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- Add heap_sort and pdqsort to the benchmark.

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- Refactor adaptive_sort and adaptive_merge.
This commit is contained in:
Ion Gaztañaga
2017-12-31 19:32:32 +01:00
parent 26019b37a9
commit e1eec15b1a
11 changed files with 1620 additions and 1094 deletions
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6
include/boost/move/adl_move_swap.hpp
View File

@ -261,6 +261,12 @@ BidirIt2 adl_move_swap_ranges_backward(BidirIt1 first1, BidirIt1 last1, BidirIt2
return last2;
}
template<class ForwardIt1, class ForwardIt2>
void adl_move_iter_swap(ForwardIt1 a, ForwardIt2 b)
{
boost::adl_move_swap(*a, *b);
}
} //namespace boost{
#endif //#ifndef BOOST_MOVE_ADL_MOVE_SWAP_HPP

253
include/boost/move/algo/adaptive_merge.hpp
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@ -18,6 +18,259 @@
namespace boost {
namespace movelib {
///@cond
namespace detail_adaptive {
template<class RandIt, class Compare, class XBuf>
inline void adaptive_merge_combine_blocks( RandIt first
, typename iterator_traits<RandIt>::size_type len1
, typename iterator_traits<RandIt>::size_type len2
, typename iterator_traits<RandIt>::size_type collected
, typename iterator_traits<RandIt>::size_type n_keys
, typename iterator_traits<RandIt>::size_type l_block
, bool use_internal_buf
, bool xbuf_used
, Compare comp
, XBuf & xbuf
)
{
typedef typename iterator_traits<RandIt>::size_type size_type;
size_type const len = len1+len2;
size_type const l_combine = len-collected;
size_type const l_combine1 = len1-collected;
if(n_keys){
RandIt const first_data = first+collected;
RandIt const keys = first;
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A combine: ", len);
if(xbuf_used){
if(xbuf.size() < l_block){
xbuf.initialize_until(l_block, *first);
}
BOOST_ASSERT(xbuf.size() >= l_block);
size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
combine_params( keys, comp, l_combine
, l_combine1, l_block, xbuf
, n_block_a, n_block_b, l_irreg1, l_irreg2); //Outputs
op_merge_blocks_with_buf
(keys, comp, first_data, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp, move_op(), xbuf.data());
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" A mrg xbf: ", len);
}
else{
size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
combine_params( keys, comp, l_combine
, l_combine1, l_block, xbuf
, n_block_a, n_block_b, l_irreg1, l_irreg2); //Outputs
if(use_internal_buf){
op_merge_blocks_with_buf
(keys, comp, first_data, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp, swap_op(), first_data-l_block);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A mrg buf: ", len);
}
else{
merge_blocks_bufferless
(keys, comp, first_data, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" A mrg nbf: ", len);
}
}
}
else{
xbuf.shrink_to_fit(l_block);
if(xbuf.size() < l_block){
xbuf.initialize_until(l_block, *first);
}
size_type *const uint_keys = xbuf.template aligned_trailing<size_type>(l_block);
size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
combine_params( uint_keys, less(), l_combine
, l_combine1, l_block, xbuf
, n_block_a, n_block_b, l_irreg1, l_irreg2, true); //Outputs
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A combine: ", len);
BOOST_ASSERT(xbuf.size() >= l_block);
op_merge_blocks_with_buf
(uint_keys, less(), first, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp, move_op(), xbuf.data());
xbuf.clear();
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" A mrg buf: ", len);
}
}
template<class RandIt, class Compare, class XBuf>
inline void adaptive_merge_final_merge( RandIt first
, typename iterator_traits<RandIt>::size_type len1
, typename iterator_traits<RandIt>::size_type len2
, typename iterator_traits<RandIt>::size_type collected
, typename iterator_traits<RandIt>::size_type l_intbuf
, typename iterator_traits<RandIt>::size_type l_block
, bool use_internal_buf
, bool xbuf_used
, Compare comp
, XBuf & xbuf
)
{
typedef typename iterator_traits<RandIt>::size_type size_type;
(void)l_block;
size_type n_keys = collected-l_intbuf;
size_type len = len1+len2;
if(use_internal_buf){
if(xbuf_used){
xbuf.clear();
//Nothing to do
if(n_keys){
unstable_sort(first, first+n_keys, comp, xbuf);
stable_merge(first, first+n_keys, first+len, comp, xbuf);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A key mrg: ", len);
}
}
else{
xbuf.clear();
unstable_sort(first, first+collected, comp, xbuf);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A k/b srt: ", len);
stable_merge(first, first+collected, first+len, comp, xbuf);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A k/b mrg: ", len);
}
}
else{
xbuf.clear();
unstable_sort(first, first+collected, comp, xbuf);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A k/b srt: ", len);
stable_merge(first, first+collected, first+len1+len2, comp, xbuf);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A k/b mrg: ", len);
}
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" A fin mrg: ", len);
}
template<class SizeType, class Xbuf>
inline SizeType adaptive_merge_n_keys_intbuf(SizeType &rl_block, SizeType len1, SizeType len2, Xbuf & xbuf, SizeType &l_intbuf_inout)
{
typedef SizeType size_type;
size_type l_block = rl_block;
size_type l_intbuf = xbuf.capacity() >= l_block ? 0u : l_block;
while(xbuf.capacity() >= l_block*2){
l_block *= 2;
}
//This is the minimum number of keys to implement the ideal algorithm
size_type n_keys = len1/l_block+len2/l_block;
while(n_keys >= ((len1-l_intbuf-n_keys)/l_block + len2/l_block)){
--n_keys;
}
++n_keys;
BOOST_ASSERT(n_keys >= ((len1-l_intbuf-n_keys)/l_block + len2/l_block));
if(xbuf.template supports_aligned_trailing<size_type>(l_block, n_keys)){
n_keys = 0u;
}
l_intbuf_inout = l_intbuf;
rl_block = l_block;
return n_keys;
}
// Main explanation of the merge algorithm.
//
// csqrtlen = ceil(sqrt(len));
//
// * First, csqrtlen [to be used as buffer] + (len/csqrtlen - 1) [to be used as keys] => to_collect
// unique elements are extracted from elements to be sorted and placed in the beginning of the range.
//
// * Step "combine_blocks": the leading (len1-to_collect) elements plus trailing len2 elements
// are merged with a non-trivial ("smart") algorithm to form an ordered range trailing "len-to_collect" elements.
//
// Explanation of the "combine_blocks" step:
//
// * Trailing [first+to_collect, first+len1) elements are divided in groups of cqrtlen elements.
// Remaining elements that can't form a group are grouped in front of those elements.
// * Trailing [first+len1, first+len1+len2) elements are divided in groups of cqrtlen elements.
// Remaining elements that can't form a group are grouped in the back of those elements.
// * In parallel the following two steps are performed:
// * Groups are selection-sorted by first or last element (depending whether they are going
// to be merged to left or right) and keys are reordered accordingly as an imitation-buffer.
// * Elements of each block pair are merged using the csqrtlen buffer taking into account
// if they belong to the first half or second half (marked by the key).
//
// * In the final merge step leading "to_collect" elements are merged with rotations
// with the rest of merged elements in the "combine_blocks" step.
//
// Corner cases:
//
// * If no "to_collect" elements can be extracted:
//
// * If more than a minimum number of elements is extracted
// then reduces the number of elements used as buffer and keys in the
// and "combine_blocks" steps. If "combine_blocks" has no enough keys due to this reduction
// then uses a rotation based smart merge.
