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537 lines
22 KiB
C++
537 lines
22 KiB
C++
/*
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pdqsort.h - Pattern-defeating quicksort.
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Copyright (c) 2015 Orson Peters
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This software is provided 'as-is', without any express or implied warranty. In no event will the
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authors be held liable for any damages arising from the use of this software.
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Permission is granted to anyone to use this software for any purpose, including commercial
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applications, and to alter it and redistribute it freely, subject to the following restrictions:
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1. The origin of this software must not be misrepresented; you must not claim that you wrote the
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original software. If you use this software in a product, an acknowledgment in the product
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documentation would be appreciated but is not required.
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2. Altered source versions must be plainly marked as such, and must not be misrepresented as
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being the original software.
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3. This notice may not be removed or altered from any source distribution.
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*/
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#ifndef TRACY_PDQSORT_H
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#define TRACY_PDQSORT_H
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#include "../common/TracyForceInline.hpp"
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#include <algorithm>
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#include <cstddef>
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#include <functional>
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#include <utility>
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#include <iterator>
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#include <cstdint>
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#include <type_traits>
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#define PDQSORT_PREFER_MOVE(x) std::move(x)
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namespace tracy{
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namespace pdqsort_detail {
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enum {
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// Partitions below this size are sorted using insertion sort.
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insertion_sort_threshold = 24,
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// Partitions above this size use Tukey's ninther to select the pivot.
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ninther_threshold = 128,
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// When we detect an already sorted partition, attempt an insertion sort that allows this
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// amount of element moves before giving up.
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partial_insertion_sort_limit = 8,
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// Must be multiple of 8 due to loop unrolling, and < 256 to fit in unsigned char.
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block_size = 64,
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// Cacheline size, assumes power of two.
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cacheline_size = 64
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};
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template<class T> struct is_default_compare : std::false_type { };
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template<class T> struct is_default_compare<std::less<T>> : std::true_type { };
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template<class T> struct is_default_compare<std::greater<T>> : std::true_type { };
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// Returns floor(log2(n)), assumes n > 0.
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template<class T>
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tracy_force_inline int log2(T n) {
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int log = 0;
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while (n >>= 1) ++log;
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return log;
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}
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// Sorts [begin, end) using insertion sort with the given comparison function.
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template<class Iter, class Compare>
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tracy_force_inline void insertion_sort(Iter begin, Iter end, Compare comp) {
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typedef typename std::iterator_traits<Iter>::value_type T;
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if (begin == end) return;
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for (Iter cur = begin + 1; cur != end; ++cur) {
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Iter sift = cur;
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Iter sift_1 = cur - 1;
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// Compare first so we can avoid 2 moves for an element already positioned correctly.
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if (comp(*sift, *sift_1)) {
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T tmp = PDQSORT_PREFER_MOVE(*sift);
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do { *sift-- = PDQSORT_PREFER_MOVE(*sift_1); }
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while (sift != begin && comp(tmp, *--sift_1));
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*sift = PDQSORT_PREFER_MOVE(tmp);
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}
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}
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}
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// Sorts [begin, end) using insertion sort with the given comparison function. Assumes
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// *(begin - 1) is an element smaller than or equal to any element in [begin, end).
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template<class Iter, class Compare>
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tracy_force_inline void unguarded_insertion_sort(Iter begin, Iter end, Compare comp) {
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typedef typename std::iterator_traits<Iter>::value_type T;
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if (begin == end) return;
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for (Iter cur = begin + 1; cur != end; ++cur) {
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Iter sift = cur;
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Iter sift_1 = cur - 1;
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// Compare first so we can avoid 2 moves for an element already positioned correctly.
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if (comp(*sift, *sift_1)) {
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T tmp = PDQSORT_PREFER_MOVE(*sift);
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do { *sift-- = PDQSORT_PREFER_MOVE(*sift_1); }
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while (comp(tmp, *--sift_1));
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*sift = PDQSORT_PREFER_MOVE(tmp);
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}
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}
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}
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// Attempts to use insertion sort on [begin, end). Will return false if more than
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// partial_insertion_sort_limit elements were moved, and abort sorting. Otherwise it will
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// successfully sort and return true.
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template<class Iter, class Compare>
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tracy_force_inline bool partial_insertion_sort(Iter begin, Iter end, Compare comp) {
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typedef typename std::iterator_traits<Iter>::value_type T;
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if (begin == end) return true;
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int limit = 0;
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for (Iter cur = begin + 1; cur != end; ++cur) {
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if (limit > partial_insertion_sort_limit) return false;
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Iter sift = cur;
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Iter sift_1 = cur - 1;
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// Compare first so we can avoid 2 moves for an element already positioned correctly.
