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530 lines
19 KiB
Plaintext
530 lines
19 KiB
Plaintext
/* Copyright (c) 2022, 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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/*
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* Based on "Designing efficient sorting algorithms for manycore GPUs"
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* by Nadathur Satish, Mark Harris, and Michael Garland
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* http://mgarland.org/files/papers/gpusort-ipdps09.pdf
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*
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* Victor Podlozhnyuk 09/24/2009
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*/
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#include <assert.h>
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#include <cooperative_groups.h>
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namespace cg = cooperative_groups;
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#include <helper_cuda.h>
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#include "mergeSort_common.h"
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////////////////////////////////////////////////////////////////////////////////
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// Helper functions
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////////////////////////////////////////////////////////////////////////////////
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static inline __host__ __device__ uint iDivUp(uint a, uint b) {
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return ((a % b) == 0) ? (a / b) : (a / b + 1);
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}
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static inline __host__ __device__ uint getSampleCount(uint dividend) {
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return iDivUp(dividend, SAMPLE_STRIDE);
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}
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#define W (sizeof(uint) * 8)
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static inline __device__ uint nextPowerOfTwo(uint x) {
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/*
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--x;
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x |= x >> 1;
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x |= x >> 2;
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x |= x >> 4;
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x |= x >> 8;
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x |= x >> 16;
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return ++x;
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*/
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return 1U << (W - __clz(x - 1));
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}
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template <uint sortDir>
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static inline __device__ uint binarySearchInclusive(uint val, uint *data,
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uint L, uint stride) {
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if (L == 0) {
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return 0;
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}
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uint pos = 0;
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for (; stride > 0; stride >>= 1) {
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uint newPos = umin(pos + stride, L);
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if ((sortDir && (data[newPos - 1] <= val)) ||
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(!sortDir && (data[newPos - 1] >= val))) {
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pos = newPos;
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}
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}
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return pos;
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}
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template <uint sortDir>
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static inline __device__ uint binarySearchExclusive(uint val, uint *data,
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uint L, uint stride) {
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if (L == 0) {
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return 0;
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}
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uint pos = 0;
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for (; stride > 0; stride >>= 1) {
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uint newPos = umin(pos + stride, L);
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if ((sortDir && (data[newPos - 1] < val)) ||
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(!sortDir && (data[newPos - 1] > val))) {
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pos = newPos;
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}
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}
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return pos;
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}
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////////////////////////////////////////////////////////////////////////////////
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// Bottom-level merge sort (binary search-based)
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////////////////////////////////////////////////////////////////////////////////
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template <uint sortDir>
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__global__ void mergeSortSharedKernel(uint *d_DstKey, uint *d_DstVal,
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uint *d_SrcKey, uint *d_SrcVal,
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uint arrayLength) {
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// Handle to thread block group
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cg::thread_block cta = cg::this_thread_block();
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__shared__ uint s_key[SHARED_SIZE_LIMIT];
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__shared__ uint s_val[SHARED_SIZE_LIMIT];
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d_SrcKey += blockIdx.x * SHARED_SIZE_LIMIT + threadIdx.x;
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d_SrcVal += blockIdx.x * SHARED_SIZE_LIMIT + threadIdx.x;
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d_DstKey += blockIdx.x * SHARED_SIZE_LIMIT + threadIdx.x;
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d_DstVal += blockIdx.x * SHARED_SIZE_LIMIT + threadIdx.x;
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s_key[threadIdx.x + 0] = d_SrcKey[0];
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s_val[threadIdx.x + 0] = d_SrcVal[0];
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s_key[threadIdx.x + (SHARED_SIZE_LIMIT / 2)] =
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d_SrcKey[(SHARED_SIZE_LIMIT / 2)];
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s_val[threadIdx.x + (SHARED_SIZE_LIMIT / 2)] =
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d_SrcVal[(SHARED_SIZE_LIMIT / 2)];
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for (uint stride = 1; stride < arrayLength; stride <<= 1) {
