/******************************************************************************* * Copyright (c) 2015-2018 Skymind, Inc. * * This program and the accompanying materials are made available under the * terms of the Apache License, Version 2.0 which is available at * https://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. * * SPDX-License-Identifier: Apache-2.0 ******************************************************************************/ // // @author raver119@gmail.com // @author Yurii Shyrma, created on 15.11.2018 // #include namespace nd4j { /////////////////////////////////////////////////////////////////////// /** * This kernel accumulates X arrays, and stores z into Z * * @tparam T * @param x * @param z * @param n * @param length */ template __device__ void accumulateKernel(void **vx, void *vz, int n, const Nd4jLong length) { auto x = reinterpret_cast(vx); auto z = reinterpret_cast(vz); __shared__ T *shmem; if (threadIdx.x == 0) { extern __shared__ unsigned char sharedmem[]; shmem = (T *) sharedmem; } __syncthreads(); for (int r = blockDim.x * blockIdx.x; r < length; r += blockDim.x * gridDim.x) { shmem[threadIdx.x] = 0.0f; Nd4jLong baseIdx = r; // aggregation step, we roll over all arrays for (int ar = 0; ar < n; ar++) { T *cdata = (T *) x[ar]; cdata += baseIdx; if (baseIdx + threadIdx.x < length) shmem[threadIdx.x] += cdata[threadIdx.x]; } T *wdata = z + baseIdx; // saving accumulated values if (baseIdx + threadIdx.x < length) wdata[threadIdx.x] = shmem[threadIdx.x]; } } /////////////////////////////////////////////////////////////////////// template __global__ void execAccumulateKernel(void **vx, void *vz, int n, const Nd4jLong length) { accumulateKernel(vx, vz, n, length); } /////////////////////////////////////////////////////////////////////// template __host__ void accumulateKernelGeneric(dim3 &launchDims, cudaStream_t *stream, void **vx, void *vz, int n, const Nd4jLong length) { execAccumulateKernel<<< launchDims.x, launchDims.y, launchDims.z, *stream>>> (vx, vz, n, length); nd4j::DebugHelper::checkErrorCode(stream, "accumulate(...) failed"); } BUILD_SINGLE_TEMPLATE(template void ND4J_EXPORT accumulateKernelGeneric, (dim3 & launchDims, cudaStream_t * stream, void * *vx, void * vz, int n, const Nd4jLong length), LIBND4J_TYPES); }