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if (comp(*sift, *sift_1)) {
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T tmp = PDQSORT_PREFER_MOVE(*sift);
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do { *sift-- = PDQSORT_PREFER_MOVE(*sift_1); }
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while (sift != begin && comp(tmp, *--sift_1));
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*sift = PDQSORT_PREFER_MOVE(tmp);
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limit += cur - sift;
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}
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}
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return true;
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}
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template<class Iter, class Compare>
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tracy_force_inline void sort2(Iter a, Iter b, Compare comp) {
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if (comp(*b, *a)) std::iter_swap(a, b);
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}
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// Sorts the elements *a, *b and *c using comparison function comp.
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template<class Iter, class Compare>
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tracy_force_inline void sort3(Iter a, Iter b, Iter c, Compare comp) {
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sort2(a, b, comp);
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sort2(b, c, comp);
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sort2(a, b, comp);
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}
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template<class T>
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tracy_force_inline T* align_cacheline(T* p) {
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#if defined(UINTPTR_MAX)
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std::uintptr_t ip = reinterpret_cast<std::uintptr_t>(p);
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#else
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std::size_t ip = reinterpret_cast<std::size_t>(p);
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#endif
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ip = (ip + cacheline_size - 1) & -cacheline_size;
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return reinterpret_cast<T*>(ip);
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}
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template<class Iter>
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tracy_force_inline void swap_offsets(Iter first, Iter last,
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unsigned char* offsets_l, unsigned char* offsets_r,
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int num, bool use_swaps) {
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typedef typename std::iterator_traits<Iter>::value_type T;
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if (use_swaps) {
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// This case is needed for the descending distribution, where we need
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// to have proper swapping for pdqsort to remain O(n).
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for (int i = 0; i < num; ++i) {
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std::iter_swap(first + offsets_l[i], last - offsets_r[i]);
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}
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} else if (num > 0) {
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Iter l = first + offsets_l[0]; Iter r = last - offsets_r[0];
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T tmp(PDQSORT_PREFER_MOVE(*l)); *l = PDQSORT_PREFER_MOVE(*r);
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for (int i = 1; i < num; ++i) {
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l = first + offsets_l[i]; *r = PDQSORT_PREFER_MOVE(*l);
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r = last - offsets_r[i]; *l = PDQSORT_PREFER_MOVE(*r);
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}
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*r = PDQSORT_PREFER_MOVE(tmp);
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}
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}
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// Partitions [begin, end) around pivot *begin using comparison function comp. Elements equal
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// to the pivot are put in the right-hand partition. Returns the position of the pivot after
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// partitioning and whether the passed sequence already was correctly partitioned. Assumes the
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// pivot is a median of at least 3 elements and that [begin, end) is at least
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// insertion_sort_threshold long. Uses branchless partitioning.
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template<class Iter, class Compare>
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tracy_force_inline std::pair<Iter, bool> partition_right_branchless(Iter begin, Iter end, Compare comp) {
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typedef typename std::iterator_traits<Iter>::value_type T;
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// Move pivot into local for speed.
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T pivot(PDQSORT_PREFER_MOVE(*begin));
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Iter first = begin;
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Iter last = end;
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// Find the first element greater than or equal than the pivot (the median of 3 guarantees
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// this exists).
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while (comp(*++first, pivot));
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// Find the first element strictly smaller than the pivot. We have to guard this search if
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// there was no element before *first.
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if (first - 1 == begin) while (first < last && !comp(*--last, pivot));
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else while ( !comp(*--last, pivot));
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// If the first pair of elements that should be swapped to partition are the same element,
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// the passed in sequence already was correctly partitioned.
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bool already_partitioned = first >= last;
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if (!already_partitioned) {
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std::iter_swap(first, last);
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++first;
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}
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// The following branchless partitioning is derived from "BlockQuicksort: How Branch
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// Mispredictions don’t affect Quicksort" by Stefan Edelkamp and Armin Weiss.
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unsigned char offsets_l_storage[block_size + cacheline_size];
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unsigned char offsets_r_storage[block_size + cacheline_size];
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unsigned char* offsets_l = align_cacheline(offsets_l_storage);
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unsigned char* offsets_r = align_cacheline(offsets_r_storage);
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int num_l, num_r, start_l, start_r;
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num_l = num_r = start_l = start_r = 0;
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while (last - first > 2 * block_size) {
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// Fill up offset blocks with elements that are on the wrong side.
