85be0b8c65
upstream commit 0604154e006e88e9e7f82d8ee5fd076bda206613
91 lines
3.5 KiB
Plaintext
Vendored
91 lines
3.5 KiB
Plaintext
Vendored
/*===---- cmath - CUDA wrapper for <cmath> ---------------------------------===
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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* THE SOFTWARE.
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*
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*===-----------------------------------------------------------------------===
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*/
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#ifndef __CLANG_CUDA_WRAPPERS_CMATH
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#define __CLANG_CUDA_WRAPPERS_CMATH
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#include_next <cmath>
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#if defined(_LIBCPP_STD_VER)
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// libc++ will need long double variants of these functions, but CUDA does not
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// provide them. We'll provide their declarations, which should allow the
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// headers to parse, but would not allow accidental use of them on a GPU.
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__attribute__((device)) long double logb(long double);
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__attribute__((device)) long double scalbn(long double, int);
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namespace std {
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// For __constexpr_fmin/fmax we only need device-side overloads before c++14
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// where they are not constexpr.
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#if _LIBCPP_STD_VER < 14
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__attribute__((device))
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inline _LIBCPP_HIDE_FROM_ABI _LIBCPP_CONSTEXPR_SINCE_CXX14 float __constexpr_fmax(float __x, float __y) _NOEXCEPT {
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return __builtin_fmaxf(__x, __y);
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}
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__attribute__((device))
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inline _LIBCPP_HIDE_FROM_ABI _LIBCPP_CONSTEXPR_SINCE_CXX14 double __constexpr_fmax(double __x, double __y) _NOEXCEPT {
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return __builtin_fmax(__x, __y);
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}
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__attribute__((device))
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inline _LIBCPP_HIDE_FROM_ABI _LIBCPP_CONSTEXPR_SINCE_CXX14 long double
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__constexpr_fmax(long double __x, long double __y) _NOEXCEPT {
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return __builtin_fmaxl(__x, __y);
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}
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template <class _Tp, class _Up, __enable_if_t<is_arithmetic<_Tp>::value && is_arithmetic<_Up>::value, int> = 0>
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__attribute__((device))
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_LIBCPP_HIDE_FROM_ABI _LIBCPP_CONSTEXPR_SINCE_CXX14 typename __promote<_Tp, _Up>::type
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__constexpr_fmax(_Tp __x, _Up __y) _NOEXCEPT {
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using __result_type = typename __promote<_Tp, _Up>::type;
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return std::__constexpr_fmax(static_cast<__result_type>(__x), static_cast<__result_type>(__y));
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}
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#endif // _LIBCPP_STD_VER < 14
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// For logb/scalbn templates we must always provide device overloads because
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// libc++ implementation uses __builtin_XXX which gets translated into a libcall
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// which we can't handle on GPU. We need to forward those to CUDA-provided
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// implementations.
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template <class _Tp>
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__attribute__((device))
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_LIBCPP_HIDE_FROM_ABI _LIBCPP_CONSTEXPR_SINCE_CXX14 _Tp __constexpr_logb(_Tp __x) {
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return ::logb(__x);
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}
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template <class _Tp>
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__attribute__((device))
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_LIBCPP_HIDE_FROM_ABI _LIBCPP_CONSTEXPR_SINCE_CXX20 _Tp __constexpr_scalbn(_Tp __x, int __exp) {
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return ::scalbn(__x, __exp);
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}
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} // namespace std//
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#endif // _LIBCPP_STD_VER
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#endif // include guard
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