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uint lPos = threadIdx.x & (stride - 1);
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uint *baseKey = s_key + 2 * (threadIdx.x - lPos);
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uint *baseVal = s_val + 2 * (threadIdx.x - lPos);
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cg::sync(cta);
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uint keyA = baseKey[lPos + 0];
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uint valA = baseVal[lPos + 0];
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uint keyB = baseKey[lPos + stride];
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uint valB = baseVal[lPos + stride];
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uint posA =
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binarySearchExclusive<sortDir>(keyA, baseKey + stride, stride, stride) +
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lPos;
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uint posB =
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binarySearchInclusive<sortDir>(keyB, baseKey + 0, stride, stride) +
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lPos;
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cg::sync(cta);
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baseKey[posA] = keyA;
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baseVal[posA] = valA;
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baseKey[posB] = keyB;
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baseVal[posB] = valB;
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}
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cg::sync(cta);
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d_DstKey[0] = s_key[threadIdx.x + 0];
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d_DstVal[0] = s_val[threadIdx.x + 0];
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d_DstKey[(SHARED_SIZE_LIMIT / 2)] =
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s_key[threadIdx.x + (SHARED_SIZE_LIMIT / 2)];
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d_DstVal[(SHARED_SIZE_LIMIT / 2)] =
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s_val[threadIdx.x + (SHARED_SIZE_LIMIT / 2)];
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}
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static void mergeSortShared(uint *d_DstKey, uint *d_DstVal, uint *d_SrcKey,
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uint *d_SrcVal, uint batchSize, uint arrayLength,
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uint sortDir) {
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if (arrayLength < 2) {
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return;
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}
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assert(SHARED_SIZE_LIMIT % arrayLength == 0);
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assert(((batchSize * arrayLength) % SHARED_SIZE_LIMIT) == 0);
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uint blockCount = batchSize * arrayLength / SHARED_SIZE_LIMIT;
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uint threadCount = SHARED_SIZE_LIMIT / 2;
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if (sortDir) {
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mergeSortSharedKernel<1U><<<blockCount, threadCount>>>(
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d_DstKey, d_DstVal, d_SrcKey, d_SrcVal, arrayLength);
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getLastCudaError("mergeSortShared<1><<<>>> failed\n");
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} else {
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mergeSortSharedKernel<0U><<<blockCount, threadCount>>>(
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d_DstKey, d_DstVal, d_SrcKey, d_SrcVal, arrayLength);
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getLastCudaError("mergeSortShared<0><<<>>> failed\n");
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}
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}
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////////////////////////////////////////////////////////////////////////////////
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// Merge step 1: generate sample ranks
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////////////////////////////////////////////////////////////////////////////////
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template <uint sortDir>
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__global__ void generateSampleRanksKernel(uint *d_RanksA, uint *d_RanksB,
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uint *d_SrcKey, uint stride, uint N,
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uint threadCount) {
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uint pos = blockIdx.x * blockDim.x + threadIdx.x;
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if (pos >= threadCount) {
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return;
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}
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const uint i = pos & ((stride / SAMPLE_STRIDE) - 1);
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const uint segmentBase = (pos - i) * (2 * SAMPLE_STRIDE);
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d_SrcKey += segmentBase;
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d_RanksA += segmentBase / SAMPLE_STRIDE;
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d_RanksB += segmentBase / SAMPLE_STRIDE;
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const uint segmentElementsA = stride;
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const uint segmentElementsB = umin(stride, N - segmentBase - stride);
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const uint segmentSamplesA = getSampleCount(segmentElementsA);
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const uint segmentSamplesB = getSampleCount(segmentElementsB);
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if (i < segmentSamplesA) {
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d_RanksA[i] = i * SAMPLE_STRIDE;
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d_RanksB[i] = binarySearchExclusive<sortDir>(
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d_SrcKey[i * SAMPLE_STRIDE], d_SrcKey + stride, segmentElementsB,
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nextPowerOfTwo(segmentElementsB));
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}
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if (i < segmentSamplesB) {
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d_RanksB[(stride / SAMPLE_STRIDE) + i] = i * SAMPLE_STRIDE;
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d_RanksA[(stride / SAMPLE_STRIDE) + i] = binarySearchInclusive<sortDir>(
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d_SrcKey[stride + i * SAMPLE_STRIDE], d_SrcKey + 0, segmentElementsA,
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nextPowerOfTwo(segmentElementsA));
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}
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}
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static void generateSampleRanks(uint *d_RanksA, uint *d_RanksB, uint *d_SrcKey,
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uint stride, uint N, uint sortDir) {
