taskflow/taskflow/core/algorithm/sort.hpp at master · yhcpp/taskflow · GitHub

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#pragma once

#include "../executor.hpp"

namespace tf {

// threshold whether or not to perform parallel sort

template <typename I>

constexpr size_t parallel_sort_cutoff() {

//using value_type = std::decay_t<decltype(*std::declval())>;

using value_type = typename std::iterator_traits::value_type;

constexpr size_t object_size = sizeof(value_type);

if constexpr(std::is_same_v<value_type, std::string>) {

return 128;

}

else {

if(object_size < 16) return 4096;

else if(object_size < 32) return 2048;

else if(object_size < 64) return 1024;

else if(object_size < 128) return 768;

else if(object_size < 256) return 512;

else if(object_size < 512) return 256;

else return 128;

}

// ----------------------------------------------------------------------------

// pattern-defeating quick sort (pdqsort)

// ----------------------------------------------------------------------------

// Sorts [begin, end) using insertion sort with the given comparison function.

template<typename RandItr, typename Compare>

void insertion_sort(RandItr begin, RandItr end, Compare comp) {

using T = typename std::iterator_traits<RandItr>::value_type;

if (begin == end) {

return;

}

for (RandItr cur = begin + 1; cur != end; ++cur) {

RandItr shift = cur;

RandItr shift_1 = cur - 1;

// Compare first to avoid 2 moves for an element

// already positioned correctly.

if (comp(*shift, *shift_1)) {

T tmp = std::move(*shift);

do {

*shift-- = std::move(*shift_1);

}while (shift != begin && comp(tmp, *--shift_1));

*shift = std::move(tmp);

}

// Sorts [begin, end) using insertion sort with the given comparison function.

// Assumes *(begin - 1) is an element smaller than or equal to any element

// in [begin, end).

template<typename RandItr, typename Compare>

void unguarded_insertion_sort(RandItr begin, RandItr end, Compare comp) {

using T = typename std::iterator_traits<RandItr>::value_type;

if (begin == end) {

return;

}

for (RandItr cur = begin + 1; cur != end; ++cur) {

RandItr shift = cur;

RandItr shift_1 = cur - 1;

// Compare first so we can avoid 2 moves

// for an element already positioned correctly.

if (comp(*shift, *shift_1)) {

T tmp = std::move(*shift);

do {

*shift-- = std::move(*shift_1);

}while (comp(tmp, *--shift_1));

*shift = std::move(tmp);

}

// Attempts to use insertion sort on [begin, end).

// Will return false if more than

// partial_insertion_sort_limit elements were moved,

// and abort sorting. Otherwise it will successfully sort and return true.

template<typename RandItr, typename Compare>

bool partial_insertion_sort(RandItr begin, RandItr end, Compare comp) {

using T = typename std::iterator_traits<RandItr>::value_type;

using D = typename std::iterator_traits<RandItr>::difference_type;

// When we detect an already sorted partition, attempt an insertion sort

// that allows this amount of element moves before giving up.

constexpr auto partial_insertion_sort_limit = D{8};

if (begin == end) return true;

auto limit = D{0};

for (RandItr cur = begin + 1; cur != end; ++cur) {

if (limit > partial_insertion_sort_limit) {

return false;

}

RandItr shift = cur;

RandItr shift_1 = cur - 1;

// Compare first so we can avoid 2 moves

// for an element already positioned correctly.

if (comp(*shift, *shift_1)) {

T tmp = std::move(*shift);

do {

*shift-- = std::move(*shift_1);

}while (shift != begin && comp(tmp, *--shift_1));

*shift = std::move(tmp);

limit += cur - shift;

}

return true;

}

// Partitions [begin, end) around pivot *begin using comparison function comp.

// Elements equal to the pivot are put in the right-hand partition.

// Returns the position of the pivot after partitioning and whether the passed

// sequence already was correctly partitioned.

// Assumes the pivot is a median of at least 3 elements and that [begin, end)

// is at least insertion_sort_threshold long.

template<typename Iter, typename Compare>

std::pair<Iter, bool> partition_right(Iter begin, Iter end, Compare comp) {

using T = typename std::iterator_traits<Iter>::value_type;

// Move pivot into local for speed.

