// -*- C++ -*- // Copyright (C) 2007-2020 Free Software Foundation, Inc. // // This file is part of the GNU ISO C++ Library. This library is free // software; you can redistribute it and/or modify it under the terms // of the GNU General Public License as published by the Free Software // Foundation; either version 3, or (at your option) any later // version. // This library is distributed in the hope that it will be useful, but // WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU // General Public License for more details. // Under Section 7 of GPL version 3, you are granted additional // permissions described in the GCC Runtime Library Exception, version // 3.1, as published by the Free Software Foundation. // You should have received a copy of the GNU General Public License and // a copy of the GCC Runtime Library Exception along with this program; // see the files COPYING3 and COPYING.RUNTIME respectively. If not, see // <http://www.gnu.org/licenses/>. /** @file parallel/random_shuffle.h * @brief Parallel implementation of std::random_shuffle(). * This file is a GNU parallel extension to the Standard C++ Library. */ // Written by Johannes Singler. #ifndef _GLIBCXX_PARALLEL_RANDOM_SHUFFLE_H #define _GLIBCXX_PARALLEL_RANDOM_SHUFFLE_H 1 #include <limits> #include <bits/stl_numeric.h> #include <parallel/parallel.h> #include <parallel/random_number.h> namespace __gnu_parallel { /** @brief Type to hold the index of a bin. * * Since many variables of this type are allocated, it should be * chosen as small as possible. */ typedef unsigned short _BinIndex; /** @brief Data known to every thread participating in __gnu_parallel::__parallel_random_shuffle(). */ template<typename _RAIter> struct _DRandomShufflingGlobalData { typedef std::iterator_traits<_RAIter> _TraitsType; typedef typename _TraitsType::value_type _ValueType; typedef typename _TraitsType::difference_type _DifferenceType; /** @brief Begin iterator of the __source. */ _RAIter& _M_source; /** @brief Temporary arrays for each thread. */ _ValueType** _M_temporaries; /** @brief Two-dimensional array to hold the thread-bin distribution. * * Dimensions (_M_num_threads + 1) __x (_M_num_bins + 1). */ _DifferenceType** _M_dist; /** @brief Start indexes of the threads' __chunks. */ _DifferenceType* _M_starts; /** @brief Number of the thread that will further process the corresponding bin. */ _ThreadIndex* _M_bin_proc; /** @brief Number of bins to distribute to. */ int _M_num_bins; /** @brief Number of bits needed to address the bins. */ int _M_num_bits; /** @brief Constructor. */ _DRandomShufflingGlobalData(_RAIter& __source) : _M_source(__source) { } }; /** @brief Local data for a thread participating in __gnu_parallel::__parallel_random_shuffle(). */ template<typename _RAIter, typename _RandomNumberGenerator> struct _DRSSorterPU { /** @brief Number of threads participating in total. */ int _M_num_threads; /** @brief Begin index for bins taken care of by this thread. */ _BinIndex _M_bins_begin; /** @brief End index for bins taken care of by this thread. */ _BinIndex __bins_end; /** @brief Random _M_seed for this thread. */ uint32_t _M_seed; /** @brief Pointer to global data. */ _DRandomShufflingGlobalData<_RAIter>* _M_sd; }; /** @brief Generate a random number in @c [0,2^__logp). * @param __logp Logarithm (basis 2) of the upper range __bound. * @param __rng Random number generator to use. */ template<typename _RandomNumberGenerator> inline int __random_number_pow2(int __logp, _RandomNumberGenerator& __rng) { return __rng.