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uint lastSegmentElements = N % (2 * stride);
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uint threadCount =
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(lastSegmentElements > stride)
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? (N + 2 * stride - lastSegmentElements) / (2 * SAMPLE_STRIDE)
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: (N - lastSegmentElements) / (2 * SAMPLE_STRIDE);
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if (sortDir) {
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generateSampleRanksKernel<1U><<<iDivUp(threadCount, 256), 256>>>(
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d_RanksA, d_RanksB, d_SrcKey, stride, N, threadCount);
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getLastCudaError("generateSampleRanksKernel<1U><<<>>> failed\n");
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} else {
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generateSampleRanksKernel<0U><<<iDivUp(threadCount, 256), 256>>>(
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d_RanksA, d_RanksB, d_SrcKey, stride, N, threadCount);
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getLastCudaError("generateSampleRanksKernel<0U><<<>>> failed\n");
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}
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}
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////////////////////////////////////////////////////////////////////////////////
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// Merge step 2: generate sample ranks and indices
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////////////////////////////////////////////////////////////////////////////////
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__global__ void mergeRanksAndIndicesKernel(uint *d_Limits, uint *d_Ranks,
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uint stride, uint N,
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uint threadCount) {
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uint pos = blockIdx.x * blockDim.x + threadIdx.x;
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if (pos >= threadCount) {
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return;
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}
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const uint i = pos & ((stride / SAMPLE_STRIDE) - 1);
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const uint segmentBase = (pos - i) * (2 * SAMPLE_STRIDE);
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d_Ranks += (pos - i) * 2;
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d_Limits += (pos - i) * 2;
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const uint segmentElementsA = stride;
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const uint segmentElementsB = umin(stride, N - segmentBase - stride);
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const uint segmentSamplesA = getSampleCount(segmentElementsA);
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const uint segmentSamplesB = getSampleCount(segmentElementsB);
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if (i < segmentSamplesA) {
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uint dstPos = binarySearchExclusive<1U>(
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d_Ranks[i], d_Ranks + segmentSamplesA, segmentSamplesB,
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nextPowerOfTwo(segmentSamplesB)) +
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i;
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d_Limits[dstPos] = d_Ranks[i];
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}
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if (i < segmentSamplesB) {
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uint dstPos = binarySearchInclusive<1U>(d_Ranks[segmentSamplesA + i],
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d_Ranks, segmentSamplesA,
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nextPowerOfTwo(segmentSamplesA)) +
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i;
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d_Limits[dstPos] = d_Ranks[segmentSamplesA + i];
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}
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}
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static void mergeRanksAndIndices(uint *d_LimitsA, uint *d_LimitsB,
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uint *d_RanksA, uint *d_RanksB, uint stride,
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uint N) {
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uint lastSegmentElements = N % (2 * stride);
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uint threadCount =
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(lastSegmentElements > stride)
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? (N + 2 * stride - lastSegmentElements) / (2 * SAMPLE_STRIDE)
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: (N - lastSegmentElements) / (2 * SAMPLE_STRIDE);
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mergeRanksAndIndicesKernel<<<iDivUp(threadCount, 256), 256>>>(
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d_LimitsA, d_RanksA, stride, N, threadCount);
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getLastCudaError("mergeRanksAndIndicesKernel(A)<<<>>> failed\n");
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mergeRanksAndIndicesKernel<<<iDivUp(threadCount, 256), 256>>>(
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d_LimitsB, d_RanksB, stride, N, threadCount);
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getLastCudaError("mergeRanksAndIndicesKernel(B)<<<>>> failed\n");
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}
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////////////////////////////////////////////////////////////////////////////////
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// Merge step 3: merge elementary intervals
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////////////////////////////////////////////////////////////////////////////////
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template <uint sortDir>
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inline __device__ void merge(uint *dstKey, uint *dstVal, uint *srcAKey,
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uint *srcAVal, uint *srcBKey, uint *srcBVal,
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uint lenA, uint nPowTwoLenA, uint lenB,
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uint nPowTwoLenB, cg::thread_block cta) {
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uint keyA, valA, keyB, valB, dstPosA, dstPosB;
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if (threadIdx.x < lenA) {
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keyA = srcAKey[threadIdx.x];
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valA = srcAVal[threadIdx.x];
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dstPosA = binarySearchExclusive<sortDir>(keyA, srcBKey, lenB, nPowTwoLenB) +
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threadIdx.x;
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}
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if (threadIdx.x < lenB) {
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keyB = srcBKey[threadIdx.x];
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valB = srcBVal[threadIdx.x];