//
// * If the minimum number of keys can't be extracted, a rotation-based merge is performed.
//
// * If auxiliary memory is more or equal than min(len1, len2), a buffered merge is performed.
//
// * If the len1 or len2 are less than 2*csqrtlen then a rotation-based merge is performed.
//
// * If auxiliary memory is more than csqrtlen+n_keys*sizeof(std::size_t),
// then no csqrtlen need to be extracted and "combine_blocks" will use integral
// keys to combine blocks.
template<class RandIt, class Compare, class XBuf>
void adaptive_merge_impl
( RandIt first
, typename iterator_traits<RandIt>::size_type len1
, typename iterator_traits<RandIt>::size_type len2
, Compare comp
, XBuf & xbuf
)
{
typedef typename iterator_traits<RandIt>::size_type size_type;
if(xbuf.capacity() >= min_value<size_type>(len1, len2)){
buffered_merge(first, first+len1, first+(len1+len2), comp, xbuf);
}
else{
const size_type len = len1+len2;
//Calculate ideal parameters and try to collect needed unique keys
size_type l_block = size_type(ceil_sqrt(len));
//One range is not big enough to extract keys and the internal buffer so a
//rotation-based based merge will do just fine
if(len1 <= l_block*2 || len2 <= l_block*2){
merge_bufferless(first, first+len1, first+len1+len2, comp);
return;
}
//Detail the number of keys and internal buffer. If xbuf has enough memory, no
//internal buffer is needed so l_intbuf will remain 0.
size_type l_intbuf = 0;
size_type n_keys = adaptive_merge_n_keys_intbuf(l_block, len1, len2, xbuf, l_intbuf);
size_type const to_collect = l_intbuf+n_keys;
//Try to extract needed unique values from the first range
size_type const collected = collect_unique(first, first+len1, to_collect, comp, xbuf);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1("\n A collect: ", len);
//Not the minimum number of keys is not available on the first range, so fallback to rotations
if(collected != to_collect && collected < 4){
merge_bufferless(first, first+collected, first+len1, comp);
merge_bufferless(first, first + len1, first + len1 + len2, comp);
return;
}
//If not enough keys but more than minimum, adjust the internal buffer and key count
bool use_internal_buf = collected == to_collect;
if (!use_internal_buf){
l_intbuf = 0u;
n_keys = collected;
l_block = lblock_for_combine(l_intbuf, n_keys, len, use_internal_buf);
//If use_internal_buf is false, then then internal buffer will be zero and rotation-based combination will be used
l_intbuf = use_internal_buf ? l_block : 0u;
}
bool const xbuf_used = collected == to_collect && xbuf.capacity() >= l_block;
//Merge trailing elements using smart merges
adaptive_merge_combine_blocks(first, len1, len2, collected, n_keys, l_block, use_internal_buf, xbuf_used, comp, xbuf);
//Merge buffer and keys with the rest of the values
adaptive_merge_final_merge (first, len1, len2, collected, l_intbuf, l_block, use_internal_buf, xbuf_used, comp, xbuf);
}
}
} //namespace detail_adaptive {
///@endcond
//! <b>Effects</b>: Merges two consecutive sorted ranges [first, middle) and [middle, last)
//! into one sorted range [first, last) according to the given comparison function comp.
//! The algorithm is stable (if there are equivalent elements in the original two ranges,

552
include/boost/move/algo/adaptive_sort.hpp
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@ -18,6 +18,558 @@
namespace boost {
namespace movelib {
///@cond
namespace detail_adaptive {
template<class RandIt>
void move_data_backward( RandIt cur_pos
, typename iterator_traits<RandIt>::size_type const l_data
, RandIt new_pos
, bool const xbuf_used)
{
//Move buffer to the total combination right
if(xbuf_used){
boost::move_backward(cur_pos, cur_pos+l_data, new_pos+l_data);
}
else{
boost::adl_move_swap_ranges_backward(cur_pos, cur_pos+l_data, new_pos+l_data);
//Rotate does less moves but it seems slower due to cache issues
//rotate_gcd(first-l_block, first+len-l_block, first+len);
}
}
template<class RandIt>
void move_data_forward( RandIt cur_pos
, typename iterator_traits<RandIt>::size_type const l_data
, RandIt new_pos
, bool const xbuf_used)
{
//Move buffer to the total combination right
if(xbuf_used){
boost::move(cur_pos, cur_pos+l_data, new_pos);
}
else{
boost::adl_move_swap_ranges(cur_pos, cur_pos+l_data, new_pos);
//Rotate does less moves but it seems slower due to cache issues
//rotate_gcd(first-l_block, first+len-l_block, first+len);
}
}
// build blocks of length 2*l_build_buf. l_build_buf is power of two
// input: [0, l_build_buf) elements are buffer, rest unsorted elements
// output: [0, l_build_buf) elements are buffer, blocks 2*l_build_buf and last subblock sorted
//
// First elements are merged from right to left until elements start
// at first. All old elements [first, first + l_build_buf) are placed at the end
// [first+len-l_build_buf, first+len). To achieve this:
// - If we have external memory to merge, we save elements from the buffer
// so that a non-swapping merge is used. Buffer elements are restored
// at the end of the buffer from the external memory.
//
// - When the external memory is not available or it is insufficient
// for a merge operation, left swap merging is used.
//
// Once elements are merged left to right in blocks of l_build_buf, then a single left
// to right merge step is performed to achieve merged blocks of size 2K.
// If external memory is available, usual merge is used, swap merging otherwise.
//
// As a last step, if auxiliary memory is available in-place merge is performed.
// until all is merged or auxiliary memory is not large enough.
template<class RandIt, class Compare, class XBuf>
typename iterator_traits<RandIt>::size_type
adaptive_sort_build_blocks
( RandIt const first
, typename iterator_traits<RandIt>::size_type const len
, typename iterator_traits<RandIt>::size_type const l_base
, typename iterator_traits<RandIt>::size_type const l_build_buf
, XBuf & xbuf
, Compare comp)
{
typedef typename iterator_traits<RandIt>::size_type size_type;
BOOST_ASSERT(l_build_buf <= len);
BOOST_ASSERT(0 == ((l_build_buf / l_base)&(l_build_buf/l_base-1)));
//Place the start pointer after the buffer
RandIt first_block = first + l_build_buf;
size_type const elements_in_blocks = len - l_build_buf;
//////////////////////////////////
// Start of merge to left step
//////////////////////////////////
size_type l_merged = 0u;
BOOST_ASSERT(l_build_buf);
//If there is no enough buffer for the insertion sort step, just avoid the external buffer
size_type kbuf = min_value<size_type>(l_build_buf, size_type(xbuf.capacity()));
kbuf = kbuf < l_base ? 0 : kbuf;
if(kbuf){
//Backup internal buffer values in external buffer so they can be overwritten
xbuf.move_assign(first+l_build_buf-kbuf, kbuf);
l_merged = op_insertion_sort_step_left(first_block, elements_in_blocks, l_base, comp, move_op());
//Now combine them using the buffer. Elements from buffer can be
//overwritten since they've been saved to xbuf
l_merged = op_merge_left_step_multiple
( first_block - l_merged, elements_in_blocks, l_merged, l_build_buf, kbuf - l_merged, comp, move_op());
//Restore internal buffer from external buffer unless kbuf was l_build_buf,
//in that case restoration will happen later
if(kbuf != l_build_buf){
boost::move(xbuf.data()+kbuf-l_merged, xbuf.data() + kbuf, first_block-l_merged+elements_in_blocks);
}
}
else{
l_merged = insertion_sort_step(first_block, elements_in_blocks, l_base, comp);
rotate_gcd(first_block - l_merged, first_block, first_block+elements_in_blocks);
}
//Now combine elements using the buffer. Elements from buffer can't be
//overwritten since xbuf was not big enough, so merge swapping elements.
l_merged = op_merge_left_step_multiple
(first_block - l_merged, elements_in_blocks, l_merged, l_build_buf, l_build_buf - l_merged, comp, swap_op());
BOOST_ASSERT(l_merged == l_build_buf);
//////////////////////////////////
// Start of merge to right step
//////////////////////////////////
//If kbuf is l_build_buf then we can merge right without swapping
//Saved data is still in xbuf
if(kbuf && kbuf == l_build_buf){
op_merge_right_step_once(first, elements_in_blocks, l_build_buf, comp, move_op());
//Restore internal buffer from external buffer if kbuf was l_build_buf.
