143 lines
5.1 KiB
Plaintext
143 lines
5.1 KiB
Plaintext
/* ******************************************************************************
|
|
*
|
|
*
|
|
* 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.
|
|
*
|
|
* See the NOTICE file distributed with this work for additional
|
|
* information regarding copyright ownership.
|
|
* 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 28.11.2018
|
|
//
|
|
|
|
#include <ops/specials_cuda.h>
|
|
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template <typename X, typename Y>
|
|
__global__ void bitonicSortStepKernelKey(void *vx, Nd4jLong const* xShapeInfo, void *vy, Nd4jLong const* yShapeInfo, int j, int k, int length, bool descending) {
|
|
|
|
auto x = static_cast<X*>(vx);
|
|
auto y = static_cast<Y*>(vy);
|
|
|
|
unsigned int i, ixj; /* Sorting partners: i and ixj */
|
|
i = threadIdx.x + blockDim.x * blockIdx.x;
|
|
|
|
__shared__ Nd4jLong xLength;
|
|
if (threadIdx.x == 0)
|
|
xLength = shape::length(xShapeInfo);
|
|
|
|
__syncthreads();
|
|
|
|
|
|
if (i >= length)
|
|
return;
|
|
|
|
ixj = i^j;
|
|
|
|
/* The threads with the lowest ids sort the array. */
|
|
if ((ixj)>i) {
|
|
int posI = shape::getIndexOffset(i, xShapeInfo);
|
|
int posIXJ = shape::getIndexOffset(ixj, xShapeInfo);
|
|
|
|
if ((i&k)==0) {
|
|
/* Sort ascending */
|
|
if (!descending == (x[posI]>x[posIXJ])) {
|
|
/* exchange(i,ixj); */
|
|
X temp = x[posI];
|
|
x[posI] = x[posIXJ];
|
|
x[posIXJ] = temp;
|
|
|
|
Y ytemp = y[posI];
|
|
y[posI] = y[posIXJ];
|
|
y[posIXJ] = ytemp;
|
|
}
|
|
} else if ((i&k)!=0) {
|
|
/* Sort descending */
|
|
if (!descending == (x[posI]<x[posIXJ])) {
|
|
/* exchange(i,ixj); */
|
|
X temp = x[posI];
|
|
x[posI] = x[posIXJ];
|
|
x[posIXJ] = temp;
|
|
|
|
Y ytemp = y[posI];
|
|
y[posI] = y[posIXJ];
|
|
y[posIXJ] = ytemp;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template<typename T>
|
|
__global__ void bitonicSortStepKernel(void *vx, Nd4jLong const* xShapeInfo, int j, int k, int length, bool descending) {
|
|
|
|
auto x = static_cast<T*>(vx);
|
|
|
|
unsigned int i, ixj; /* Sorting partners: i and ixj */
|
|
i = threadIdx.x + blockDim.x * blockIdx.x;
|
|
|
|
__shared__ Nd4jLong xLength;
|
|
if (threadIdx.x == 0)
|
|
xLength = shape::length(xShapeInfo);
|
|
|
|
__syncthreads();
|
|
|
|
|
|
if (i >= length)
|
|
return;
|
|
|
|
ixj = i^j;
|
|
|
|
/* The threads with the lowest ids sort the array. */
|
|
if ((ixj)>i) {
|
|
int posI = shape::getIndexOffset(i, xShapeInfo);
|
|
int posIXJ = shape::getIndexOffset(ixj, xShapeInfo);
|
|
|
|
if ((i&k)==0) {
|
|
/* Sort ascending */
|
|
if (!descending == (x[posI]>x[posIXJ])) {
|
|
/* exchange(i,ixj); */
|
|
T temp = x[posI];
|
|
x[posI] = x[posIXJ];
|
|
x[posIXJ] = temp;
|
|
}
|
|
} else if ((i&k)!=0) {
|
|
/* Sort descending */
|
|
if (!descending == (x[posI]<x[posIXJ])) {
|
|
/* exchange(i,ixj); */
|
|
T temp = x[posI];
|
|
x[posI] = x[posIXJ];
|
|
x[posIXJ] = temp;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template<typename T>
|
|
__host__ void bitonicSortStepGeneric(dim3 &launchDims, cudaStream_t *stream, void *vx, Nd4jLong const* xShapeInfo, int j, int k, int length, bool descending) {
|
|
bitonicSortStepKernel<T><<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(vx, xShapeInfo, j, k, length, descending);
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
template <typename X, typename Y>
|
|
__host__ void bitonicSortStepGenericKey(dim3 &launchDims, cudaStream_t *stream, void *vx, Nd4jLong const* xShapeInfo, void *vy, Nd4jLong const* yShapeInfo, int j, int k, int length, bool descending) {
|
|
bitonicSortStepKernelKey<X,Y><<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(vx, xShapeInfo, vy, yShapeInfo, j, k, length, descending);
|
|
}
|
|
|
|
|
|
BUILD_SINGLE_TEMPLATE(template void ND4J_EXPORT bitonicSortStepGeneric, (dim3 &launchDims, cudaStream_t *stream, void *vx, Nd4jLong const* xShapeInfo, int j, int k, int length, bool descending), LIBND4J_TYPES);
|
|
BUILD_DOUBLE_TEMPLATE(template void ND4J_EXPORT bitonicSortStepGenericKey, (dim3 &launchDims, cudaStream_t *stream, void *vx, Nd4jLong const* xShapeInfo, void *vy, Nd4jLong const* yShapeInfo, int j, int k, int length, bool descending), LIBND4J_TYPES, LIBND4J_TYPES);
|