T pivot(std::move(*begin));

Iter first = begin;

Iter last = end;

// Find the first element greater than or equal than the pivot

// (the median of 3 guarantees/ this exists).

while (comp(*++first, pivot));

// Find the first element strictly smaller than the pivot.

// We have to guard this search if there was no element before *first.

if (first - 1 == begin) while (first < last && !comp(*--last, pivot));

else while (!comp(*--last, pivot));

// If the first pair of elements that should be swapped to partition

// are the same element, the passed in sequence already was correctly

// partitioned.

bool already_partitioned = first >= last;

// Keep swapping pairs of elements that are on the wrong side of the pivot.

// Previously swapped pairs guard the searches,

// which is why the first iteration is special-cased above.

while (first < last) {

std::iter_swap(first, last);

while (comp(*++first, pivot));

while (!comp(*--last, pivot));

}

// Put the pivot in the right place.

Iter pivot_pos = first - 1;

*begin = std::move(*pivot_pos);

*pivot_pos = std::move(pivot);

return std::make_pair(pivot_pos, already_partitioned);

}

// Similar function to the one above, except elements equal to the pivot

// are put to the left of the pivot and it doesn't check or return

// if the passed sequence already was partitioned.

// Since this is rarely used (the many equal case),

// and in that case pdqsort already has O(n) performance,

// no block quicksort is applied here for simplicity.

template<typename RandItr, typename Compare>

RandItr partition_left(RandItr begin, RandItr end, Compare comp) {

using T = typename std::iterator_traits<RandItr>::value_type;

T pivot(std::move(*begin));

RandItr first = begin;

RandItr last = end;

while (comp(pivot, *--last));

if (last + 1 == end) {

while (first < last && !comp(pivot, *++first));

}

else {

while (!comp(pivot, *++first));

}

while (first < last) {

std::iter_swap(first, last);

while (comp(pivot, *--last));

while (!comp(pivot, *++first));

}

RandItr pivot_pos = last;

*begin = std::move(*pivot_pos);

*pivot_pos = std::move(pivot);

return pivot_pos;

}

template<typename Iter, typename Compare>

void parallel_pdqsort(

tf::Subflow& sf,

Iter begin, Iter end, Compare comp,

int bad_allowed, bool leftmost = true

) {

// Partitions below this size are sorted sequentially

constexpr auto cutoff = parallel_sort_cutoff<Iter>();

// Partitions below this size are sorted using insertion sort

constexpr auto insertion_sort_threshold = 24;

// Partitions above this size use Tukey's ninther to select the pivot.

constexpr auto ninther_threshold = 128;

//using diff_t = typename std::iterator_traits<Iter>::difference_type;

// Use a while loop for tail recursion elimination.

while (true) {

//diff_t size = end - begin;

size_t size = end - begin;

if(size <= cutoff) {

std::sort(begin, end, comp);

return;

}

//// Insertion sort is faster for small arrays.

//if (size < insertion_sort_threshold) {

// if (leftmost) {

// insertion_sort(begin, end, comp);

// }

// else {

// unguarded_insertion_sort(begin, end, comp);

// }

// return;

//}

// Choose pivot as median of 3 or pseudomedian of 9.

//diff_t s2 = size / 2;

size_t s2 = size >> 1;

if (size > ninther_threshold) {

sort3(begin, begin + s2, end - 1, comp);

sort3(begin + 1, begin + (s2 - 1), end - 2, comp);

sort3(begin + 2, begin + (s2 + 1), end - 3, comp);

sort3(begin + (s2 - 1), begin + s2, begin + (s2 + 1), comp);

std::iter_swap(begin, begin + s2);

}

else {

sort3(begin + s2, begin, end - 1, comp);

}

// If *(begin - 1) is the end of the right partition

// of a previous partition operation, there is no element in [begin, end)

// that is smaller than *(begin - 1).

// Then if our pivot compares equal to *(begin - 1) we change strategy,

// putting equal elements in the left partition,

// greater elements in the right partition.