//as this operation was previously delayed.
boost::move(xbuf.data(), xbuf.data() + kbuf, first);
}
else{
op_merge_right_step_once(first, elements_in_blocks, l_build_buf, comp, swap_op());
}
xbuf.clear();
//2*l_build_buf or total already merged
return min_value(elements_in_blocks, 2*l_build_buf);
}
template<class RandItKeys, class KeyCompare, class RandIt, class Compare, class XBuf>
void adaptive_sort_combine_blocks
( RandItKeys const keys
, KeyCompare key_comp
, RandIt const first
, typename iterator_traits<RandIt>::size_type const len
, typename iterator_traits<RandIt>::size_type const l_prev_merged
, typename iterator_traits<RandIt>::size_type const l_block
, bool const use_buf
, bool const xbuf_used
, XBuf & xbuf
, Compare comp
, bool merge_left)
{
(void)xbuf;
typedef typename iterator_traits<RandIt>::size_type size_type;
size_type const l_reg_combined = 2*l_prev_merged;
size_type l_irreg_combined = 0;
size_type const l_total_combined = calculate_total_combined(len, l_prev_merged, &l_irreg_combined);
size_type const n_reg_combined = len/l_reg_combined;
RandIt combined_first = first;
(void)l_total_combined;
BOOST_ASSERT(l_total_combined <= len);
size_type const max_i = n_reg_combined + (l_irreg_combined != 0);
if(merge_left || !use_buf) {
for( size_type combined_i = 0; combined_i != max_i; ++combined_i, combined_first += l_reg_combined) {
//Now merge blocks
bool const is_last = combined_i==n_reg_combined;
size_type const l_cur_combined = is_last ? l_irreg_combined : l_reg_combined;
range_xbuf<RandIt, move_op> rbuf( (use_buf && xbuf_used) ? (combined_first-l_block) : combined_first, combined_first);
size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
combine_params( keys, key_comp, l_cur_combined
, l_prev_merged, l_block, rbuf
, n_block_a, n_block_b, l_irreg1, l_irreg2); //Outputs
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A combpar: ", len + l_block);
BOOST_MOVE_ADAPTIVE_SORT_INVARIANT(is_sorted(combined_first, combined_first + n_block_a*l_block+l_irreg1, comp));
BOOST_MOVE_ADAPTIVE_SORT_INVARIANT(is_sorted(combined_first + n_block_a*l_block+l_irreg1, combined_first + n_block_a*l_block+l_irreg1+n_block_b*l_block+l_irreg2, comp));
if(!use_buf){
merge_blocks_bufferless
(keys, key_comp, combined_first, l_block, 0u, n_block_a, n_block_b, l_irreg2, comp);
}
else{
merge_blocks_left
(keys, key_comp, combined_first, l_block, 0u, n_block_a, n_block_b, l_irreg2, comp, xbuf_used);
}
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" After merge_blocks_L: ", len + l_block);
}
}
else{
combined_first += l_reg_combined*(max_i-1);
for( size_type combined_i = max_i; combined_i--; combined_first -= l_reg_combined) {
bool const is_last = combined_i==n_reg_combined;
size_type const l_cur_combined = is_last ? l_irreg_combined : l_reg_combined;
RandIt const combined_last(combined_first+l_cur_combined);
range_xbuf<RandIt, move_op> rbuf(combined_last, xbuf_used ? (combined_last+l_block) : combined_last);
size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
combine_params( keys, key_comp, l_cur_combined
, l_prev_merged, l_block, rbuf
, n_block_a, n_block_b, l_irreg1, l_irreg2); //Outputs
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A combpar: ", len + l_block);
BOOST_MOVE_ADAPTIVE_SORT_INVARIANT(is_sorted(combined_first, combined_first + n_block_a*l_block+l_irreg1, comp));
BOOST_MOVE_ADAPTIVE_SORT_INVARIANT(is_sorted(combined_first + n_block_a*l_block+l_irreg1, combined_first + n_block_a*l_block+l_irreg1+n_block_b*l_block+l_irreg2, comp));
merge_blocks_right
(keys, key_comp, combined_first, l_block, n_block_a, n_block_b, l_irreg2, comp, xbuf_used);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" After merge_blocks_R: ", len + l_block);
}
}
}
//Returns true if buffer is placed in
//[buffer+len-l_intbuf, buffer+len). Otherwise, buffer is
//[buffer,buffer+l_intbuf)
template<class RandIt, class Compare, class XBuf>
bool adaptive_sort_combine_all_blocks
( RandIt keys
, typename iterator_traits<RandIt>::size_type &n_keys
, RandIt const buffer
, typename iterator_traits<RandIt>::size_type const l_buf_plus_data
, typename iterator_traits<RandIt>::size_type l_merged
, typename iterator_traits<RandIt>::size_type &l_intbuf
, XBuf & xbuf
, Compare comp)
{
typedef typename iterator_traits<RandIt>::size_type size_type;
RandIt const first = buffer + l_intbuf;
size_type const l_data = l_buf_plus_data - l_intbuf;
size_type const l_unique = l_intbuf+n_keys;
//Backup data to external buffer once if possible
bool const common_xbuf = l_data > l_merged && l_intbuf && l_intbuf <= xbuf.capacity();
if(common_xbuf){
xbuf.move_assign(buffer, l_intbuf);
}
bool prev_merge_left = true;
size_type l_prev_total_combined = l_merged, l_prev_block = 0;
bool prev_use_internal_buf = true;
for( size_type n = 0; l_data > l_merged
; l_merged*=2
, ++n){
//If l_intbuf is non-zero, use that internal buffer.
