// -*- C++ -*- //===-- unseq_backend_simd.h ----------------------------------------------===// // // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // //===----------------------------------------------------------------------===// #ifndef _PSTL_UNSEQ_BACKEND_SIMD_H #define _PSTL_UNSEQ_BACKEND_SIMD_H #include #include "utils.h" // This header defines the minimum set of vector routines required // to support parallel STL. namespace __pstl { namespace __unseq_backend { // Expect vector width up to 64 (or 512 bit) const std::size_t __lane_size = 64; template _Iterator __simd_walk_1(_Iterator __first, _DifferenceType __n, _Function __f) noexcept { _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __n; ++__i) __f(__first[__i]); return __first + __n; } template _Iterator2 __simd_walk_2(_Iterator1 __first1, _DifferenceType __n, _Iterator2 __first2, _Function __f) noexcept { _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __n; ++__i) __f(__first1[__i], __first2[__i]); return __first2 + __n; } template _Iterator3 __simd_walk_3(_Iterator1 __first1, _DifferenceType __n, _Iterator2 __first2, _Iterator3 __first3, _Function __f) noexcept { _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __n; ++__i) __f(__first1[__i], __first2[__i], __first3[__i]); return __first3 + __n; } // TODO: check whether __simd_first() can be used here template bool __simd_or(_Index __first, _DifferenceType __n, _Pred __pred) noexcept { #if defined(_PSTL_EARLYEXIT_PRESENT) _DifferenceType __i; _PSTL_PRAGMA_VECTOR_UNALIGNED _PSTL_PRAGMA_SIMD_EARLYEXIT for (__i = 0; __i < __n; ++__i) if (__pred(__first[__i])) break; return __i < __n; #else _DifferenceType __block_size = 4 < __n ? 4 : __n; const _Index __last = __first + __n; while (__last != __first) { __INT32_TYPE__ __flag = 1; _PSTL_PRAGMA_SIMD_REDUCTION(& : __flag) for (_DifferenceType __i = 0; __i < __block_size; ++__i) if (__pred(*(__first + __i))) __flag = 0; if (!__flag) return true; __first += __block_size; if (__last - __first >= __block_size << 1) { // Double the block _Size. Any unnecessary iterations can be amortized against work done so far. __block_size <<= 1; } else { __block_size = __last - __first; } } return false; #endif } template _Index __simd_first(_Index __first, _DifferenceType __begin, _DifferenceType __end, _Compare __comp) noexcept { #if defined(_PSTL_EARLYEXIT_PRESENT) _DifferenceType __i = __begin; _PSTL_PRAGMA_VECTOR_UNALIGNED // Do not generate peel loop part _PSTL_PRAGMA_SIMD_EARLYEXIT for (; __i < __end; ++__i) { if (__comp(__first, __i)) { break; } } return __first + __i; #else // Experiments show good block sizes like this const _DifferenceType __block_size = 8; alignas(__lane_size) _DifferenceType __lane[__block_size] = {0}; while (__end - __begin >= __block_size) { _DifferenceType __found = 0; _PSTL_PRAGMA_VECTOR_UNALIGNED // Do not generate peel loop part _PSTL_PRAGMA_SIMD_REDUCTION(| : __found) for (_DifferenceType __i = __begin; __i < __begin + __block_size; ++__i) { const _DifferenceType __t = __comp(__first, __i); __lane[__i - __begin] = __t; __found |= __t; } if (__found) { _DifferenceType __i; // This will vectorize for (__i = 0; __i < __block_size; ++__i) { if (__lane[__i]) { break; } } return __first + __begin + __i; } __begin += __block_size; } //Keep remainder scalar while (__begin != __end) { if (__comp(__first, __begin)) { return __first + __begin; } ++__begin; } return __first + __end; #endif //_PSTL_EARLYEXIT_PRESENT } template std::pair<_Index1, _Index2> __simd_first(_Index1 __first1, _DifferenceType __n, _Index2 __first2, _Pred __pred) noexcept { #if