// We do not have to recurse on the left partition,

// since it's sorted (all equal).

if (!leftmost && !comp(*(begin - 1), *begin)) {

begin = partition_left(begin, end, comp) + 1;

continue;

}

// Partition and get results.

auto pair = partition_right(begin, end, comp);

auto pivot_pos = pair.first;

auto already_partitioned = pair.second;

// Check for a highly unbalanced partition.

//diff_t l_size = pivot_pos - begin;

//diff_t r_size = end - (pivot_pos + 1);

size_t l_size = pivot_pos - begin;

size_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));

}

// decently balanced

else {

// 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.

sf.silent_async(

[&sf, begin, pivot_pos, &comp, bad_allowed, leftmost] () mutable {

parallel_pdqsort(sf, begin, pivot_pos, comp, bad_allowed, leftmost);

}

);

begin = pivot_pos + 1;

leftmost = false;

}

// ----------------------------------------------------------------------------

// 3-way quick sort

// ----------------------------------------------------------------------------

// 3-way quick sort

template <typename RandItr, typename C>

void parallel_3wqsort(tf::Subflow& sf, RandItr first, RandItr last, C compare) {

using namespace std::string_literals;

constexpr auto cutoff = parallel_sort_cutoff<RandItr>();

sort_partition:

if(static_cast<size_t>(last - first) < cutoff) {

std::sort(first, last+1, compare);

return;

}

auto m = pseudo_median_of_nine(first, last, compare);

if(m != first) {

std::iter_swap(first, m);

}

auto l = first;

auto r = last;

auto f = std::next(first, 1);

bool is_swapped_l = false;

bool is_swapped_r = false;

while(f <= r) {

if(compare(*f, *l)) {

is_swapped_l = true;

std::iter_swap(l, f);

l++;

f++;

}

else if(compare(*l, *f)) {

is_swapped_r = true;

std::iter_swap(r, f);

r--;

}

else {

f++;

}

if(l - first > 1 && is_swapped_l) {

//sf.emplace([&](tf::Subflow& sfl) mutable {

// parallel_3wqsort(sfl, first, l-1, compare);

//});

sf.silent_async([&sf, first, l, &compare] () mutable {

parallel_3wqsort(sf, first, l-1, compare);

});

}

if(last - r > 1 && is_swapped_r) {

//sf.emplace([&](tf::Subflow& sfr) mutable {

// parallel_3wqsort(sfr, r+1, last, compare);

//});

//sf.silent_async([&sf, r, last, &compare] () mutable {

// parallel_3wqsort(sf, r+1, last, compare);

//});

first = r+1;

goto sort_partition;

}

//sf.join();

}

// ----------------------------------------------------------------------------

// tf::Taskflow::sort

// ----------------------------------------------------------------------------

// Function: sort

template <typename B, typename E, typename C>

Task FlowBuilder::sort(B&& beg, E&& end, C&& cmp) {

using I = stateful_iterator_t<B, E>;

Task task = emplace(

[b=std::forward(beg),

e=std::forward<E>(end),

c=std::forward<C>(cmp)

] (Subflow& sf) mutable {

// fetch the iterator values

I beg = b;

I end = e;

if(beg == end) {

return;

}

size_t W = sf._executor.num_workers();

size_t N = std::distance(beg, end);

// only myself - no need to spawn another graph

if(W <= 1 || N <= parallel_sort_cutoff()) {

std::sort(beg, end, c);

return;

}

//parallel_3wqsort(sf, beg, end-1, c);

parallel_pdqsort(sf, beg, end, c, log2(end - beg));

sf.join();

});

return task;

}

// Function: sort

template <typename B, typename E>

Task FlowBuilder::sort(B&& beg, E&& end) {

using I = stateful_iterator_t<B, E>;

//using value_type = std::decay_t<decltype(*std::declval())>;

using value_type = typename std::iterator_traits::value_type;

return sort(

std::forward(beg), std::forward<E>(end), std::less<value_type>{}

);

}

} // namespace tf ------------------------------------------------------------

taskflow/taskflow/core/algorithm/sort.hpp at master · yhcpp/taskflow · GitHub

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