// Implies l_block == l_intbuf && use_internal_buf == true
//If l_intbuf is zero, see if half keys can be reused as a reduced emergency buffer,
// Implies l_block == n_keys/2 && use_internal_buf == true
//Otherwise, just give up and and use all keys to merge using rotations (use_internal_buf = false)
bool use_internal_buf = false;
size_type const l_block = lblock_for_combine(l_intbuf, n_keys, 2*l_merged, use_internal_buf);
BOOST_ASSERT(!l_intbuf || (l_block == l_intbuf));
BOOST_ASSERT(n == 0 || (!use_internal_buf || prev_use_internal_buf) );
BOOST_ASSERT(n == 0 || (!use_internal_buf || l_prev_block == l_block) );
bool const is_merge_left = (n&1) == 0;
size_type const l_total_combined = calculate_total_combined(l_data, l_merged);
if(n && prev_use_internal_buf && prev_merge_left){
if(is_merge_left || !use_internal_buf){
move_data_backward(first-l_prev_block, l_prev_total_combined, first, common_xbuf);
}
else{
//Put the buffer just after l_total_combined
RandIt const buf_end = first+l_prev_total_combined;
RandIt const buf_beg = buf_end-l_block;
if(l_prev_total_combined > l_total_combined){
size_type const l_diff = l_prev_total_combined - l_total_combined;
move_data_backward(buf_beg-l_diff, l_diff, buf_end-l_diff, common_xbuf);
}
else if(l_prev_total_combined < l_total_combined){
size_type const l_diff = l_total_combined - l_prev_total_combined;
move_data_forward(buf_end, l_diff, buf_beg, common_xbuf);
}
}
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" After move_data : ", l_data + l_intbuf);
}
//Combine to form l_merged*2 segments
if(n_keys){
adaptive_sort_combine_blocks
( keys, comp, !use_internal_buf || is_merge_left ? first : first-l_block
, l_data, l_merged, l_block, use_internal_buf, common_xbuf, xbuf, comp, is_merge_left);
}
else{
size_type *const uint_keys = xbuf.template aligned_trailing<size_type>();
adaptive_sort_combine_blocks
( uint_keys, less(), !use_internal_buf || is_merge_left ? first : first-l_block
, l_data, l_merged, l_block, use_internal_buf, common_xbuf, xbuf, comp, is_merge_left);
}
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(is_merge_left ? " After comb blocks L: " : " After comb blocks R: ", l_data + l_intbuf);
prev_merge_left = is_merge_left;
l_prev_total_combined = l_total_combined;
l_prev_block = l_block;
prev_use_internal_buf = use_internal_buf;
}
BOOST_ASSERT(l_prev_total_combined == l_data);
bool const buffer_right = prev_use_internal_buf && prev_merge_left;
l_intbuf = prev_use_internal_buf ? l_prev_block : 0u;
n_keys = l_unique - l_intbuf;
//Restore data from to external common buffer if used
if(common_xbuf){
if(buffer_right){
boost::move(xbuf.data(), xbuf.data() + l_intbuf, buffer+l_data);
}
else{
boost::move(xbuf.data(), xbuf.data() + l_intbuf, buffer);
}
}
return buffer_right;
}
template<class RandIt, class Compare, class XBuf>
void adaptive_sort_final_merge( bool buffer_right
, RandIt const first
, typename iterator_traits<RandIt>::size_type const l_intbuf
, typename iterator_traits<RandIt>::size_type const n_keys
, typename iterator_traits<RandIt>::size_type const len
, XBuf & xbuf
, Compare comp)
{
//BOOST_ASSERT(n_keys || xbuf.size() == l_intbuf);
xbuf.clear();
typedef typename iterator_traits<RandIt>::size_type size_type;
size_type const n_key_plus_buf = l_intbuf+n_keys;
if(buffer_right){
//Use stable sort as some buffer elements might not be unique (see non_unique_buf)
stable_sort(first+len-l_intbuf, first+len, comp, xbuf);
stable_merge(first+n_keys, first+len-l_intbuf, first+len, antistable<Compare>(comp), xbuf);
unstable_sort(first, first+n_keys, comp, xbuf);
stable_merge(first, first+n_keys, first+len, comp, xbuf);
}
else{
//Use stable sort as some buffer elements might not be unique (see non_unique_buf)
stable_sort(first, first+n_key_plus_buf, comp, xbuf);
if(xbuf.capacity() >= n_key_plus_buf){
buffered_merge(first, first+n_key_plus_buf, first+len, comp, xbuf);
}
else if(xbuf.capacity() >= min_value<size_type>(l_intbuf, n_keys)){
stable_merge(first+n_keys, first+n_key_plus_buf, first+len, comp, xbuf);
stable_merge(first, first+n_keys, first+len, comp, xbuf);
}
else{
stable_merge(first, first+n_key_plus_buf, first+len, comp, xbuf);
}
}
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" After final_merge : ", len);
}
template<class RandIt, class Compare, class Unsigned, class XBuf>
bool adaptive_sort_build_params
(RandIt first, Unsigned const len, Compare comp
, Unsigned &n_keys, Unsigned &l_intbuf, Unsigned &l_base, Unsigned &l_build_buf
, XBuf & xbuf
)
{
typedef Unsigned size_type;
//Calculate ideal parameters and try to collect needed unique keys
l_base = 0u;
//Try to find a value near sqrt(len) that is 2^N*l_base where
//l_base <= AdaptiveSortInsertionSortThreshold. This property is important
//as build_blocks merges to the left iteratively duplicating the
//merged size and all the buffer must be used just before the final
//merge to right step. This guarantees "build_blocks" produces
//segments of size l_build_buf*2, maximizing the classic merge phase.
l_intbuf = size_type(ceil_sqrt_multiple(len, &l_base));
//The internal buffer can be expanded if there is enough external memory
while(xbuf.capacity() >= l_intbuf*2){
l_intbuf *= 2;
}
//This is the minimum number of keys to implement the ideal algorithm
//
//l_intbuf is used as buffer plus the key count
size_type n_min_ideal_keys = l_intbuf-1;
while(n_min_ideal_keys >= (len-l_intbuf-n_min_ideal_keys)/l_intbuf){
--n_min_ideal_keys;
}
n_min_ideal_keys += 1;
BOOST_ASSERT(n_min_ideal_keys <= l_intbuf);
if(xbuf.template supports_aligned_trailing<size_type>(l_intbuf, (len-l_intbuf-1)/l_intbuf+1)){
n_keys = 0u;
l_build_buf = l_intbuf;
}
else{
//Try to achieve a l_build_buf of length l_intbuf*2, so that we can merge with that
//l_intbuf*2 buffer in "build_blocks" and use half of them as buffer and the other half
//as keys in combine_all_blocks. In that case n_keys >= n_min_ideal_keys but by a small margin.
//
//If available memory is 2*sqrt(l), then only sqrt(l) unique keys are needed,
//(to be used for keys in combine_all_blocks) as the whole l_build_buf
//will be backuped in the buffer during build_blocks.
bool const non_unique_buf = xbuf.capacity() >= l_intbuf;
size_type const to_collect = non_unique_buf ? n_min_ideal_keys : l_intbuf*2;
size_type collected = collect_unique(first, first+len, to_collect, comp, xbuf);
//If available memory is 2*sqrt(l), then for "build_params"
//the situation is the same as if 2*l_intbuf were collected.
if(non_unique_buf && collected == n_min_ideal_keys){
l_build_buf = l_intbuf;
n_keys = n_min_ideal_keys;
}
else if(collected == 2*l_intbuf){
//l_intbuf*2 elements found. Use all of them in the build phase
l_build_buf = l_intbuf*2;
n_keys = l_intbuf;
}
else if(collected == (n_min_ideal_keys+l_intbuf)){
l_build_buf = l_intbuf;
n_keys = n_min_ideal_keys;
}
//If collected keys are not enough, try to fix n_keys and l_intbuf. If no fix
//is possible (due to very low unique keys), then go to a slow sort based on rotations.
else{
BOOST_ASSERT(collected < (n_min_ideal_keys+l_intbuf));
if(collected < 4){ //No combination possible with less that 4 keys
return false;
}
n_keys = l_intbuf;
while(n_keys&(n_keys-1)){
n_keys &= n_keys-1; // make it power or 2
}
while(n_keys > collected){
n_keys/=2;
}
//AdaptiveSortInsertionSortThreshold is always power of two so the minimum is power of two
l_base = min_value<Unsigned>(n_keys, AdaptiveSortInsertionSortThreshold);
l_intbuf = 0;
l_build_buf = n_keys;
}
BOOST_ASSERT((n_keys+l_intbuf) >= l_build_buf);
}
return true;
}
// Main explanation of the sort algorithm.