__genrand_bits(__logp); } /** @brief Random shuffle code executed by each thread. * @param __pus Array of thread-local data records. */ template<typename _RAIter, typename _RandomNumberGenerator> void __parallel_random_shuffle_drs_pu(_DRSSorterPU<_RAIter, _RandomNumberGenerator>* __pus) { typedef std::iterator_traits<_RAIter> _TraitsType; typedef typename _TraitsType::value_type _ValueType; typedef typename _TraitsType::difference_type _DifferenceType; _ThreadIndex __iam = omp_get_thread_num(); _DRSSorterPU<_RAIter, _RandomNumberGenerator>* __d = &__pus[__iam]; _DRandomShufflingGlobalData<_RAIter>* __sd = __d->_M_sd; // Indexing: _M_dist[bin][processor] _DifferenceType __length = (__sd->_M_starts[__iam + 1] - __sd->_M_starts[__iam]); _BinIndex* __oracles = new _BinIndex[__length]; _DifferenceType* __dist = new _DifferenceType[__sd->_M_num_bins + 1]; _BinIndex* __bin_proc = new _BinIndex[__sd->_M_num_bins]; _ValueType** __temporaries = new _ValueType*[__d->_M_num_threads]; // Compute oracles and count appearances. for (_BinIndex __b = 0; __b < __sd->_M_num_bins + 1; ++__b) __dist[__b] = 0; int __num_bits = __sd->_M_num_bits; _RandomNumber __rng(__d->_M_seed); // First main loop. for (_DifferenceType __i = 0; __i < __length; ++__i) { _BinIndex __oracle = __random_number_pow2(__num_bits, __rng); __oracles[__i] = __oracle; // To allow prefix (partial) sum. ++(__dist[__oracle + 1]); } for (_BinIndex __b = 0; __b < __sd->_M_num_bins + 1; ++__b) __sd->_M_dist[__b][__iam + 1] = __dist[__b]; # pragma omp barrier # pragma omp single { // Sum up bins, __sd->_M_dist[__s + 1][__d->_M_num_threads] now // contains the total number of items in bin __s for (_BinIndex __s = 0; __s < __sd->_M_num_bins; ++__s) __gnu_sequential::partial_sum(__sd->_M_dist[__s + 1], __sd->_M_dist[__s + 1] + __d->_M_num_threads + 1, __sd->_M_dist[__s + 1]); } # pragma omp barrier _SequenceIndex __offset = 0, __global_offset = 0; for (_BinIndex __s = 0; __s < __d->_M_bins_begin; ++__s) __global_offset += __sd->_M_dist[__s + 1][__d->_M_num_threads]; # pragma omp barrier for (_BinIndex __s = __d->_M_bins_begin; __s < __d->__bins_end; ++__s) { for (int __t = 0; __t < __d->_M_num_threads + 1; ++__t) __sd->_M_dist[__s + 1][__t] += __offset; __offset = __sd->_M_dist[__s + 1][__d->_M_num_threads]; } __sd->_M_temporaries[__iam] = static_cast<_ValueType*> (::operator new(sizeof(_ValueType) * __offset)); # pragma omp barrier // Draw local copies to avoid false sharing. for (_BinIndex __b = 0; __b < __sd->_M_num_bins + 1; ++__b) __dist[__b] = __sd->_M_dist[__b][__iam]; for (_BinIndex __b = 0; __b < __sd->_M_num_bins; ++__b) __bin_proc[__b] = __sd->_M_bin_proc[__b]; for (_ThreadIndex __t = 0; __t < __d->_M_num_threads; ++__t) __temporaries[__t] = __sd->_M_temporaries[__t]; _RAIter __source = __sd->_M_source; _DifferenceType __start = __sd->_M_starts[__iam]; // Distribute according to oracles, second main loop. for (_DifferenceType __i = 0; __i < __length; ++__i) { _BinIndex __target_bin = __oracles[__i]; _ThreadIndex __target_p = __bin_proc[__target_bin]; // Last column [__d->_M_num_threads] stays unchanged. ::new(&(__temporaries[__target_p][__dist[__target_bin + 1]++])) _ValueType(*(__source + __i + __start)); } delete[] __oracles; delete[] __dist; delete[] __bin_proc; delete[] __temporaries; # pragma omp barrier // Shuffle bins internally. for (_BinIndex __b = __d->_M_bins_begin; __b < __d->__bins_end; ++__b) { _ValueType* __begin = (__sd->_M_temporaries[__iam] + (__b == __d->_M_bins_begin ? 0 : __sd->_M_dist[__b][__d->_M_num_threads])), *__end = (__sd->_M_temporaries[__iam] + __sd->_M_dist[__b + 1][__d->_M_num_threads]); __sequential_random_shuffle(__begin, __end, __rng); std::copy(__begin, __end, __sd->_M_source + __global_offset + (__b == __d->_M_bins_begin ? 0 : __sd->_M_dist[__b][__d->_M_num_threads])); } for (_SequenceIndex __i = 0; __i < __offset; ++__i) __sd->_M_temporaries[__iam][__i].~_ValueType(); ::operator delete(__sd->_M_temporaries[__iam]); } /** @brief Round up to the next greater power of 2. * @param __x _Integer to round up */ template<typename _Tp> _Tp __round_up_to_pow2(_Tp __x) { if (__x <= 1) return 1; else return (_Tp)1 << (__rd_log2(__x - 1) + 1); } /** @brief Main parallel random shuffle step. * @param __begin Begin iterator of sequence. * @param __end End iterator of sequence. * @param __n Length of sequence. * @param __num_threads Number of threads to use. * @param __rng Random number generator to use. */ template<typename _RAIter, typename _RandomNumberGenerator> void __parallel_random_shuffle_drs(_RAIter __begin, _RAIter __end, typename std::iterator_traits <_RAIter>::difference_type __n, _ThreadIndex __num_threads, _RandomNumberGenerator& __rng) { typedef std::iterator_traits<_RAIter> _TraitsType; typedef typename _TraitsType::value_type _ValueType; typedef typename _TraitsType::difference_type _DifferenceType; _GLIBCXX_CALL(__n) const _Settings& __s = _Settings::get(); if (__num_threads > __n) __num_threads = static_cast<_ThreadIndex>(__n); _BinIndex __num_bins, __num_bins_cache; #if _GLIBCXX_RANDOM_SHUFFLE_CONSIDER_L1 // Try the L1 cache first. // Must fit into L1. __num_bins_cache = std::max<_DifferenceType>(1, __n / (__s.L1_cache_size_lb / sizeof(_ValueType))); __num_bins_cache = __round_up_to_pow2(__num_bins_cache); // No more buckets than TLB entries, power of 2 // Power of 2 and at least one element per bin, at most the TLB size. __num_bins = std::min<_DifferenceType>(__n, __num_bins_cache); #if _GLIBCXX_RANDOM_SHUFFLE_CONSIDER_TLB // 2 TLB entries needed per bin. __num_bins = std::min<_DifferenceType>(__s.TLB_size / 2, __num_bins); #endif __num_bins = __round_up_to_pow2(__num_bins); if (__num_bins < __num_bins_cache) { #endif // Now try the L2 cache // Must fit into L2 __num_bins_cache = static_cast<_BinIndex> (std::max<_DifferenceType>(1, __n / (__s.L2_cache_size / sizeof(_ValueType)))); __num_bins_cache = __round_up_to_pow2(__num_bins_cache); // No more buckets than TLB entries, power of 2. __num_bins = static_cast<_BinIndex> (std::min(__n, static_cast<_DifferenceType>(__num_bins_cache))); // Power of 2 and at least one element per bin, at most the TLB