364 lines
16 KiB
C++
Executable File
364 lines
16 KiB
C++
Executable File
//////////////////////////////////////////////////////////////////////////////
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//
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// (C) Copyright Ion Gaztanaga 2015-2016.
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// Distributed under the Boost Software License, Version 1.0.
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// (See accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt)
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//
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// See http://www.boost.org/libs/move for documentation.
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//
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//////////////////////////////////////////////////////////////////////////////
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#ifndef BOOST_MOVE_ADAPTIVE_MERGE_HPP
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#define BOOST_MOVE_ADAPTIVE_MERGE_HPP
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#include <boost/move/detail/config_begin.hpp>
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#include <boost/move/algo/detail/adaptive_sort_merge.hpp>
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#if defined(BOOST_CLANG) || (defined(BOOST_GCC) && (BOOST_GCC >= 40600))
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#pragma GCC diagnostic push
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#pragma GCC diagnostic ignored "-Wsign-conversion"
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#endif
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namespace boost {
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namespace movelib {
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///@cond
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namespace detail_adaptive {
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template<class RandIt, class Compare, class XBuf>
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inline void adaptive_merge_combine_blocks( RandIt first
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, typename iter_size<RandIt>::type len1
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, typename iter_size<RandIt>::type len2
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, typename iter_size<RandIt>::type collected
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, typename iter_size<RandIt>::type n_keys
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, typename iter_size<RandIt>::type l_block
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, bool use_internal_buf
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, bool xbuf_used
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, Compare comp
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, XBuf & xbuf
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)
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{
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typedef typename iter_size<RandIt>::type size_type;
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size_type const len = size_type(len1+len2);
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size_type const l_combine = size_type(len-collected);
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size_type const l_combine1 = size_type(len1-collected);
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if(n_keys){
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RandIt const first_data = first+collected;
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RandIt const keys = first;
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BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A combine: ", len);
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if(xbuf_used){
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if(xbuf.size() < l_block){
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xbuf.initialize_until(l_block, *first);
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}
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BOOST_ASSERT(xbuf.size() >= l_block);
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size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
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combine_params( keys, comp, l_combine
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, l_combine1, l_block, xbuf
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, n_block_a, n_block_b, l_irreg1, l_irreg2); //Outputs
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op_merge_blocks_with_buf
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(keys, comp, first_data, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp, move_op(), xbuf.data());
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BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" A mrg xbf: ", len);
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}
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else{
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size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
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combine_params( keys, comp, l_combine
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, l_combine1, l_block, xbuf
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, n_block_a, n_block_b, l_irreg1, l_irreg2); //Outputs
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if(use_internal_buf){
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op_merge_blocks_with_buf
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( keys, comp, first_data, l_block, l_irreg1, n_block_a, n_block_b
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, l_irreg2, comp, swap_op(), first_data-l_block);
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BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A mrg buf: ", len);
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}
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else{
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merge_blocks_bufferless
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(keys, comp, first_data, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp);
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BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" A mrg nbf: ", len);
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}
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}
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}
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else{
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xbuf.shrink_to_fit(l_block);
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if(xbuf.size() < l_block){
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xbuf.initialize_until(l_block, *first);
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}
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size_type *const uint_keys = xbuf.template aligned_trailing<size_type>(l_block);
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size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
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combine_params( uint_keys, less(), l_combine
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, l_combine1, l_block, xbuf
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, n_block_a, n_block_b, l_irreg1, l_irreg2, true); //Outputs
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BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A combine: ", len);
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BOOST_ASSERT(xbuf.size() >= l_block);
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op_merge_blocks_with_buf
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(uint_keys, less(), first, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp, move_op(), xbuf.data());
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xbuf.clear();
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BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" A mrg buf: ", len);
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}
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}
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template<class RandIt, class Compare, class XBuf>
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inline void adaptive_merge_final_merge( RandIt first
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, typename iter_size<RandIt>::type len1
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, typename iter_size<RandIt>::type len2
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, typename iter_size<RandIt>::type collected
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, typename iter_size<RandIt>::type l_intbuf
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, typename iter_size<RandIt>::type //l_block
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, bool //use_internal_buf
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, bool xbuf_used
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, Compare comp
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, XBuf & xbuf
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)
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{
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typedef typename iter_size<RandIt>::type size_type;
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size_type n_keys = size_type(collected-l_intbuf);
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size_type len = size_type(len1+len2);
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if (!xbuf_used || n_keys) {
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xbuf.clear();
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const size_type middle = xbuf_used && n_keys ? n_keys: collected;
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unstable_sort(first, first + middle, comp, xbuf);
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BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2(" A k/b srt: ", len);
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stable_merge(first, first + middle, first + len, comp, xbuf);
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}
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BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1(" A fin mrg: ", len);
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}
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template<class SizeType>
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inline static SizeType adaptive_merge_n_keys_without_external_keys(SizeType l_block, SizeType len1, SizeType len2, SizeType l_intbuf)