//
// csqrtlen = ceil(sqrt(len));
//
// * First, 2*csqrtlen unique elements elements are extracted from elements to be
// sorted and placed in the beginning of the range.
//
// * Step "build_blocks": In this nearly-classic merge step, 2*csqrtlen unique elements
// will be used as auxiliary memory, so trailing len-2*csqrtlen elements are
// are grouped in blocks of sorted 4*csqrtlen elements. At the end of the step
// 2*csqrtlen unique elements are again the leading elements of the whole range.
//
// * Step "combine_blocks": pairs of previously formed blocks are merged with a different
// ("smart") algorithm to form blocks of 8*csqrtlen elements. This step is slower than the
// "build_blocks" step and repeated iteratively (forming blocks of 16*csqrtlen, 32*csqrtlen
// elements, etc) of until all trailing (len-2*csqrtlen) elements are merged.
//
// In "combine_blocks" len/csqrtlen elements used are as "keys" (markers) to
// know if elements belong to the first or second block to be merged and another
// leading csqrtlen elements are used as buffer. Explanation of the "combine_blocks" step:
//
// Iteratively until all trailing (len-2*csqrtlen) elements are merged:
// Iteratively for each pair of previously merged block:
// * Blocks are divided groups of csqrtlen elements and
// 2*merged_block/csqrtlen keys are sorted to be used as markers
// * Groups are selection-sorted by first or last element (depending whether they are going
// to be merged to left or right) and keys are reordered accordingly as an imitation-buffer.
// * Elements of each block pair are merged using the csqrtlen buffer taking into account
// if they belong to the first half or second half (marked by the key).
//
// * In the final merge step leading elements (2*csqrtlen) are sorted and merged with
// rotations with the rest of sorted elements in the "combine_blocks" step.
//
// Corner cases:
//
// * If no 2*csqrtlen elements can be extracted:
//
// * If csqrtlen+len/csqrtlen are extracted, then only csqrtlen elements are used
// as buffer in the "build_blocks" step forming blocks of 2*csqrtlen elements. This
// means that an additional "combine_blocks" step will be needed to merge all elements.
//
// * If no csqrtlen+len/csqrtlen elements can be extracted, but still more than a minimum,
// then reduces the number of elements used as buffer and keys in the "build_blocks"
// and "combine_blocks" steps. If "combine_blocks" has no enough keys due to this reduction
// then uses a rotation based smart merge.
//
// * If the minimum number of keys can't be extracted, a rotation-based sorting is performed.
//
// * If auxiliary memory is more or equal than ceil(len/2), half-copying mergesort is used.
//
// * If auxiliary memory is more than csqrtlen+n_keys*sizeof(std::size_t),
// then only csqrtlen elements need to be extracted and "combine_blocks" will use integral
// keys to combine blocks.
//
// * If auxiliary memory is available, the "build_blocks" will be extended to build bigger blocks
// using classic merge and "combine_blocks" will use bigger blocks when merging.
template<class RandIt, class Compare, class XBuf>
void adaptive_sort_impl
( RandIt first
, typename iterator_traits<RandIt>::size_type const len
, Compare comp
, XBuf & xbuf
)
{
typedef typename iterator_traits<RandIt>::size_type size_type;
//Small sorts go directly to insertion sort
if(len <= size_type(AdaptiveSortInsertionSortThreshold)){
insertion_sort(first, first + len, comp);
}
else if((len-len/2) <= xbuf.capacity()){
merge_sort(first, first+len, comp, xbuf.data());
}
else{
//Make sure it is at least four
BOOST_STATIC_ASSERT(AdaptiveSortInsertionSortThreshold >= 4);
size_type l_base = 0;
size_type l_intbuf = 0;
size_type n_keys = 0;
size_type l_build_buf = 0;
//Calculate and extract needed unique elements. If a minimum is not achieved
//fallback to a slow stable sort
if(!adaptive_sort_build_params(first, len, comp, n_keys, l_intbuf, l_base, l_build_buf, xbuf)){
stable_sort(first, first+len, comp, xbuf);
}
else{
BOOST_ASSERT(l_build_buf);
//Otherwise, continue the adaptive_sort
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1("\n After collect_unique: ", len);
size_type const n_key_plus_buf = l_intbuf+n_keys;
//l_build_buf is always power of two if l_intbuf is zero
BOOST_ASSERT(l_intbuf || (0 == (l_build_buf & (l_build_buf-1))));
//Classic merge sort until internal buffer and xbuf are exhausted
size_type const l_merged = adaptive_sort_build_blocks
(first+n_key_plus_buf-l_build_buf, len-n_key_plus_buf+l_build_buf, l_base, l_build_buf, xbuf, comp);
BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" After build_blocks: ", len);
//Non-trivial merge
bool const buffer_right = adaptive_sort_combine_all_blocks
(first, n_keys, first+n_keys, len-n_keys, l_merged, l_intbuf, xbuf, comp);
//Sort keys and buffer and merge the whole sequence
adaptive_sort_final_merge(buffer_right, first, l_intbuf, n_keys, len, xbuf, comp);
}
}
}
} //namespace detail_adaptive {
///@endcond
//! <b>Effects</b>: Sorts the elements in the range [first, last) in ascending order according
//! to comparison functor "comp". The sort is stable (order of equal elements
//! is guaranteed to be preserved). Performance is improved if additional raw storage is

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111
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@ -0,0 +1,111 @@
//////////////////////////////////////////////////////////////////////////////
//
// (C) Copyright Ion Gaztanaga 2017-2018.
// Distributed under the Boost Software License, Version 1.0.
// (See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
//
// See http://www.boost.org/libs/move for documentation.
