/* Copyright (c) 2016 Baidu, Inc. All Rights Reserve. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #ifndef HL_DEVICE_FUNCTIONS_CUH_ #define HL_DEVICE_FUNCTIONS_CUH_ namespace paddle { template inline __device__ T paddleAtomicAdd(T* address, T val); template <> inline __device__ float paddleAtomicAdd(float* address, float val) { return atomicAdd(address, val); } template <> inline __device__ double paddleAtomicAdd(double* address, double val) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 600 return atomicAdd(address, val); #else // NOLINTNEXTLINE unsigned long long int* address_as_ull = (unsigned long long int*)address; unsigned long long int old = *address_as_ull, assumed; // NOLINT do { assumed = old; old = atomicCAS(address_as_ull, assumed, __double_as_longlong(val + __longlong_as_double(assumed))); } while (assumed != old); return __longlong_as_double(old); #endif } } // namespace paddle /** * @brief sum reduction * * @param[in,out] smem input data, better to use __shared__ memory. * @param[in] tid thread index. * @param[in] threads the total thread number used to reduce, * such as, blockDim.x. * * @return smem[0]: the sum of each elements in smem. */ __device__ __forceinline__ void simpleReduce(real* smem, int tid, int threads) { for (unsigned int s = threads / 2; s > 0; s >>= 1) { if (tid < s) { smem[tid] += smem[tid + s]; } __syncthreads(); } } #endif /* HL_DEVICE_FUNCTIONS_CUH_ */