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dstPosB = binarySearchInclusive<sortDir>(keyB, srcAKey, lenA, nPowTwoLenA) +
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threadIdx.x;
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}
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cg::sync(cta);
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if (threadIdx.x < lenA) {
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dstKey[dstPosA] = keyA;
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dstVal[dstPosA] = valA;
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}
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if (threadIdx.x < lenB) {
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dstKey[dstPosB] = keyB;
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dstVal[dstPosB] = valB;
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}
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}
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template <uint sortDir>
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__global__ void mergeElementaryIntervalsKernel(uint *d_DstKey, uint *d_DstVal,
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uint *d_SrcKey, uint *d_SrcVal,
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uint *d_LimitsA, uint *d_LimitsB,
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uint stride, uint N) {
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// Handle to thread block group
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cg::thread_block cta = cg::this_thread_block();
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__shared__ uint s_key[2 * SAMPLE_STRIDE];
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__shared__ uint s_val[2 * SAMPLE_STRIDE];
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const uint intervalI = blockIdx.x & ((2 * stride) / SAMPLE_STRIDE - 1);
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const uint segmentBase = (blockIdx.x - intervalI) * SAMPLE_STRIDE;
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d_SrcKey += segmentBase;
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d_SrcVal += segmentBase;
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d_DstKey += segmentBase;
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d_DstVal += segmentBase;
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// Set up threadblock-wide parameters
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__shared__ uint startSrcA, startSrcB, lenSrcA, lenSrcB, startDstA, startDstB;
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if (threadIdx.x == 0) {
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uint segmentElementsA = stride;
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uint segmentElementsB = umin(stride, N - segmentBase - stride);
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uint segmentSamplesA = getSampleCount(segmentElementsA);
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uint segmentSamplesB = getSampleCount(segmentElementsB);
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uint segmentSamples = segmentSamplesA + segmentSamplesB;
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startSrcA = d_LimitsA[blockIdx.x];
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startSrcB = d_LimitsB[blockIdx.x];
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uint endSrcA = (intervalI + 1 < segmentSamples) ? d_LimitsA[blockIdx.x + 1]
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: segmentElementsA;
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uint endSrcB = (intervalI + 1 < segmentSamples) ? d_LimitsB[blockIdx.x + 1]
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: segmentElementsB;
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lenSrcA = endSrcA - startSrcA;
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lenSrcB = endSrcB - startSrcB;
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startDstA = startSrcA + startSrcB;
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startDstB = startDstA + lenSrcA;
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}
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// Load main input data
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cg::sync(cta);
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if (threadIdx.x < lenSrcA) {
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s_key[threadIdx.x + 0] = d_SrcKey[0 + startSrcA + threadIdx.x];
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s_val[threadIdx.x + 0] = d_SrcVal[0 + startSrcA + threadIdx.x];
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}
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if (threadIdx.x < lenSrcB) {
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s_key[threadIdx.x + SAMPLE_STRIDE] =
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d_SrcKey[stride + startSrcB + threadIdx.x];
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s_val[threadIdx.x + SAMPLE_STRIDE] =
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d_SrcVal[stride + startSrcB + threadIdx.x];
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}
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// Merge data in shared memory
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cg::sync(cta);
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merge<sortDir>(s_key, s_val, s_key + 0, s_val + 0, s_key + SAMPLE_STRIDE,
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s_val + SAMPLE_STRIDE, lenSrcA, SAMPLE_STRIDE, lenSrcB,
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SAMPLE_STRIDE, cta);
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// Store merged data
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cg::sync(cta);
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if (threadIdx.x < lenSrcA) {
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d_DstKey[startDstA + threadIdx.x] = s_key[threadIdx.x];
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d_DstVal[startDstA + threadIdx.x] = s_val[threadIdx.x];
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}
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if (threadIdx.x < lenSrcB) {
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d_DstKey[startDstB + threadIdx.x] = s_key[lenSrcA + threadIdx.x];
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d_DstVal[startDstB + threadIdx.x] = s_val[lenSrcA + threadIdx.x];
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}
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}
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static void mergeElementaryIntervals(uint *d_DstKey, uint *d_DstVal,
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uint *d_SrcKey, uint *d_SrcVal,
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uint *d_LimitsA, uint *d_LimitsB,
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uint stride, uint N, uint sortDir) {
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uint lastSegmentElements = N % (2 * stride);
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uint mergePairs = (lastSegmentElements > stride)
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? getSampleCount(N)
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: (N - lastSegmentElements) / SAMPLE_STRIDE;
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if (sortDir) {
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mergeElementaryIntervalsKernel<1U><<<mergePairs, SAMPLE_STRIDE>>>(
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d_DstKey, d_DstVal, d_SrcKey, d_SrcVal, d_LimitsA, d_LimitsB, stride,