size. #if _GLIBCXX_RANDOM_SHUFFLE_CONSIDER_TLB // 2 TLB entries needed per bin. __num_bins = std::min(static_cast<_DifferenceType>(__s.TLB_size / 2), __num_bins); #endif __num_bins = __round_up_to_pow2(__num_bins); #if _GLIBCXX_RANDOM_SHUFFLE_CONSIDER_L1 } #endif __num_bins = __round_up_to_pow2( std::max<_BinIndex>(__num_threads, __num_bins)); if (__num_threads <= 1) { _RandomNumber __derived_rng( __rng(std::numeric_limits<uint32_t>::max())); __sequential_random_shuffle(__begin, __end, __derived_rng); return; } _DRandomShufflingGlobalData<_RAIter> __sd(__begin); _DRSSorterPU<_RAIter, _RandomNumber >* __pus; _DifferenceType* __starts; # pragma omp parallel num_threads(__num_threads) { _ThreadIndex __num_threads = omp_get_num_threads(); # pragma omp single { __pus = new _DRSSorterPU<_RAIter, _RandomNumber>[__num_threads]; __sd._M_temporaries = new _ValueType*[__num_threads]; __sd._M_dist = new _DifferenceType*[__num_bins + 1]; __sd._M_bin_proc = new _ThreadIndex[__num_bins]; for (_BinIndex __b = 0; __b < __num_bins + 1; ++__b) __sd._M_dist[__b] = new _DifferenceType[__num_threads + 1]; for (_BinIndex __b = 0; __b < (__num_bins + 1); ++__b) { __sd._M_dist[0][0] = 0; __sd._M_dist[__b][0] = 0; } __starts = __sd._M_starts = new _DifferenceType[__num_threads + 1]; int __bin_cursor = 0; __sd._M_num_bins = __num_bins; __sd._M_num_bits = __rd_log2(__num_bins); _DifferenceType __chunk_length = __n / __num_threads, __split = __n % __num_threads, __start = 0; _DifferenceType __bin_chunk_length = __num_bins / __num_threads, __bin_split = __num_bins % __num_threads; for (_ThreadIndex __i = 0; __i < __num_threads; ++__i) { __starts[__i] = __start; __start += (__i < __split ? (__chunk_length + 1) : __chunk_length); int __j = __pus[__i]._M_bins_begin = __bin_cursor; // Range of bins for this processor. __bin_cursor += (__i < __bin_split ? (__bin_chunk_length + 1) : __bin_chunk_length); __pus[__i].__bins_end = __bin_cursor; for (; __j < __bin_cursor; ++__j) __sd._M_bin_proc[__j] = __i; __pus[__i]._M_num_threads = __num_threads; __pus[__i]._M_seed = __rng(std::numeric_limits<uint32_t>::max()); __pus[__i]._M_sd = &__sd; } __starts[__num_threads] = __start; } //single // Now shuffle in parallel. __parallel_random_shuffle_drs_pu(__pus); } // parallel delete[] __starts; delete[] __sd._M_bin_proc; for (int __s = 0; __s < (__num_bins + 1); ++__s) delete[] __sd._M_dist[__s]; delete[] __sd._M_dist; delete[] __sd._M_temporaries; delete[] __pus; } /** @brief Sequential cache-efficient random shuffle. * @param __begin Begin iterator of sequence. * @param __end End iterator of sequence. * @param __rng Random number generator to use. */ template<typename _RAIter, typename _RandomNumberGenerator> void __sequential_random_shuffle(_RAIter __begin, _RAIter __end, _RandomNumberGenerator& __rng) { typedef std::iterator_traits<_RAIter> _TraitsType; typedef typename _TraitsType::value_type _ValueType; typedef typename _TraitsType::difference_type _DifferenceType; _DifferenceType __n = __end - __begin; const _Settings& __s = _Settings::get(); _BinIndex __num_bins, __num_bins_cache; #if _GLIBCXX_RANDOM_SHUFFLE_CONSIDER_L1 // Try the L1 cache first, must fit into L1. __num_bins_cache = std::max<_DifferenceType> (1, __n / (__s.L1_cache_size_lb / sizeof(_ValueType))); __num_bins_cache = __round_up_to_pow2(__num_bins_cache); // No more buckets than TLB entries, power of 2 // Power of 2 and at least one element per bin, at most the TLB size __num_bins = std::min(__n, (_DifferenceType)__num_bins_cache); #if _GLIBCXX_RANDOM_SHUFFLE_CONSIDER_TLB // 2 TLB entries needed per bin __num_bins = std::min((_DifferenceType)__s.TLB_size / 2, __num_bins); #endif __num_bins = __round_up_to_pow2(__num_bins); if (__num_bins < __num_bins_cache) { #endif // Now try the L2 cache, must fit into L2. __num_bins_cache = static_cast<_BinIndex> (std::max<_DifferenceType>(1, __n / (__s.L2_cache_size / sizeof(_ValueType)))); __num_bins_cache = __round_up_to_pow2(__num_bins_cache); // No more buckets than TLB entries, power of 2 // Power of 2 and at least one element per bin, at most the TLB size. __num_bins = static_cast<_BinIndex> (std::min(__n, static_cast<_DifferenceType>(__num_bins_cache))); #if _GLIBCXX_RANDOM_SHUFFLE_CONSIDER_TLB // 2 TLB entries needed per bin __num_bins = std::min<_DifferenceType>(__s.TLB_size / 2, __num_bins); #endif __num_bins = __round_up_to_pow2(__num_bins); #if _GLIBCXX_RANDOM_SHUFFLE_CONSIDER_L1 } #endif int __num_bits = __rd_log2(__num_bins); if (__num_bins > 1) { _ValueType* __target = static_cast<_ValueType*>(::operator new(sizeof(_ValueType) * __n)); _BinIndex* __oracles = new _BinIndex[__n]; _DifferenceType* __dist0 = new _DifferenceType[__num_bins + 1], * __dist1 = new _DifferenceType[__num_bins + 1]; for (int __b = 0; __b < __num_bins + 1; ++__b) __dist0[__b] = 0; _RandomNumber __bitrng(__rng(0xFFFFFFFF)); for (_DifferenceType __i = 0; __i < __n; ++__i) { _BinIndex __oracle = __random_number_pow2(__num_bits, __bitrng); __oracles[__i] = __oracle; // To allow prefix (partial) sum. ++(__dist0[__oracle + 1]); } // Sum up bins. __gnu_sequential::partial_sum(__dist0, __dist0 + __num_bins + 1, __dist0); for (int __b = 0; __b < __num_bins + 1; ++__b) __dist1[__b] = __dist0[__b]; // Distribute according to oracles. for (_DifferenceType __i = 0; __i < __n; ++__i) ::new(&(__target[(__dist0[__oracles[__i]])++])) _ValueType(*(__begin + __i)); for (int __b = 0; __b < __num_bins; ++__b) __sequential_random_shuffle(__target + __dist1[__b], __target + __dist1[__b + 1], __rng); // Copy elements back. std::copy(__target, __target + __n, __begin); delete[] __dist0; delete[] __dist1; delete[] __oracles; for (_DifferenceType __i = 0; __i < __n; ++__i) __target[__i].~_ValueType(); ::operator delete(__target); } else __gnu_sequential::random_shuffle(__begin, __end, __rng); } /** @brief Parallel random public call. * @param __begin Begin iterator of sequence. * @param __end End iterator of sequence. * @param __rng Random number generator to use. */ template<typename _RAIter, typename _RandomNumberGenerator> inline void __parallel_random_shuffle(_RAIter __begin, _RAIter __end, _RandomNumberGenerator __rng = _RandomNumber()) { typedef std::iterator_traits<_RAIter> _TraitsType; typedef typename _TraitsType::difference_type _DifferenceType; _DifferenceType __n = __end - __begin; __parallel_random_shuffle_drs(__begin, __end, __n, __get_max_threads(), __rng); } } #endif /* _GLIBCXX_PARALLEL_RANDOM_SHUFFLE_H */