mirror of
https://github.com/NVIDIA/cuda-samples.git
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177 lines
5.6 KiB
C
177 lines
5.6 KiB
C
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/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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// Type-specific implementation of rounded arithmetic operators.
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// Thin layer over the CUDA intrinsics.
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#ifndef CUDA_INTERVAL_ROUNDED_ARITH_H
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#define CUDA_INTERVAL_ROUNDED_ARITH_H
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// Generic class, no actual implementation yet
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template <class T>
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struct rounded_arith {
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__device__ T add_down(const T &x, const T &y);
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__device__ T add_up(const T &x, const T &y);
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__device__ T sub_down(const T &x, const T &y);
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__device__ T sub_up(const T &x, const T &y);
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__device__ T mul_down(const T &x, const T &y);
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__device__ T mul_up(const T &x, const T &y);
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__device__ T div_down(const T &x, const T &y);
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__device__ T div_up(const T &x, const T &y);
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__device__ T median(const T &x, const T &y);
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__device__ T sqrt_down(const T &x);
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__device__ T sqrt_up(const T &x);
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__device__ T int_down(const T &x);
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__device__ T int_up(const T &x);
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__device__ T pos_inf();
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__device__ T neg_inf();
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__device__ __host__ T nan();
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__device__ T min(T const &x, T const &y);
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__device__ T max(T const &x, T const &y);
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};
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// Specialization for float
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template <>
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struct rounded_arith<float> {
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__device__ float add_down(const float &x, const float &y) {
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return __fadd_rd(x, y);
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}
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__device__ float add_up(const float &x, const float &y) {
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return __fadd_ru(x, y);
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}
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__device__ float sub_down(const float &x, const float &y) {
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return __fadd_rd(x, -y);
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}
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__device__ float sub_up(const float &x, const float &y) {
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return __fadd_ru(x, -y);
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}
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__device__ float mul_down(const float &x, const float &y) {
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return __fmul_rd(x, y);
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}
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__device__ float mul_up(const float &x, const float &y) {
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return __fmul_ru(x, y);
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}
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__device__ float div_down(const float &x, const float &y) {
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return __fdiv_rd(x, y);
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}
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__device__ float div_up(const float &x, const float &y) {
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return __fdiv_ru(x, y);
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}
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__device__ float median(const float &x, const float &y) {
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return (x + y) * .5f;
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}
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__device__ float sqrt_down(const float &x) { return __fsqrt_rd(x); }
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__device__ float sqrt_up(const float &x) { return __fsqrt_ru(x); }
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__device__ float int_down(const float &x) { return floorf(x); }
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__device__ float int_up(const float &x) { return ceilf(x); }
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__device__ float neg_inf() { return __int_as_float(0xff800000); }
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__device__ float pos_inf() { return __int_as_float(0x7f800000); }
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__device__ __host__ float nan() { return nanf(""); }
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__device__ float min(float const &x, float const &y) { return fminf(x, y); }
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__device__ float max(float const &x, float const &y) { return fmaxf(x, y); }
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};
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// Specialization for double
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template <>
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struct rounded_arith<double> {
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__device__ double add_down(const double &x, const double &y) {
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return __dadd_rd(x, y);
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}
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__device__ double add_up(const double &x, const double &y) {
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return __dadd_ru(x, y);
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}
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__device__ double sub_down(const double &x, const double &y) {
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return __dadd_rd(x, -y);
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}
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__device__ double sub_up(const double &x, const double &y) {
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return __dadd_ru(x, -y);
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}
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__device__ double mul_down(const double &x, const double &y) {
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return __dmul_rd(x, y);
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}
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__device__ double mul_up(const double &x, const double &y) {
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return __dmul_ru(x, y);
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}
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__device__ double div_down(const double &x, const double &y) {
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return __ddiv_rd(x, y);
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}
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__device__ double div_up(const double &x, const double &y) {
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return __ddiv_ru(x, y);
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}
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__device__ double median(const double &x, const double &y) {
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return (x + y) * .5;
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}
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__device__ double sqrt_down(const double &x) { return __dsqrt_rd(x); }
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__device__ double sqrt_up(const double &x) { return __dsqrt_ru(x); }
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__device__ double int_down(const double &x) { return floor(x); }
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__device__ double int_up(const double &x) { return ceil(x); }
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__device__ double neg_inf() {
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return __longlong_as_double(0xfff0000000000000ull);
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}
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__device__ double pos_inf() {
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return __longlong_as_double(0x7ff0000000000000ull);
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}
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__device__ __host__ double nan() { return ::nan(""); }
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__device__ double min(double const &x, double const &y) { return fmin(x, y); }
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__device__ double max(double const &x, double const &y) { return fmax(x, y); }
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};
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#endif
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