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{
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typedef SizeType size_type;
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//This is the minimum number of keys to implement the ideal algorithm
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size_type n_keys = size_type(len1/l_block + len2/l_block);
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const size_type second_half_blocks = size_type(len2/l_block);
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const size_type first_half_aux = size_type(len1 - l_intbuf);
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while(n_keys >= ((first_half_aux-n_keys)/l_block + second_half_blocks)){
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--n_keys;
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}
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++n_keys;
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return n_keys;
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}
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template<class SizeType>
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inline static SizeType adaptive_merge_n_keys_with_external_keys(SizeType l_block, SizeType len1, SizeType len2, SizeType l_intbuf)
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{
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typedef SizeType size_type;
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//This is the minimum number of keys to implement the ideal algorithm
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size_type n_keys = size_type((len1-l_intbuf)/l_block + len2/l_block);
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return n_keys;
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}
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template<class SizeType, class Xbuf>
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inline SizeType adaptive_merge_n_keys_intbuf(SizeType &rl_block, SizeType len1, SizeType len2, Xbuf & xbuf, SizeType &l_intbuf_inout)
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{
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typedef SizeType size_type;
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size_type l_block = rl_block;
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size_type l_intbuf = xbuf.capacity() >= l_block ? 0u : l_block;
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if (xbuf.capacity() > l_block){
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l_block = xbuf.capacity();
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}
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//This is the minimum number of keys to implement the ideal algorithm
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size_type n_keys = adaptive_merge_n_keys_without_external_keys(l_block, len1, len2, l_intbuf);
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BOOST_ASSERT(n_keys >= ((len1-l_intbuf-n_keys)/l_block + len2/l_block));
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if(xbuf.template supports_aligned_trailing<size_type>
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( l_block
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, adaptive_merge_n_keys_with_external_keys(l_block, len1, len2, l_intbuf)))
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{
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n_keys = 0u;
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}
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l_intbuf_inout = l_intbuf;
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rl_block = l_block;
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return n_keys;
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}
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// Main explanation of the merge algorithm.
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//
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// csqrtlen = ceil(sqrt(len));
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//
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// * First, csqrtlen [to be used as buffer] + (len/csqrtlen - 1) [to be used as keys] => to_collect
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// unique elements are extracted from elements to be sorted and placed in the beginning of the range.
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//
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// * Step "combine_blocks": the leading (len1-to_collect) elements plus trailing len2 elements
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// are merged with a non-trivial ("smart") algorithm to form an ordered range trailing "len-to_collect" elements.
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//
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// Explanation of the "combine_blocks" step:
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//
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// * Trailing [first+to_collect, first+len1) elements are divided in groups of cqrtlen elements.
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// Remaining elements that can't form a group are grouped in front of those elements.
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// * Trailing [first+len1, first+len1+len2) elements are divided in groups of cqrtlen elements.
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// Remaining elements that can't form a group are grouped in the back of those elements.
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// * In parallel the following two steps are performed:
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// * Groups are selection-sorted by first or last element (depending whether they are going
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// to be merged to left or right) and keys are reordered accordingly as an imitation-buffer.
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// * Elements of each block pair are merged using the csqrtlen buffer taking into account
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// if they belong to the first half or second half (marked by the key).
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//
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// * In the final merge step leading "to_collect" elements are merged with rotations
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// with the rest of merged elements in the "combine_blocks" step.
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//
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// Corner cases:
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//
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// * If no "to_collect" elements can be extracted:
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//
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// * If more than a minimum number of elements is extracted
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// then reduces the number of elements used as buffer and keys in the
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// and "combine_blocks" steps. If "combine_blocks" has no enough keys due to this reduction
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// then uses a rotation based smart merge.
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//
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// * If the minimum number of keys can't be extracted, a rotation-based merge is performed.
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//
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// * If auxiliary memory is more or equal than min(len1, len2), a buffered merge is performed.
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//
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// * If the len1 or len2 are less than 2*csqrtlen then a rotation-based merge is performed.
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//
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// * If auxiliary memory is more than csqrtlen+n_keys*sizeof(std::size_t),
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// then no csqrtlen need to be extracted and "combine_blocks" will use integral
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// keys to combine blocks.
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template<class RandIt, class Compare, class XBuf>
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void adaptive_merge_impl
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( RandIt first
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, typename iter_size<RandIt>::type len1
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, typename iter_size<RandIt>::type len2
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, Compare comp
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, XBuf & xbuf
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)
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{
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typedef typename iter_size<RandIt>::type size_type;
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if(xbuf.capacity() >= min_value<size_type>(len1, len2)){
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buffered_merge( first, first+len1
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, first + len1+len2, comp, xbuf);
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}
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else{
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const size_type len = size_type(len1+len2);
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//Calculate ideal parameters and try to collect needed unique keys
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size_type l_block = size_type(ceil_sqrt(len));
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//One range is not big enough to extract keys and the internal buffer so a
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//rotation-based based merge will do just fine
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if(len1 <= l_block*2 || len2 <= l_block*2){
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merge_bufferless(first, first+len1, first+len1+len2, comp);
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return;
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}
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//Detail the number of keys and internal buffer. If xbuf has enough memory, no
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//internal buffer is needed so l_intbuf will remain 0.