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if (num_l == 0) {
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start_l = 0;
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Iter it = first;
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for (unsigned char i = 0; i < block_size;) {
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offsets_l[num_l] = i++; num_l += !comp(*it, pivot); ++it;
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offsets_l[num_l] = i++; num_l += !comp(*it, pivot); ++it;
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offsets_l[num_l] = i++; num_l += !comp(*it, pivot); ++it;
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offsets_l[num_l] = i++; num_l += !comp(*it, pivot); ++it;
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offsets_l[num_l] = i++; num_l += !comp(*it, pivot); ++it;
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offsets_l[num_l] = i++; num_l += !comp(*it, pivot); ++it;
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offsets_l[num_l] = i++; num_l += !comp(*it, pivot); ++it;
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offsets_l[num_l] = i++; num_l += !comp(*it, pivot); ++it;
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}
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}
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if (num_r == 0) {
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start_r = 0;
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Iter it = last;
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for (unsigned char i = 0; i < block_size;) {
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offsets_r[num_r] = ++i; num_r += comp(*--it, pivot);
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offsets_r[num_r] = ++i; num_r += comp(*--it, pivot);
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offsets_r[num_r] = ++i; num_r += comp(*--it, pivot);
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offsets_r[num_r] = ++i; num_r += comp(*--it, pivot);
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offsets_r[num_r] = ++i; num_r += comp(*--it, pivot);
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offsets_r[num_r] = ++i; num_r += comp(*--it, pivot);
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offsets_r[num_r] = ++i; num_r += comp(*--it, pivot);
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offsets_r[num_r] = ++i; num_r += comp(*--it, pivot);
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}
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}
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// Swap elements and update block sizes and first/last boundaries.
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int num = std::min(num_l, num_r);
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swap_offsets(first, last, offsets_l + start_l, offsets_r + start_r,
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num, num_l == num_r);
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num_l -= num; num_r -= num;
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start_l += num; start_r += num;
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if (num_l == 0) first += block_size;
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if (num_r == 0) last -= block_size;
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}
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int l_size = 0, r_size = 0;
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int unknown_left = (last - first) - ((num_r || num_l) ? block_size : 0);
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if (num_r) {
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// Handle leftover block by assigning the unknown elements to the other block.
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l_size = unknown_left;
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r_size = block_size;
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} else if (num_l) {
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l_size = block_size;
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r_size = unknown_left;
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} else {
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// No leftover block, split the unknown elements in two blocks.
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l_size = unknown_left/2;
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r_size = unknown_left - l_size;
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}
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// Fill offset buffers if needed.
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if (unknown_left && !num_l) {
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start_l = 0;
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Iter it = first;
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for (unsigned char i = 0; i < l_size;) {
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offsets_l[num_l] = i++; num_l += !comp(*it, pivot); ++it;
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}
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}
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if (unknown_left && !num_r) {
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start_r = 0;
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Iter it = last;
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for (unsigned char i = 0; i < r_size;) {
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offsets_r[num_r] = ++i; num_r += comp(*--it, pivot);
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}
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}
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int num = std::min(num_l, num_r);
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swap_offsets(first, last, offsets_l + start_l, offsets_r + start_r, num, num_l == num_r);
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num_l -= num; num_r -= num;
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start_l += num; start_r += num;
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if (num_l == 0) first += l_size;
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if (num_r == 0) last -= r_size;
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// We have now fully identified [first, last)'s proper position. Swap the last elements.
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if (num_l) {
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offsets_l += start_l;
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while (num_l--) std::iter_swap(first + offsets_l[num_l], --last);
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first = last;
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}
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if (num_r) {
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offsets_r += start_r;
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while (num_r--) std::iter_swap(last - offsets_r[num_r], first), ++first;
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last = first;
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}
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// Put the pivot in the right place.
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Iter pivot_pos = first - 1;
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*begin = PDQSORT_PREFER_MOVE(*pivot_pos);
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*pivot_pos = PDQSORT_PREFER_MOVE(pivot);
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return std::make_pair(pivot_pos, already_partitioned);
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}
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// Partitions [begin, end) around pivot *begin using comparison function comp. Elements equal
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// to the pivot are put in the right-hand partition. Returns the position of the pivot after
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// partitioning and whether the passed sequence already was correctly partitioned. Assumes the
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// pivot is a median of at least 3 elements and that [begin, end) is at least
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// insertion_sort_threshold long.
