step);
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auto ks = keepSmall<SortMode::Bubbletonic>(rank, part, Processes);
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if ( isActive(rank, Processes) &&
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isActive(part, Processes) ) {
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// Exchange with partner, keep nim-or-max and sort - O(N)
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timeCall(Texchange, mpi.exchange, data.getActive(), data.getShadow(), part, step);
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timeCall(Tminmax, minmax, data.getActive(), data.getShadow(), ks);
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timeCall(TelbowSort, elbowSort, data, ascending<SortMode::Bubbletonic>(rank, Processes));
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}
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}
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// Invert if the node was descending.
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if (!ascending<SortMode::Bubbletonic>(rank, 0))
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elbowSort(data, true);
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}
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/*!
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* A distributed version of the Bitonic sort algorithm.
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*
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* @note
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* Each MPI process should run an instance of this function.
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*
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* @tparam ShadowedDataT A Shadowed buffer type with random access iterator.
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*
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* @param data [ShadowedDataT] The local to MPI process data to sort
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* @param Processes [mpi_id_t] The total number of MPI processes
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* @param rank [mpi_id_t] The current process id
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*/
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template<typename ShadowedDataT>
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void distBitonic(ShadowedDataT& data, mpi_id_t Processes, mpi_id_t rank) {
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// Initially sort to create a half part of a bitonic sequence
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timeCall(TfullSort, fullSort, data, ascending<SortMode::Bitonic>(rank, 0));
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// Run through sort network using elbow-sort ( O(LogN * LogN) iterations )
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auto p = static_cast<uint32_t>(std::log2(Processes));
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for (size_t depth = 1; depth <= p; ++depth) {
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for (size_t step = depth; step > 0;) {
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--step;
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// Find out exchange configuration
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auto part = partner<SortMode::Bitonic>(rank, step);
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auto ks = keepSmall<SortMode::Bitonic>(rank, part, depth);
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// Exchange with partner, keep nim-or-max
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timeCall(Texchange, mpi.exchange, data.getActive(), data.getShadow(), part, (depth << 8) | step);
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timeCall(Tminmax, minmax, data.getActive(), data.getShadow(), ks);
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}
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// sort - O(N)
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timeCall(TelbowSort, elbowSort, data, ascending<SortMode::Bitonic>(rank, depth));
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}
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}
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#endif //DISTBITONIC_H_
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