cuda-samples/Samples/MonteCarloMultiGPU/MonteCarlo_reduction.cuh
2021-10-21 16:34:49 +05:30

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/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
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#ifndef MONTECARLO_REDUCTION_CUH
#define MONTECARLO_REDUCTION_CUH
#include <cooperative_groups.h>
namespace cg = cooperative_groups;
////////////////////////////////////////////////////////////////////////////////
// This function calculates total sum for each of the two input arrays.
// SUM_N must be power of two
// Unrolling provides a bit of a performance improvement for small
// to medium path counts.
////////////////////////////////////////////////////////////////////////////////
template <class T, int SUM_N, int blockSize>
__device__ void sumReduce(T *sum, T *sum2, cg::thread_block &cta,
cg::thread_block_tile<32> &tile32,
__TOptionValue *d_CallValue) {
const int VEC = 32;
const int tid = cta.thread_rank();
T beta = sum[tid];
T beta2 = sum2[tid];
T temp, temp2;
for (int i = VEC / 2; i > 0; i >>= 1) {
if (tile32.thread_rank() < i) {
temp = sum[tid + i];
temp2 = sum2[tid + i];
beta += temp;
beta2 += temp2;
sum[tid] = beta;
sum2[tid] = beta2;
}
cg::sync(tile32);
}
cg::sync(cta);
if (tid == 0) {
beta = 0;
beta2 = 0;
for (int i = 0; i < blockDim.x; i += VEC) {
beta += sum[i];
beta2 += sum2[i];
}
__TOptionValue t = {beta, beta2};
*d_CallValue = t;
}
cg::sync(cta);
}
#endif