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template<class Iter, class Compare>
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tracy_force_inline std::pair<Iter, bool> partition_right(Iter begin, Iter end, Compare comp) {
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typedef typename std::iterator_traits<Iter>::value_type T;
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// Move pivot into local for speed.
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T pivot(PDQSORT_PREFER_MOVE(*begin));
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Iter first = begin;
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Iter last = end;
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// Find the first element greater than or equal than the pivot (the median of 3 guarantees
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// this exists).
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while (comp(*++first, pivot));
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// Find the first element strictly smaller than the pivot. We have to guard this search if
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// there was no element before *first.
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if (first - 1 == begin) while (first < last && !comp(*--last, pivot));
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else while ( !comp(*--last, pivot));
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// If the first pair of elements that should be swapped to partition are the same element,
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// the passed in sequence already was correctly partitioned.
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bool already_partitioned = first >= last;
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// Keep swapping pairs of elements that are on the wrong side of the pivot. Previously
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// swapped pairs guard the searches, which is why the first iteration is special-cased
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// above.
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while (first < last) {
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std::iter_swap(first, last);
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while (comp(*++first, pivot));
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while (!comp(*--last, pivot));
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}
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// Put the pivot in the right place.
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Iter pivot_pos = first - 1;
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*begin = PDQSORT_PREFER_MOVE(*pivot_pos);
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*pivot_pos = PDQSORT_PREFER_MOVE(pivot);
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return std::make_pair(pivot_pos, already_partitioned);
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}
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// Similar function to the one above, except elements equal to the pivot are put to the left of
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// the pivot and it doesn't check or return if the passed sequence already was partitioned.
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// Since this is rarely used (the many equal case), and in that case pdqsort already has O(n)
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// performance, no block quicksort is applied here for simplicity.
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template<class Iter, class Compare>
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tracy_force_inline Iter partition_left(Iter begin, Iter end, Compare comp) {
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typedef typename std::iterator_traits<Iter>::value_type T;
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T pivot(PDQSORT_PREFER_MOVE(*begin));
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Iter first = begin;
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Iter last = end;
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while (comp(pivot, *--last));
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if (last + 1 == end) while (first < last && !comp(pivot, *++first));
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else while ( !comp(pivot, *++first));
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while (first < last) {
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std::iter_swap(first, last);
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while (comp(pivot, *--last));
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while (!comp(pivot, *++first));
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}
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Iter pivot_pos = last;
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*begin = PDQSORT_PREFER_MOVE(*pivot_pos);
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*pivot_pos = PDQSORT_PREFER_MOVE(pivot);
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return pivot_pos;
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}
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template<class Iter, class Compare, bool Branchless>
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inline void pdqsort_loop(Iter begin, Iter end, Compare comp, int bad_allowed, bool leftmost = true) {
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typedef typename std::iterator_traits<Iter>::difference_type diff_t;
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// Use a while loop for tail recursion elimination.
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while (true) {
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diff_t size = end - begin;
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// Insertion sort is faster for small arrays.
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if (size < insertion_sort_threshold) {
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if (leftmost) insertion_sort(begin, end, comp);
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else unguarded_insertion_sort(begin, end, comp);
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return;
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}
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// Choose pivot as median of 3 or pseudomedian of 9.
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diff_t s2 = size / 2;
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if (size > ninther_threshold) {
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sort3(begin, begin + s2, end - 1, comp);
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sort3(begin + 1, begin + (s2 - 1), end - 2, comp);
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sort3(begin + 2, begin + (s2 + 1), end - 3, comp);
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sort3(begin + (s2 - 1), begin + s2, begin + (s2 + 1), comp);
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std::iter_swap(begin, begin + s2);
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} else sort3(begin + s2, begin, end - 1, comp);
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// If *(begin - 1) is the end of the right partition of a previous partition operation
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// there is no element in [begin, end) that is smaller than *(begin - 1). Then if our
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// pivot compares equal to *(begin - 1) we change strategy, putting equal elements in
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// the left partition, greater elements in the right partition. We do not have to
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// recurse on the left partition, since it's sorted (all equal).
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if (!leftmost && !comp(*(begin - 1), *begin)) {
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begin = partition_left(begin, end, comp) + 1;
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continue;
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}
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// Partition and get results.