//
//////////////////////////////////////////////////////////////////////////////
//! \file
#ifndef BOOST_MOVE_DETAIL_HEAP_SORT_HPP
#define BOOST_MOVE_DETAIL_HEAP_SORT_HPP
#ifndef BOOST_CONFIG_HPP
# include <boost/config.hpp>
#endif
#
#if defined(BOOST_HAS_PRAGMA_ONCE)
# pragma once
#endif
#include <boost/move/detail/config_begin.hpp>
#include <boost/move/detail/workaround.hpp>
#include <boost/move/detail/iterator_traits.hpp>
#include <boost/move/algo/detail/is_sorted.hpp>
#include <boost/move/utility_core.hpp>
namespace boost { namespace movelib{
template <class RandomAccessIterator, class Compare>
class heap_sort_helper
{
typedef typename boost::movelib::iterator_traits<RandomAccessIterator>::size_type size_type;
typedef typename boost::movelib::iterator_traits<RandomAccessIterator>::value_type value_type;
static void adjust_heap(RandomAccessIterator first, size_type hole_index, size_type const len, value_type &value, Compare comp)
{
size_type const top_index = hole_index;
size_type second_child = 2 * (hole_index + 1);
while (second_child < len) {
if (comp(*(first + second_child), *(first + (second_child - 1))))
second_child--;
*(first + hole_index) = boost::move(*(first + second_child));
hole_index = second_child;
second_child = 2 * (second_child + 1);
}
if (second_child == len) {
*(first + hole_index) = boost::move(*(first + (second_child - 1)));
hole_index = second_child - 1;
}
{ //push_heap-like ending
size_type parent = (hole_index - 1) / 2;
while (hole_index > top_index && comp(*(first + parent), value)) {
*(first + hole_index) = boost::move(*(first + parent));
hole_index = parent;
parent = (hole_index - 1) / 2;
}
*(first + hole_index) = boost::move(value);
}
}
static void make_heap(RandomAccessIterator first, RandomAccessIterator last, Compare comp)
{
size_type const len = size_type(last - first);
if (len > 1) {
size_type parent = len/2u - 1u;
do {
value_type v(boost::move(*(first + parent)));
adjust_heap(first, parent, len, v, comp);
}while (parent--);
}
}
static void sort_heap(RandomAccessIterator first, RandomAccessIterator last, Compare comp)
{
size_type len = size_type(last - first);
while (len > 1) {
//move biggest to the safe zone
--last;
value_type v(boost::move(*last));
*last = boost::move(*first);
adjust_heap(first, size_type(0), --len, v, comp);
}
}
public:
static void sort(RandomAccessIterator first, RandomAccessIterator last, Compare comp)
{
make_heap(first, last, comp);
sort_heap(first, last, comp);
BOOST_ASSERT(boost::movelib::is_sorted(first, last, comp));
}
};
template <class RandomAccessIterator, class Compare>
BOOST_MOVE_FORCEINLINE void heap_sort(RandomAccessIterator first, RandomAccessIterator last, Compare comp)
{
heap_sort_helper<RandomAccessIterator, Compare>::sort(first, last, comp);
}
}} //namespace boost { namespace movelib{
#include <boost/move/detail/config_end.hpp>
#endif //#ifndef BOOST_MOVE_DETAIL_HEAP_SORT_HPP

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#ifndef BOOST_MOVE_DETAIL_IS_SORTED_HPP
#define BOOST_MOVE_DETAIL_IS_SORTED_HPP
///////////////////////////////////////////////////////////////////////////////
//
// (C) Copyright Ion Gaztanaga 2017-2018. Distributed under the Boost
// Software License, Version 1.0. (See accompanying file
// LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
//
// See http://www.boost.org/libs/container for documentation.
//
///////////////////////////////////////////////////////////////////////////////
#ifndef BOOST_CONFIG_HPP
# include <boost/config.hpp>
#endif
#if defined(BOOST_HAS_PRAGMA_ONCE)
# pragma once
#endif
namespace boost {
namespace movelib {
template<class ForwardIt, class Pred>
bool is_sorted(ForwardIt const first, ForwardIt last, Pred pred)
{
if (first != last) {
ForwardIt next = first, cur(first);
while (++next != last) {
if (pred(*next, *cur))
return false;
cur = next;
}
}
return true;
}
template<class ForwardIt, class Pred>
bool is_sorted_and_unique(ForwardIt first, ForwardIt last, Pred pred)
{
if (first != last) {
ForwardIt next = first;
while (++next != last) {
if (!pred(*first, *next))
return false;
first = next;
}
}
return true;
}
} //namespace movelib {
} //namespace boost {
#endif //BOOST_MOVE_DETAIL_IS_SORTED_HPP

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@ -256,101 +256,6 @@ void swap_merge_right
op_merge_right(first1, last1, last2, buf_last, comp, swap_op());
}
template <class BidirIt, class Distance, class Compare>
void merge_bufferless_ONlogN_recursive
(BidirIt first, BidirIt middle, BidirIt last, Distance len1, Distance len2, Compare comp)
{
typedef typename iterator_traits<BidirIt>::size_type size_type;
while(1) {
//#define MERGE_BUFFERLESS_RECURSIVE_OPT
#ifndef MERGE_BUFFERLESS_RECURSIVE_OPT
if (len2 == 0) {
return;
}
if (!len1) {
return;
}
if ((len1 | len2) == 1) {
if (comp(*middle, *first))
adl_move_swap(*first, *middle);
return;
}
#else
if (len2 == 0) {
return;
}
if (!len1) {
return;
}
BidirIt middle_prev = middle; --middle_prev;
if(!comp(*middle, *middle_prev))
return;
while(true) {
if (comp(*middle, *first))
break;
++first;
if(--len1 == 1)
break;
}
if (len1 == 1 && len2 == 1) {
//comp(*middle, *first) == true already tested in the loop
adl_move_swap(*first, *middle);
return;
}
#endif
BidirIt first_cut = first;
BidirIt second_cut = middle;
Distance len11 = 0;
Distance len22 = 0;
if (len1 > len2) {
len11 = len1 / 2;
first_cut += len11;
second_cut = boost::movelib::lower_bound(middle, last, *first_cut, comp);
len22 = size_type(second_cut - middle);
}
else {
len22 = len2 / 2;
second_cut += len22;
first_cut = boost::movelib::upper_bound(first, middle, *second_cut, comp);
len11 = size_type(first_cut - first);
}
BidirIt new_middle = rotate_gcd(first_cut, middle, second_cut);
//Avoid one recursive call doing a manual tail call elimination on the biggest range
const Distance len_internal = len11+len22;
if( len_internal < (len1 + len2 - len_internal) ) {
merge_bufferless_ONlogN_recursive(first, first_cut, new_middle, len11, len22, comp);
//merge_bufferless_recursive(new_middle, second_cut, last, len1 - len11, len2 - len22, comp);
first = new_middle;
middle = second_cut;
len1 -= len11;
len2 -= len22;
}
else {
//merge_bufferless_recursive(first, first_cut, new_middle, len11, len22, comp);
merge_bufferless_ONlogN_recursive(new_middle, second_cut, last, len1 - len11, len2 - len22, comp);
middle = first_cut;
last = new_middle;
len1 = len11;
len2 = len22;
}
}
}
//Complexity: NlogN
template<class BidirIt, class Compare>
void merge_bufferless_ONlogN(BidirIt first, BidirIt middle, BidirIt last, Compare comp)
{
merge_bufferless_ONlogN_recursive
(first, middle, last, middle - first, last - middle, comp);
}
//Complexity: min(len1,len2)^2 + max(len1,len2)
template<class RandIt, class Compare>
void merge_bufferless_ON2(RandIt first, RandIt middle, RandIt last, Compare comp)
@ -384,10 +289,81 @@ void merge_bufferless_ON2(RandIt first, RandIt middle, RandIt last, Compare comp
}
}
static const std::size_t MergeBufferlessONLogNRotationThreshold = 32;
template <class RandIt, class Distance, class Compare>
void merge_bufferless_ONlogN_recursive
(RandIt first, RandIt middle, RandIt last, Distance len1, Distance len2, Compare comp)
{
typedef typename iterator_traits<RandIt>::size_type size_type;
while(1) {
//trivial cases
if (!len2) {
return;
}
else if (!len1) {
return;
}
else if (size_type(len1 | len2) == 1u) {
if (comp(*middle, *first))
adl_move_swap(*first, *middle);
return;
}
else if(size_type(len1+len2) < MergeBufferlessONLogNRotationThreshold){
merge_bufferless_ON2(first, middle, last, comp);
return;
}
RandIt first_cut = first;
RandIt second_cut = middle;
Distance len11 = 0;
Distance len22 = 0;
if (len1 > len2) {
len11 = len1 / 2;
first_cut += len11;
second_cut = boost::movelib::lower_bound(middle, last, *first_cut, comp);
len22 = size_type(second_cut - middle);
}
else {
len22 = len2 / 2;
second_cut += len22;
first_cut = boost::movelib::upper_bound(first, middle, *second_cut, comp);
len11 = size_type(first_cut - first);
}
RandIt new_middle = rotate_gcd(first_cut, middle, second_cut);
//Avoid one recursive call doing a manual tail call elimination on the biggest range
const Distance len_internal = len11+len22;
if( len_internal < (len1 + len2 - len_internal) ) {
merge_bufferless_ONlogN_recursive(first, first_cut, new_middle, len11, len22, comp);
first = new_middle;
middle = second_cut;
len1 -= len11;
len2 -= len22;
}
else {
merge_bufferless_ONlogN_recursive(new_middle, second_cut, last, len1 - len11, len2 - len22, comp);
middle = first_cut;
last = new_middle;
len1 = len11;
len2 = len22;
}
}
}
//Complexity: NlogN
template<class RandIt, class Compare>
void merge_bufferless_ONlogN(RandIt first, RandIt middle, RandIt last, Compare comp)
{
merge_bufferless_ONlogN_recursive
(first, middle, last, middle - first, last - middle, comp);
}
template<class RandIt, class Compare>
void merge_bufferless(RandIt first, RandIt middle, RandIt last, Compare comp)
{
//#define BOOST_ADAPTIVE_MERGE_NLOGN_MERGE
#define BOOST_ADAPTIVE_MERGE_NLOGN_MERGE
#ifdef BOOST_ADAPTIVE_MERGE_NLOGN_MERGE
merge_bufferless_ONlogN(first, middle, last, comp);
#else

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@ -0,0 +1,334 @@
//////////////////////////////////////////////////////////////////////////////
//
// (C) Copyright Orson Peters 2017.
