cavis/libnd4j/include/loops/cuda/specials/averagingKernel.cu

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/*******************************************************************************
* 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 <loops/special_kernels.h>
namespace sd {
///////////////////////////////////////////////////////////////////////
template<typename T>
__device__ void averagingKernel(void **vdx, void *vdz, int n, Nd4jLong length, bool propagate) {
auto dx = reinterpret_cast<T **>(vdx);
auto dz = reinterpret_cast<T *>(vdz);
__shared__
T *shmem;
if (threadIdx.x == 0) {
extern __shared__ unsigned char sharedmem[];
shmem = (T *) sharedmem;
}
__syncthreads();
// each block cycles over it's own part of arrays
for (int r = blockDim.x * blockIdx.x; r < length; r += blockDim.x * gridDim.x) {
shmem[threadIdx.x] = (T) 0.0f;
Nd4jLong baseIdx = r;
// aggregation step, we roll over all arrays
for (int ar = 0; ar < n; ar++) {
T *cdata = (T *) dx[ar];
cdata += baseIdx;
if (baseIdx + threadIdx.x < length)
shmem[threadIdx.x] += cdata[threadIdx.x];
}
// average data in shared memory
if (baseIdx + threadIdx.x < length)
shmem[threadIdx.x] /= n;
// div step & write out step
if (dz != nullptr) {
T *wdata = dz + baseIdx;
if (baseIdx + threadIdx.x < length) {
wdata[threadIdx.x] = shmem[threadIdx.x];
}
}
// propagate averaged data to all arrays
if (propagate)
for (int ar = 0; ar < n; ar++) {
T *cdata = (T *) dx[ar];
cdata += baseIdx;
if (baseIdx + threadIdx.x < length)
cdata[threadIdx.x] = shmem[threadIdx.x];
}
}
}
///////////////////////////////////////////////////////////////////////
template<typename T>
__global__ void execAveragingKernel(void **vdx, void *vdz, int n, Nd4jLong length, bool propagate) {
averagingKernel<T>(vdx, vdz, n, length, propagate);
}
///////////////////////////////////////////////////////////////////////
template<typename T>
__host__ void
averagingKernelGeneric(dim3 &launchDims, cudaStream_t *stream, void **vdx, void *vdz, int n, Nd4jLong length,
bool propagate) {
execAveragingKernel<T><<< launchDims.x, launchDims.y, launchDims.z, *stream>>>(vdx, vdz, n, length, propagate);
sd::DebugHelper::checkErrorCode(stream, "averaging(...) failed");
}
BUILD_SINGLE_TEMPLATE(template void ND4J_EXPORT averagingKernelGeneric, (dim3 & launchDims, cudaStream_t * stream, void * *vdx, void * vdz, int n, Nd4jLong length, bool propagate), LIBND4J_TYPES);
}