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std::pair<Iter, bool> part_result =
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Branchless ? partition_right_branchless(begin, end, comp)
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: partition_right(begin, end, comp);
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Iter pivot_pos = part_result.first;
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bool already_partitioned = part_result.second;
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// Check for a highly unbalanced partition.
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diff_t l_size = pivot_pos - begin;
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||
diff_t r_size = end - (pivot_pos + 1);
|
||
bool highly_unbalanced = l_size < size / 8 || r_size < size / 8;
|
||
|
||
// If we got a highly unbalanced partition we shuffle elements to break many patterns.
|
||
if (highly_unbalanced) {
|
||
// If we had too many bad partitions, switch to heapsort to guarantee O(n log n).
|
||
if (--bad_allowed == 0) {
|
||
std::make_heap(begin, end, comp);
|
||
std::sort_heap(begin, end, comp);
|
||
return;
|
||
}
|
||
|
||
if (l_size >= insertion_sort_threshold) {
|
||
std::iter_swap(begin, begin + l_size / 4);
|
||
std::iter_swap(pivot_pos - 1, pivot_pos - l_size / 4);
|
||
|
||
if (l_size > ninther_threshold) {
|
||
std::iter_swap(begin + 1, begin + (l_size / 4 + 1));
|
||
std::iter_swap(begin + 2, begin + (l_size / 4 + 2));
|
||
std::iter_swap(pivot_pos - 2, pivot_pos - (l_size / 4 + 1));
|
||
std::iter_swap(pivot_pos - 3, pivot_pos - (l_size / 4 + 2));
|
||
}
|
||
}
|
||
|
||
if (r_size >= insertion_sort_threshold) {
|
||
std::iter_swap(pivot_pos + 1, pivot_pos + (1 + r_size / 4));
|
||
std::iter_swap(end - 1, end - r_size / 4);
|
||
|
||
if (r_size > ninther_threshold) {
|
||
std::iter_swap(pivot_pos + 2, pivot_pos + (2 + r_size / 4));
|
||
std::iter_swap(pivot_pos + 3, pivot_pos + (3 + r_size / 4));
|
||
std::iter_swap(end - 2, end - (1 + r_size / 4));
|
||
std::iter_swap(end - 3, end - (2 + r_size / 4));
|
||
}
|
||
}
|
||
} else {
|
||
// If we were decently balanced and we tried to sort an already partitioned
|
||
// sequence try to use insertion sort.
|
||
if (already_partitioned && partial_insertion_sort(begin, pivot_pos, comp)
|
||
&& partial_insertion_sort(pivot_pos + 1, end, comp)) return;
|
||
}
|
||
|
||
// Sort the left partition first using recursion and do tail recursion elimination for
|
||
// the right-hand partition.
|
||
pdqsort_loop<Iter, Compare, Branchless>(begin, pivot_pos, comp, bad_allowed, leftmost);
|
||
begin = pivot_pos + 1;
|
||
leftmost = false;
|
||
}
|
||
}
|
||
}
|
||
|
||
|
||
template<class Iter, class Compare>
|
||
inline void pdqsort(Iter begin, Iter end, Compare comp) {
|
||
if (begin == end) return;
|
||
pdqsort_detail::pdqsort_loop<Iter, Compare,
|
||
pdqsort_detail::is_default_compare<typename std::decay<Compare>::type>::value &&
|
||
std::is_arithmetic<typename std::iterator_traits<Iter>::value_type>::value>(
|
||
begin, end, comp, pdqsort_detail::log2(end - begin));
|
||
}
|
||
|
||
template<class Iter>
|
||
inline void pdqsort(Iter begin, Iter end) {
|
||
typedef typename std::iterator_traits<Iter>::value_type T;
|
||
pdqsort(begin, end, std::less<T>());
|
||
}
|
||
|
||
template<class Iter, class Compare>
|
||
inline void pdqsort_branchless(Iter begin, Iter end, Compare comp) {
|
||
if (begin == end) return;
|
||
pdqsort_detail::pdqsort_loop<Iter, Compare, true>(
|
||
begin, end, comp, pdqsort_detail::log2(end - begin));
|
||
}
|
||
|
||
template<class Iter>
|
||
tracy_force_inline void pdqsort_branchless(Iter begin, Iter end) {
|
||
typedef typename std::iterator_traits<Iter>::value_type T;
|
||
pdqsort_branchless(begin, end, std::less<T>());
|
||
}
|
||
|
||
}
|
||
|
||
#undef PDQSORT_PREFER_MOVE
|
||
|
||
#endif
|