// (C) Copyright Ion Gaztanaga 2017-2018.
// Distributed under the Boost Software License, Version 1.0.
// (See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
//
// See http://www.boost.org/libs/move for documentation.
//
//////////////////////////////////////////////////////////////////////////////
//
// This implementation of Pattern-defeating quicksort (pdqsort) was written
// by Orson Peters, and discussed in the Boost mailing list:
// http://boost.2283326.n4.nabble.com/sort-pdqsort-td4691031.html
//
// This implementation is the adaptation by Ion Gaztanaga of code originally in GitHub
// with permission from the author to relicense it under the Boost Software License
// (see the Boost mailing list for details).
//
// The original copyright statement is pasted here for completeness:
//
// pdqsort.h - Pattern-defeating quicksort.
// Copyright (c) 2015 Orson Peters
// This software is provided 'as-is', without any express or implied warranty. In no event will the
// authors be held liable for any damages arising from the use of this software.
// Permission is granted to anyone to use this software for any purpose, including commercial
// applications, and to alter it and redistribute it freely, subject to the following restrictions:
// 1. The origin of this software must not be misrepresented; you must not claim that you wrote the
// original software. If you use this software in a product, an acknowledgment in the product
// documentation would be appreciated but is not required.
// 2. Altered source versions must be plainly marked as such, and must not be misrepresented as
// being the original software.
// 3. This notice may not be removed or altered from any source distribution.
//
//////////////////////////////////////////////////////////////////////////////
#ifndef BOOST_MOVE_ALGO_PDQSORT_HPP
#define BOOST_MOVE_ALGO_PDQSORT_HPP
#ifndef BOOST_CONFIG_HPP
# include <boost/config.hpp>
#endif
#
#if defined(BOOST_HAS_PRAGMA_ONCE)
# pragma once
#endif
#include <boost/move/detail/config_begin.hpp>
#include <boost/move/detail/workaround.hpp>
#include <boost/move/utility_core.hpp>
#include <boost/move/algo/detail/insertion_sort.hpp>
#include <boost/move/algo/detail/heap_sort.hpp>
#include <boost/move/detail/iterator_traits.hpp>
#include <boost/move/adl_move_swap.hpp>
#include <cstddef>
namespace boost {
namespace movelib {
namespace pdqsort_detail {
//A simple pair implementation to avoid including <utility>
template<class T1, class T2>
struct pair
{
pair()
{}
pair(const T1 &t1, const T2 &t2)
: first(t1), second(t2)
{}
T1 first;
T2 second;
};
enum {
// Partitions below this size are sorted using insertion sort.
insertion_sort_threshold = 24,
// Partitions above this size use Tukey's ninther to select the pivot.
ninther_threshold = 128,
// When we detect an already sorted partition, attempt an insertion sort that allows this
// amount of element moves before giving up.
partial_insertion_sort_limit = 8,
// Must be multiple of 8 due to loop unrolling, and < 256 to fit in unsigned char.
block_size = 64,
// Cacheline size, assumes power of two.
cacheline_size = 64
};
// Returns floor(log2(n)), assumes n > 0.
template<class Unsigned>
Unsigned log2(Unsigned n) {
Unsigned log = 0;
while (n >>= 1) ++log;
return log;
}
// 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<class Iter, class Compare>
inline bool partial_insertion_sort(Iter begin, Iter end, Compare comp) {
typedef typename boost::movelib::iterator_traits<Iter>::value_type T;
typedef typename boost::movelib::iterator_traits<Iter>::size_type size_type;
if (begin == end) return true;
size_type limit = 0;
for (Iter cur = begin + 1; cur != end; ++cur) {
if (limit > partial_insertion_sort_limit) return false;
Iter sift = cur;
Iter sift_1 = cur - 1;
// Compare first so we can avoid 2 moves for an element already positioned correctly.
if (comp(*sift, *sift_1)) {
T tmp = boost::move(*sift);
do { *sift-- = boost::move(*sift_1); }
while (sift != begin && comp(tmp, *--sift_1));
*sift = boost::move(tmp);
limit += size_type(cur - sift);
}
}
return true;
}
template<class Iter, class Compare>
inline void sort2(Iter a, Iter b, Compare comp) {
if (comp(*b, *a)) boost::adl_move_iter_swap(a, b);
}
// Sorts the elements *a, *b and *c using comparison function comp.
template<class Iter, class Compare>
inline void sort3(Iter a, Iter b, Iter c, Compare comp) {
sort2(a, b, comp);
sort2(b, c, comp);
sort2(a, b, comp);
}
// 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<class Iter, class Compare>
pdqsort_detail::pair<Iter, bool> partition_right(Iter begin, Iter end, Compare comp) {
typedef typename boost::movelib::iterator_traits<Iter>::value_type T;
// Move pivot into local for speed.