defined(_PSTL_EARLYEXIT_PRESENT) _DifferenceType __i = 0; _PSTL_PRAGMA_VECTOR_UNALIGNED _PSTL_PRAGMA_SIMD_EARLYEXIT for (; __i < __n; ++__i) if (__pred(__first1[__i], __first2[__i])) break; return std::make_pair(__first1 + __i, __first2 + __i); #else const _Index1 __last1 = __first1 + __n; const _Index2 __last2 = __first2 + __n; // Experiments show good block sizes like this const _DifferenceType __block_size = 8; alignas(__lane_size) _DifferenceType __lane[__block_size] = {0}; while (__last1 - __first1 >= __block_size) { _DifferenceType __found = 0; _DifferenceType __i; _PSTL_PRAGMA_VECTOR_UNALIGNED // Do not generate peel loop part _PSTL_PRAGMA_SIMD_REDUCTION(| : __found) for (__i = 0; __i < __block_size; ++__i) { const _DifferenceType __t = __pred(__first1[__i], __first2[__i]); __lane[__i] = __t; __found |= __t; } if (__found) { _DifferenceType __i2; // This will vectorize for (__i2 = 0; __i2 < __block_size; ++__i2) { if (__lane[__i2]) break; } return std::make_pair(__first1 + __i2, __first2 + __i2); } __first1 += __block_size; __first2 += __block_size; } //Keep remainder scalar for (; __last1 != __first1; ++__first1, ++__first2) if (__pred(*(__first1), *(__first2))) return std::make_pair(__first1, __first2); return std::make_pair(__last1, __last2); #endif //_PSTL_EARLYEXIT_PRESENT } template _DifferenceType __simd_count(_Index __index, _DifferenceType __n, _Pred __pred) noexcept { _DifferenceType __count = 0; _PSTL_PRAGMA_SIMD_REDUCTION(+ : __count) for (_DifferenceType __i = 0; __i < __n; ++__i) if (__pred(*(__index + __i))) ++__count; return __count; } template _OutputIterator __simd_unique_copy(_InputIterator __first, _DifferenceType __n, _OutputIterator __result, _BinaryPredicate __pred) noexcept { if (__n == 0) return __result; _DifferenceType __cnt = 1; __result[0] = __first[0]; _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 1; __i < __n; ++__i) { _PSTL_PRAGMA_SIMD_ORDERED_MONOTONIC(__cnt : 1) if (!__pred(__first[__i], __first[__i - 1])) { __result[__cnt] = __first[__i]; ++__cnt; } } return __result + __cnt; } template _OutputIterator __simd_assign(_InputIterator __first, _DifferenceType __n, _OutputIterator __result, _Assigner __assigner) noexcept { _PSTL_USE_NONTEMPORAL_STORES_IF_ALLOWED _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __n; ++__i) __assigner(__first + __i, __result + __i); return __result + __n; } template _OutputIterator __simd_copy_if(_InputIterator __first, _DifferenceType __n, _OutputIterator __result, _UnaryPredicate __pred) noexcept { _DifferenceType __cnt = 0; _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __n; ++__i) { _PSTL_PRAGMA_SIMD_ORDERED_MONOTONIC(__cnt : 1) if (__pred(__first[__i])) { __result[__cnt] = __first[__i]; ++__cnt; } } return __result + __cnt; } template _DifferenceType __simd_calc_mask_2(_InputIterator __first, _DifferenceType __n, bool* __mask, _BinaryPredicate __pred) noexcept { _DifferenceType __count = 0; _PSTL_PRAGMA_SIMD_REDUCTION(+ : __count) for (_DifferenceType __i = 0; __i < __n; ++__i) { __mask[__i] = !__pred(__first[__i], __first[__i - 1]); __count += __mask[__i]; } return __count; } template _DifferenceType __simd_calc_mask_1(_InputIterator __first, _DifferenceType __n, bool* __mask, _UnaryPredicate __pred) noexcept { _DifferenceType __count = 0; _PSTL_PRAGMA_SIMD_REDUCTION(+ : __count) for (_DifferenceType __i = 0; __i < __n; ++__i) { __mask[__i] = __pred(__first[__i]); __count += __mask[__i]; } return __count; } template void __simd_copy_by_mask(_InputIterator __first, _DifferenceType __n, _OutputIterator __result, bool* __mask, _Assigner __assigner) noexcept { _DifferenceType __cnt = 0; _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __n; ++__i) { if (__mask[__i]) { _PSTL_PRAGMA_SIMD_ORDERED_MONOTONIC(__cnt : 1) { __assigner(__first + __i, __result + __cnt); ++__cnt; } } } } template void __simd_partition_by_mask(_InputIterator __first, _DifferenceType __n, _OutputIterator1 __out_true, _OutputIterator2 __out_false, bool* __mask) noexcept { _DifferenceType __cnt_true = 0, __cnt_false = 0; _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __n; ++__i) { _PSTL_PRAGMA_SIMD_ORDERED_MONOTONIC_2ARGS(__cnt_true : 1, __cnt_false : 1) if (__mask[__i]) { __out_true[__cnt_true] = __first[__i]; ++__cnt_true; } else { __out_false[__cnt_false] = __first[__i]; ++__cnt_false; } } } template _Index __simd_fill_n(_Index __first, _DifferenceType __n, const _Tp& __value) noexcept { _PSTL_USE_NONTEMPORAL_STORES_IF_ALLOWED _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __n; ++__i) __first[__i] = __value; return __first + __n; } template _Index __simd_generate_n(_Index __first, _DifferenceType __size, _Generator __g) noexcept { _PSTL_USE_NONTEMPORAL_STORES_IF_ALLOWED _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __size; ++__i) __first[__i] = __g(); return __first + __size; } template _Index __simd_adjacent_find(_Index __first, _Index __last, _BinaryPredicate __pred, bool __or_semantic) noexcept { if (__last - __first < 2) return __last; typedef typename std::iterator_traits<_Index>::difference_type _DifferenceType; _DifferenceType __i = 0; #if defined(_PSTL_EARLYEXIT_PRESENT) //Some compiler versions fail to compile the following loop when iterators are used. Indices are used instead const _DifferenceType __n = __last - __first - 1; _PSTL_PRAGMA_VECTOR_UNALIGNED _PSTL_PRAGMA_SIMD_EARLYEXIT for (; __i < __n; ++__i) if (__pred(__first[__i], __first[__i + 1])) break; return __i < __n ? __first + __i : __last; #else // Experiments show good block sizes like this //TODO: to consider tuning block_size for various data types const _DifferenceType __block_size = 8; alignas(__lane_size) _DifferenceType __lane[__block_size] = {0}; while (__last - __first >= __block_size) { _DifferenceType __found = 0; _PSTL_PRAGMA_VECTOR_UNALIGNED // Do not generate peel loop part _PSTL_PRAGMA_SIMD_REDUCTION(| : __found) for (__i = 0; __i < __block_size - 1; ++__i) { //TODO: to improve SIMD vectorization const _DifferenceType __t = __pred(*(__first + __i), *(__first + __i + 1)); __lane[__i] = __t; __found |= __t; } //Process a pair of elements on a boundary of a data block if (__first + __block_size < __last && __pred(*(__first + __i), *(__first + __i + 1))) __lane[__i] = __found = 1; if (__found) { if (__or_semantic) return __first; // This will vectorize for (__i = 0; __i < __block_size; ++__i) if (__lane[__i]) break; return __first + __i; //As far as found is true a __result (__lane[__i] is true) is guaranteed } __first += __block_size; } //Process the rest elements for (; __last - __first > 1; ++__first) if (__pred(*__first, *(__first + 1))) return __first; return __last; #endif } // It was created to reduce the code inside std::enable_if template using is_arithmetic_plus = std::integral_constant::value && std::is_same<_BinaryOperation, std::plus<_Tp>>::value>; template typename std::enable_if::value, _Tp>::type __simd_transform_reduce(_DifferenceType __n, _Tp __init, _BinaryOperation, _UnaryOperation __f) noexcept { _PSTL_PRAGMA_SIMD_REDUCTION(+ : __init) for (_DifferenceType __i = 0; __i < __n; ++__i) __init += __f(__i); return __init; } template typename std::enable_if::value, _Tp>::type __simd_transform_reduce(_Size __n, _Tp __init, _BinaryOperation __binary_op, _UnaryOperation __f) noexcept { const _Size __block_size = __lane_size / sizeof(_Tp); if (__n > 2 * __block_size && __block_size > 1) { alignas(__lane_size) char __lane_[__lane_size]; _Tp* __lane = reinterpret_cast<_Tp*>(__lane_); // initializer _PSTL_PRAGMA_SIMD for (_Size __i = 0; __i < __block_size; ++__i) { ::new (__lane + __i) _Tp(__binary_op(__f(__i), __f(__block_size + __i))); } // main loop _Size __i = 2 * __block_size; const _Size last_iteration = __block_size * (__n / __block_size); for (; __i < last_iteration; __i += __block_size) { _PSTL_PRAGMA_SIMD for (_Size __j = 0; __j < __block_size; ++__j) { __lane[__j] = __binary_op(__lane[__j], __f(__i + __j)); } } // remainder _PSTL_PRAGMA_SIMD for (_Size __j = 0; __j < __n - last_iteration; ++__j) { __lane[__j] = __binary_op(__lane[__j], __f(last_iteration + __j)); } // combiner for (_Size __j = 0; __j < __block_size; ++__j) { __init = __binary_op(__init, __lane[__j]); } // destroyer _PSTL_PRAGMA_SIMD for (_Size __j = 0; __j < __block_size; ++__j) { __lane[__j].~_Tp(); } } else { for (_Size __i = 0; __i < __n; ++__i) { __init = __binary_op(__init, __f(__i)); } } return __init; } // Exclusive scan for "+" and arithmetic types template typename std::enable_if::value, std::pair<_OutputIterator, _Tp>>::type __simd_scan(_InputIterator __first, _Size __n, _OutputIterator __result, _UnaryOperation __unary_op, _Tp __init, _BinaryOperation, /*Inclusive*/ std::false_type) { _PSTL_PRAGMA_SIMD_SCAN(+ : __init) for (_Size __i = 0; __i < __n; ++__i) { __result[__i] = __init; _PSTL_PRAGMA_SIMD_EXCLUSIVE_SCAN(__init) __init += __unary_op(__first[__i]); } return std::make_pair(__result + __n, __init); } // As soon as we cannot call __binary_op in "combiner" we create a wrapper over _Tp to encapsulate __binary_op template struct _Combiner { _Tp __value; _BinaryOp* __bin_op; // Here is a pointer to function because of default ctor _Combiner() : __value{}, __bin_op(nullptr) {} _Combiner(const _Tp& __v, const _BinaryOp* __b) : __value(__v), __bin_op(const_cast<_BinaryOp*>(__b)) {} _Combiner(const _Combiner& __obj) : __value{}, __bin_op(__obj.__bin_op) {} void operator()(const _Combiner& __obj) { __value = (*__bin_op)(__value, __obj.__value); } }; // Exclusive scan for other binary operations and types template typename std::enable_if::value, std::pair<_OutputIterator, _Tp>>::type __simd_scan(_InputIterator __first, _Size __n, _OutputIterator __result, _UnaryOperation __unary_op, _Tp __init, _BinaryOperation __binary_op, /*Inclusive*/ std::false_type) { typedef _Combiner<_Tp, _BinaryOperation> _CombinerType; _CombinerType __init_{__init, &__binary_op}; _PSTL_PRAGMA_DECLARE_REDUCTION(__bin_op, _CombinerType) _PSTL_PRAGMA_SIMD_SCAN(__bin_op : __init_) for (_Size __i = 0; __i < __n; ++__i) { __result[__i] = __init_.__value; _PSTL_PRAGMA_SIMD_EXCLUSIVE_SCAN(__init_) _PSTL_PRAGMA_FORCEINLINE __init_.__value = __binary_op(__init_.__value, __unary_op(__first[__i])); } return std::make_pair(__result + __n, __init_.__value); } // Inclusive scan for "+" and arithmetic types template typename std::enable_if::value, std::pair<_OutputIterator, _Tp>>::type __simd_scan(_InputIterator __first, _Size __n, _OutputIterator __result, _UnaryOperation __unary_op, _Tp __init, _BinaryOperation, /*Inclusive*/ std::true_type) { _PSTL_PRAGMA_SIMD_SCAN(+ : __init) for (_Size __i = 0; __i < __n; ++__i) { __init += __unary_op(__first[__i]); _PSTL_PRAGMA_SIMD_INCLUSIVE_SCAN(__init) __result[__i] = __init; } return std::make_pair(__result + __n, __init); } // Inclusive scan