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N);
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getLastCudaError("mergeElementaryIntervalsKernel<1> failed\n");
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} else {
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mergeElementaryIntervalsKernel<0U><<<mergePairs, SAMPLE_STRIDE>>>(
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d_DstKey, d_DstVal, d_SrcKey, d_SrcVal, d_LimitsA, d_LimitsB, stride,
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N);
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getLastCudaError("mergeElementaryIntervalsKernel<0> failed\n");
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}
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}
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extern "C" void bitonicSortShared(uint *d_DstKey, uint *d_DstVal,
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uint *d_SrcKey, uint *d_SrcVal,
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uint batchSize, uint arrayLength,
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uint sortDir);
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extern "C" void bitonicMergeElementaryIntervals(uint *d_DstKey, uint *d_DstVal,
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uint *d_SrcKey, uint *d_SrcVal,
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uint *d_LimitsA,
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uint *d_LimitsB, uint stride,
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uint N, uint sortDir);
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static uint *d_RanksA, *d_RanksB, *d_LimitsA, *d_LimitsB;
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static const uint MAX_SAMPLE_COUNT = 32768;
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extern "C" void initMergeSort(void) {
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checkCudaErrors(
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cudaMalloc((void **)&d_RanksA, MAX_SAMPLE_COUNT * sizeof(uint)));
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checkCudaErrors(
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cudaMalloc((void **)&d_RanksB, MAX_SAMPLE_COUNT * sizeof(uint)));
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checkCudaErrors(
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cudaMalloc((void **)&d_LimitsA, MAX_SAMPLE_COUNT * sizeof(uint)));
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checkCudaErrors(
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cudaMalloc((void **)&d_LimitsB, MAX_SAMPLE_COUNT * sizeof(uint)));
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}
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extern "C" void closeMergeSort(void) {
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checkCudaErrors(cudaFree(d_RanksA));
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checkCudaErrors(cudaFree(d_RanksB));
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checkCudaErrors(cudaFree(d_LimitsB));
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checkCudaErrors(cudaFree(d_LimitsA));
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}
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extern "C" void mergeSort(uint *d_DstKey, uint *d_DstVal, uint *d_BufKey,
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uint *d_BufVal, uint *d_SrcKey, uint *d_SrcVal,
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uint N, uint sortDir) {
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uint stageCount = 0;
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for (uint stride = SHARED_SIZE_LIMIT; stride < N; stride <<= 1, stageCount++)
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;
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uint *ikey, *ival, *okey, *oval;
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if (stageCount & 1) {
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ikey = d_BufKey;
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ival = d_BufVal;
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okey = d_DstKey;
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oval = d_DstVal;
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} else {
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ikey = d_DstKey;
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ival = d_DstVal;
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okey = d_BufKey;
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oval = d_BufVal;
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}
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assert(N <= (SAMPLE_STRIDE * MAX_SAMPLE_COUNT));
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assert(N % SHARED_SIZE_LIMIT == 0);
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mergeSortShared(ikey, ival, d_SrcKey, d_SrcVal, N / SHARED_SIZE_LIMIT,
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SHARED_SIZE_LIMIT, sortDir);
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for (uint stride = SHARED_SIZE_LIMIT; stride < N; stride <<= 1) {
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uint lastSegmentElements = N % (2 * stride);
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// Find sample ranks and prepare for limiters merge
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generateSampleRanks(d_RanksA, d_RanksB, ikey, stride, N, sortDir);
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// Merge ranks and indices
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mergeRanksAndIndices(d_LimitsA, d_LimitsB, d_RanksA, d_RanksB, stride, N);
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// Merge elementary intervals
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mergeElementaryIntervals(okey, oval, ikey, ival, d_LimitsA, d_LimitsB,
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stride, N, sortDir);
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if (lastSegmentElements <= stride) {
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// Last merge segment consists of a single array which just needs to be
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// passed through
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checkCudaErrors(cudaMemcpy(
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okey + (N - lastSegmentElements), ikey + (N - lastSegmentElements),
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lastSegmentElements * sizeof(uint), cudaMemcpyDeviceToDevice));
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checkCudaErrors(cudaMemcpy(
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oval + (N - lastSegmentElements), ival + (N - lastSegmentElements),
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lastSegmentElements * sizeof(uint), cudaMemcpyDeviceToDevice));
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}
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uint *t;
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t = ikey;
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ikey = okey;
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okey = t;
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t = ival;
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ival = oval;
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oval = t;
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}
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}
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