T pivot(boost::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) {
boost::adl_move_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 = boost::move(*pivot_pos);
*pivot_pos = boost::move(pivot);
return pdqsort_detail::pair<Iter, bool>(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<class Iter, class Compare>
inline Iter partition_left(Iter begin, Iter end, Compare comp) {
typedef typename boost::movelib::iterator_traits<Iter>::value_type T;
T pivot(boost::move(*begin));
Iter first = begin;
Iter last = end;
while (comp(pivot, *--last));
if (last + 1 == end) while (first < last && !comp(pivot, *++first));
else while ( !comp(pivot, *++first));
while (first < last) {
boost::adl_move_iter_swap(first, last);
while (comp(pivot, *--last));
while (!comp(pivot, *++first));
}
Iter pivot_pos = last;
*begin = boost::move(*pivot_pos);
*pivot_pos = boost::move(pivot);
return pivot_pos;
}
template<class Iter, class Compare>
void pdqsort_loop( Iter begin, Iter end, Compare comp
, typename boost::movelib::iterator_traits<Iter>::size_type bad_allowed
, bool leftmost = true)
{
typedef typename boost::movelib::iterator_traits<Iter>::size_type size_type;
// Use a while loop for tail recursion elimination.
while (true) {
size_type size = size_type(end - begin);
// Insertion sort is faster for small arrays.
if (size < insertion_sort_threshold) {
insertion_sort(begin, end, comp);
return;
}
// Choose pivot as median of 3 or pseudomedian of 9.
size_type s2 = size / 2;
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);
boost::adl_move_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.
pdqsort_detail::pair<Iter, bool> part_result = partition_right(begin, end, comp);
Iter pivot_pos = part_result.first;
bool already_partitioned = part_result.second;
// Check for a highly unbalanced partition.
size_type l_size = size_type(pivot_pos - begin);
size_type r_size = size_type(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) {
boost::movelib::heap_sort(begin, end, comp);
return;
}
if (l_size >= insertion_sort_threshold) {
boost::adl_move_iter_swap(begin, begin + l_size / 4);
boost::adl_move_iter_swap(pivot_pos - 1, pivot_pos - l_size / 4);
if (l_size > ninther_threshold) {
boost::adl_move_iter_swap(begin + 1, begin + (l_size / 4 + 1));
boost::adl_move_iter_swap(begin + 2, begin + (l_size / 4 + 2));
boost::adl_move_iter_swap(pivot_pos - 2, pivot_pos - (l_size / 4 + 1));
boost::adl_move_iter_swap(pivot_pos - 3, pivot_pos - (l_size / 4 + 2));
}
}
if (r_size >= insertion_sort_threshold) {
boost::adl_move_iter_swap(pivot_pos + 1, pivot_pos + (1 + r_size / 4));
boost::adl_move_iter_swap(end - 1, end - r_size / 4);
if (r_size > ninther_threshold) {
boost::adl_move_iter_swap(pivot_pos + 2, pivot_pos + (2 + r_size / 4));
boost::adl_move_iter_swap(pivot_pos + 3, pivot_pos + (3 + r_size / 4));
boost::adl_move_iter_swap(end - 2, end - (1 + r_size / 4));
boost::adl_move_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>(begin, pivot_pos, comp, bad_allowed, leftmost);
begin = pivot_pos + 1;
leftmost = false;
}
}
}
template<class Iter, class Compare>
void pdqsort(Iter begin, Iter end, Compare comp)
{
if (begin == end) return;
typedef typename boost::movelib::iterator_traits<Iter>::size_type size_type;
pdqsort_detail::pdqsort_loop<Iter, Compare>(begin, end, comp, pdqsort_detail::log2(size_type(end - begin)));
}
} //namespace movelib {
} //namespace boost {
#include <boost/move/detail/config_end.hpp>
#endif //BOOST_MOVE_ALGO_PDQSORT_HPP

6
proj/vc7ide/move.vcproj
View File

@ -216,6 +216,9 @@
<File
RelativePath="..\..\..\..\boost\move\algo\detail\basic_op.hpp">
</File>
<File
RelativePath="..\..\..\..\boost\move\algo\detail\heap_sort.hpp">
</File>
<File
RelativePath="..\..\..\..\boost\move\algo\detail\insertion_sort.hpp">
</File>
@ -225,6 +228,9 @@
<File
RelativePath="..\..\..\..\boost\move\algo\detail\merge_sort.hpp">
</File>
<File
RelativePath="..\..\..\..\boost\move\algo\detail\pdqsort.hpp">
</File>
<File
RelativePath="..\..\..\..\boost\move\algo\detail\set_difference.hpp">
</File>

4
test/bench_merge.cpp
View File

@ -26,6 +26,7 @@ using boost::timer::cpu_times;
using boost::timer::nanosecond_type;
//#define BOOST_MOVE_ADAPTIVE_SORT_STATS
//#define BOOST_MOVE_ADAPTIVE_SORT_STATS_LEVEL 2
void print_stats(const char *str, boost::ulong_long_type element_count)
{
std::printf("%sCmp:%8.04f Cpy:%9.04f\n", str, double(order_perf_type::num_compare)/element_count, double(order_perf_type::num_copy)/element_count );
@ -84,7 +85,7 @@ const char *AlgoNames [] = { "StdMerge "
, "SqrtHAdaptMerge "
, "SqrtAdaptMerge "
, "Sqrt2AdaptMerge "
, "QHalfAdaptMerge "
, "QuartAdaptMerge "
, "StdInplaceMerge "
};
@ -256,6 +257,7 @@ int main()
#endif
measure_all<order_perf_type>(1000001,0);
measure_all<order_perf_type>(3000001,0);
measure_all<order_perf_type>(5000001,0);
#endif //NDEBUG
#endif //#ifndef BENCH_MERGE_SHORT

17
test/bench_sort.cpp
View File

@ -36,6 +36,8 @@ void print_stats(const char *str, boost::ulong_long_type element_count)
#include <boost/move/algo/adaptive_sort.hpp>
#include <boost/move/algo/detail/merge_sort.hpp>
#include <boost/move/algo/detail/pdqsort.hpp>
#include <boost/move/algo/detail/heap_sort.hpp>
#include <boost/move/core.hpp>
template<class T>
@ -75,6 +77,7 @@ enum AlgoType
{
MergeSort,
StableSort,
PdQsort,
AdaptiveSort,
SqrtHAdaptiveSort,
SqrtAdaptiveSort,
@ -88,6 +91,7 @@ enum AlgoType
const char *AlgoNames [] = { "MergeSort "
, "StableSort "
, "PdQsort "
, "AdaptSort "
, "SqrtHAdaptSort "
, "SqrtAdaptSort "
@ -119,6 +123,9 @@ bool measure_algo(T *elements, std::size_t key_reps[], std::size_t element_count
case StableSort:
std::stable_sort(elements,elements+element_count,order_type_less());
break;
case PdQsort:
boost::movelib::pdqsort(elements,elements+element_count,order_type_less());
break;
case AdaptiveSort:
boost::movelib::adaptive_sort(elements, elements+element_count, order_type_less());
break;
@ -145,8 +152,9 @@ bool measure_algo(T *elements, std::size_t key_reps[], std::size_t element_count
boost::movelib::detail_adaptive::slow_stable_sort(elements, elements+element_count, order_type_less());
break;
case HeapSort:
std::make_heap(elements, elements+element_count, order_type_less());
std::sort_heap(elements, elements+element_count, order_type_less());
boost::movelib::heap_sort(elements, elements+element_count, order_type_less());
boost::movelib::heap_sort((order_move_type*)0, (order_move_type*)0, order_type_less());
break;
}
timer.stop();
@ -182,7 +190,7 @@ bool measure_algo(T *elements, std::size_t key_reps[], std::size_t element_count
, units
, prev_clock ? double(new_clock)/double(prev_clock): 1.0);
prev_clock = new_clock;
bool res = is_order_type_ordered(elements, element_count, alg != HeapSort);
bool res = is_order_type_ordered(elements, element_count, alg != HeapSort && alg != PdQsort);
return res;
}
@ -205,6 +213,9 @@ bool measure_all(std::size_t L, std::size_t NK)
res = res && measure_algo(A,Keys,L,NK,StableSort, prev_clock);
//
prev_clock = back_clock;
res = res && measure_algo(A,Keys,L,NK,PdQsort, prev_clock);
//
prev_clock = back_clock;
res = res && measure_algo(A,Keys,L,NK,HeapSort, prev_clock);
//
prev_clock = back_clock;