for other binary operations and types template typename std::enable_if::value, std::pair<_OutputIterator, _Tp>>::type __simd_scan(_InputIterator __first, _Size __n, _OutputIterator __result, _UnaryOperation __unary_op, _Tp __init, _BinaryOperation __binary_op, std::true_type) { typedef _Combiner<_Tp, _BinaryOperation> _CombinerType; _CombinerType __init_{__init, &__binary_op}; _PSTL_PRAGMA_DECLARE_REDUCTION(__bin_op, _CombinerType) _PSTL_PRAGMA_SIMD_SCAN(__bin_op : __init_) for (_Size __i = 0; __i < __n; ++__i) { _PSTL_PRAGMA_FORCEINLINE __init_.__value = __binary_op(__init_.__value, __unary_op(__first[__i])); _PSTL_PRAGMA_SIMD_INCLUSIVE_SCAN(__init_) __result[__i] = __init_.__value; } return std::make_pair(__result + __n, __init_.__value); } // [restriction] - std::iterator_traits<_ForwardIterator>::value_type should be DefaultConstructible. // complexity [violation] - We will have at most (__n-1 + number_of_lanes) comparisons instead of at most __n-1. template _ForwardIterator __simd_min_element(_ForwardIterator __first, _Size __n, _Compare __comp) noexcept { if (__n == 0) { return __first; } typedef typename std::iterator_traits<_ForwardIterator>::value_type _ValueType; struct _ComplexType { _ValueType __min_val; _Size __min_ind; _Compare* __min_comp; _ComplexType() : __min_val{}, __min_ind{}, __min_comp(nullptr) {} _ComplexType(const _ValueType& val, const _Compare* comp) : __min_val(val), __min_ind(0), __min_comp(const_cast<_Compare*>(comp)) { } _ComplexType(const _ComplexType& __obj) : __min_val(__obj.__min_val), __min_ind(__obj.__min_ind), __min_comp(__obj.__min_comp) { } _PSTL_PRAGMA_DECLARE_SIMD void operator()(const _ComplexType& __obj) { if (!(*__min_comp)(__min_val, __obj.__min_val) && ((*__min_comp)(__obj.__min_val, __min_val) || __obj.__min_ind - __min_ind < 0)) { __min_val = __obj.__min_val; __min_ind = __obj.__min_ind; } } }; _ComplexType __init{*__first, &__comp}; _PSTL_PRAGMA_DECLARE_REDUCTION(__min_func, _ComplexType) _PSTL_PRAGMA_SIMD_REDUCTION(__min_func : __init) for (_Size __i = 1; __i < __n; ++__i) { const _ValueType __min_val = __init.__min_val; const _ValueType __current = __first[__i]; if (__comp(__current, __min_val)) { __init.__min_val = __current; __init.__min_ind = __i; } } return __first + __init.__min_ind; } // [restriction] - std::iterator_traits<_ForwardIterator>::value_type should be DefaultConstructible. // complexity [violation] - We will have at most (2*(__n-1) + 4*number_of_lanes) comparisons instead of at most [1.5*(__n-1)]. template std::pair<_ForwardIterator, _ForwardIterator> __simd_minmax_element(_ForwardIterator __first, _Size __n, _Compare __comp) noexcept { if (__n == 0) { return std::make_pair(__first, __first); } typedef typename std::iterator_traits<_ForwardIterator>::value_type _ValueType; struct _ComplexType { _ValueType __min_val; _ValueType __max_val; _Size __min_ind; _Size __max_ind; _Compare* __minmax_comp; _ComplexType() : __min_val{}, __max_val{}, __min_ind{}, __max_ind{}, __minmax_comp(nullptr) {} _ComplexType(const _ValueType& __min, const _ValueType& __max, const _Compare* __comp) : __min_val(__min), __max_val(__max), __min_ind(0), __max_ind(0), __minmax_comp(const_cast<_Compare*>(__comp)) { } _ComplexType(const _ComplexType& __obj) : __min_val(__obj.__min_val), __max_val(__obj.__max_val), __min_ind(__obj.__min_ind), __max_ind(__obj.__max_ind), __minmax_comp(__obj.__minmax_comp) { } void operator()(const _ComplexType& __obj) { // min if ((*__minmax_comp)(__obj.__min_val, __min_val)) { __min_val = __obj.__min_val; __min_ind = __obj.__min_ind; } else if (!(*__minmax_comp)(__min_val, __obj.