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size_type l_intbuf = 0;
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size_type n_keys = adaptive_merge_n_keys_intbuf(l_block, len1, len2, xbuf, l_intbuf);
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size_type const to_collect = size_type(l_intbuf+n_keys);
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//Try to extract needed unique values from the first range
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size_type const collected = collect_unique(first, first+len1, to_collect, comp, xbuf);
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BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1("\n A collect: ", len);
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//Not the minimum number of keys is not available on the first range, so fallback to rotations
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if(collected != to_collect && collected < 4){
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merge_bufferless(first, first+collected, first+len1, comp);
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merge_bufferless(first, first + len1, first + len1 + len2, comp);
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return;
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}
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//If not enough keys but more than minimum, adjust the internal buffer and key count
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bool use_internal_buf = collected == to_collect;
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if (!use_internal_buf){
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l_intbuf = 0u;
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n_keys = collected;
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l_block = lblock_for_combine(l_intbuf, n_keys, len, use_internal_buf);
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//If use_internal_buf is false, then then internal buffer will be zero and rotation-based combination will be used
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l_intbuf = use_internal_buf ? l_block : 0u;
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}
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bool const xbuf_used = collected == to_collect && xbuf.capacity() >= l_block;
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//Merge trailing elements using smart merges
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adaptive_merge_combine_blocks(first, len1, len2, collected, n_keys, l_block, use_internal_buf, xbuf_used, comp, xbuf);
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//Merge buffer and keys with the rest of the values
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adaptive_merge_final_merge (first, len1, len2, collected, l_intbuf, l_block, use_internal_buf, xbuf_used, comp, xbuf);
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}
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}
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} //namespace detail_adaptive {
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///@endcond
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//! <b>Effects</b>: Merges two consecutive sorted ranges [first, middle) and [middle, last)
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//! into one sorted range [first, last) according to the given comparison function comp.
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//! The algorithm is stable (if there are equivalent elements in the original two ranges,
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//! the elements from the first range (preserving their original order) precede the elements
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//! from the second range (preserving their original order).
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//!
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//! <b>Requires</b>:
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//! - RandIt must meet the requirements of ValueSwappable and RandomAccessIterator.
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//! - The type of dereferenced RandIt must meet the requirements of MoveAssignable and MoveConstructible.
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//!
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//! <b>Parameters</b>:
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//! - first: the beginning of the first sorted range.
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//! - middle: the end of the first sorted range and the beginning of the second
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//! - last: the end of the second sorted range
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//! - comp: comparison function object which returns true if the first argument is is ordered before the second.
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//! - uninitialized, uninitialized_len: raw storage starting on "uninitialized", able to hold "uninitialized_len"
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//! elements of type iterator_traits<RandIt>::value_type. Maximum performance is achieved when uninitialized_len
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//! is min(std::distance(first, middle), std::distance(middle, last)).
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//!
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//! <b>Throws</b>: If comp throws or the move constructor, move assignment or swap of the type
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//! of dereferenced RandIt throws.
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//!
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//! <b>Complexity</b>: Always K x O(N) comparisons and move assignments/constructors/swaps.
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//! Constant factor for comparisons and data movement is minimized when uninitialized_len
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//! is min(std::distance(first, middle), std::distance(middle, last)).
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//! Pretty good enough performance is achieved when uninitialized_len is
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//! ceil(sqrt(std::distance(first, last)))*2.
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//!
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//! <b>Caution</b>: Experimental implementation, not production-ready.
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template<class RandIt, class Compare>
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void adaptive_merge( RandIt first, RandIt middle, RandIt last, Compare comp
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, typename iterator_traits<RandIt>::value_type* uninitialized = 0
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, typename iter_size<RandIt>::type uninitialized_len = 0)
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{
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typedef typename iter_size<RandIt>::type size_type;
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typedef typename iterator_traits<RandIt>::value_type value_type;
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if (first == middle || middle == last){
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return;
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}
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//Reduce ranges to merge if possible
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do {
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if (comp(*middle, *first)){
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break;
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}
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++first;
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if (first == middle)
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return;
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} while(1);
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RandIt first_high(middle);
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--first_high;
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do {
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--last;
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if (comp(*last, *first_high)){
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++last;
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break;
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}
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if (last == middle)
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return;
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} while(1);
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::boost::movelib::adaptive_xbuf<value_type, value_type*, size_type> xbuf(uninitialized, size_type(uninitialized_len));
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::boost::movelib::detail_adaptive::adaptive_merge_impl(first, size_type(middle - first), size_type(last - middle), comp, xbuf);
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}
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} //namespace movelib {
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} //namespace boost {
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#if defined(BOOST_CLANG) || (defined(BOOST_GCC) && (BOOST_GCC >= 40600))
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#pragma GCC diagnostic pop
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#endif
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#include <boost/move/detail/config_end.hpp>
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#endif //#define BOOST_MOVE_ADAPTIVE_MERGE_HPP
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