__min_val)) { __min_val = __obj.__min_val; __min_ind = (__min_ind - __obj.__min_ind < 0) ? __min_ind : __obj.__min_ind; } // max if ((*__minmax_comp)(__max_val, __obj.__max_val)) { __max_val = __obj.__max_val; __max_ind = __obj.__max_ind; } else if (!(*__minmax_comp)(__obj.__max_val, __max_val)) { __max_val = __obj.__max_val; __max_ind = (__max_ind - __obj.__max_ind < 0) ? __obj.__max_ind : __max_ind; } } }; _ComplexType __init{*__first, *__first, &__comp}; _PSTL_PRAGMA_DECLARE_REDUCTION(__min_func, _ComplexType); _PSTL_PRAGMA_SIMD_REDUCTION(__min_func : __init) for (_Size __i = 1; __i < __n; ++__i) { auto __min_val = __init.__min_val; auto __max_val = __init.__max_val; auto __current = __first + __i; if (__comp(*__current, __min_val)) { __init.__min_val = *__current; __init.__min_ind = __i; } else if (!__comp(*__current, __max_val)) { __init.__max_val = *__current; __init.__max_ind = __i; } } return std::make_pair(__first + __init.__min_ind, __first + __init.__max_ind); } template std::pair<_OutputIterator1, _OutputIterator2> __simd_partition_copy(_InputIterator __first, _DifferenceType __n, _OutputIterator1 __out_true, _OutputIterator2 __out_false, _UnaryPredicate __pred) noexcept { _DifferenceType __cnt_true = 0, __cnt_false = 0; _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 0; __i < __n; ++__i) { _PSTL_PRAGMA_SIMD_ORDERED_MONOTONIC_2ARGS(__cnt_true : 1, __cnt_false : 1) if (__pred(__first[__i])) { __out_true[__cnt_true] = __first[__i]; ++__cnt_true; } else { __out_false[__cnt_false] = __first[__i]; ++__cnt_false; } } return std::make_pair(__out_true + __cnt_true, __out_false + __cnt_false); } template _ForwardIterator1 __simd_find_first_of(_ForwardIterator1 __first, _ForwardIterator1 __last, _ForwardIterator2 __s_first, _ForwardIterator2 __s_last, _BinaryPredicate __pred) noexcept { typedef typename std::iterator_traits<_ForwardIterator1>::difference_type _DifferencType; const _DifferencType __n1 = __last - __first; const _DifferencType __n2 = __s_last - __s_first; if (__n1 == 0 || __n2 == 0) { return __last; // according to the standard } // Common case // If first sequence larger than second then we'll run simd_first with parameters of first sequence. // Otherwise, vice versa. if (__n1 < __n2) { for (; __first != __last; ++__first) { if (__unseq_backend::__simd_or( __s_first, __n2, __internal::__equal_value_by_pred(*__first, __pred))) { return __first; } } } else { for (; __s_first != __s_last; ++__s_first) { const auto __result = __unseq_backend::__simd_first( __first, _DifferencType(0), __n1, [__s_first, &__pred](_ForwardIterator1 __it, _DifferencType __i) { return __pred(__it[__i], *__s_first); }); if (__result != __last) { return __result; } } } return __last; } template _RandomAccessIterator __simd_remove_if(_RandomAccessIterator __first, _DifferenceType __n, _UnaryPredicate __pred) noexcept { // find first element we need to remove auto __current = __unseq_backend::__simd_first( __first, _DifferenceType(0), __n, [&__pred](_RandomAccessIterator __it, _DifferenceType __i) { return __pred(__it[__i]); }); __n -= __current - __first; // if we have in sequence only one element that pred(__current[1]) != false we can exit the function if (__n < 2) { return __current; } _DifferenceType __cnt = 0; _PSTL_PRAGMA_SIMD for (_DifferenceType __i = 1; __i < __n; ++__i) { _PSTL_PRAGMA_SIMD_ORDERED_MONOTONIC(__cnt : 1) if (!__pred(__current[__i])) { __current[__cnt] = std::move(__current[__i]); ++__cnt; } } return __current + __cnt; } } // namespace __unseq_backend } // namespace __pstl #endif /* _PSTL_UNSEQ_BACKEND_SIMD_H */