forked from NVIDIA/CUDALibrarySamples
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathcurand_scrambled_sobol32_poisson_example.cpp
129 lines (94 loc) · 3.63 KB
/
curand_scrambled_sobol32_poisson_example.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
/*
* This program uses the host CURAND API to generate 100
* quasirandom floats.
*/
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include <stdexcept>
#include <vector>
#include <cuda_runtime.h>
#include <curand.h>
#include "curand_utils.h"
using data_type = unsigned int;
void run_on_device(const int &n, const unsigned long long &offset,
const unsigned int &num_dimensions, const double &lambda,
const curandOrdering_t &order, const curandRngType_t &rng,
const cudaStream_t &stream, curandGenerator_t &gen,
std::vector<data_type> &h_data) {
data_type *d_data = nullptr;
/* C data to device */
CUDA_CHECK(cudaMalloc(reinterpret_cast<void **>(&d_data),
sizeof(data_type) * h_data.size()));
/* Create quasi-random number generator */
CURAND_CHECK(curandCreateGenerator(&gen, CURAND_RNG_QUASI_SCRAMBLED_SOBOL64));
/* Set cuRAND to stream */
CURAND_CHECK(curandSetStream(gen, stream));
/* Set offset */
CURAND_CHECK(curandSetGeneratorOffset(gen, offset));
/* Set Dimension */
CURAND_CHECK(curandSetQuasiRandomGeneratorDimensions(gen, num_dimensions));
/* Set ordering */
CURAND_CHECK(curandSetGeneratorOrdering(gen, order));
/* Generate n floats on device */
CURAND_CHECK(curandGeneratePoisson(gen, d_data, h_data.size(), lambda));
/* Copy data to host */
CUDA_CHECK(cudaMemcpyAsync(h_data.data(), d_data,
sizeof(data_type) * h_data.size(),
cudaMemcpyDeviceToHost, stream));
/* Sync stream */
CUDA_CHECK(cudaStreamSynchronize(stream));
/* Cleanup */
CUDA_CHECK(cudaFree(d_data));
CURAND_CHECK(curandDestroyGenerator(gen));
}
void run_on_host(const int &n, const unsigned long long &offset,
const unsigned int &num_dimensions, const double &lambda,
const curandOrdering_t &order, const curandRngType_t &rng,
const cudaStream_t &stream, curandGenerator_t &gen,
std::vector<data_type> &h_data) {
/* Create quasi-random number generator */
CURAND_CHECK(
curandCreateGeneratorHost(&gen, CURAND_RNG_QUASI_SCRAMBLED_SOBOL64));
/* Set cuRAND to stream */
CURAND_CHECK(curandSetStream(gen, stream));
/* Set offset */
CURAND_CHECK(curandSetGeneratorOffset(gen, offset));
/* Set Dimension */
CURAND_CHECK(curandSetQuasiRandomGeneratorDimensions(gen, num_dimensions));
/* Set ordering */
CURAND_CHECK(curandSetGeneratorOrdering(gen, order));
/* Generate n floats on device */
CURAND_CHECK(
curandGeneratePoisson(gen, h_data.data(), h_data.size(), lambda));
/* Cleanup */
CURAND_CHECK(curandDestroyGenerator(gen));
}
int main(int argc, char *argv[]) {
cudaStream_t stream = NULL;
curandGenerator_t gen = NULL;
curandRngType_t rng = CURAND_RNG_QUASI_SCRAMBLED_SOBOL64;
curandOrdering_t order = CURAND_ORDERING_QUASI_DEFAULT;
const int n = 10;
const double lambda = 10.0;
const unsigned long long offset = 0ULL;
const unsigned int num_dimensions = 1;
/* Create stream */
CUDA_CHECK(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
/* Allocate n floats on host */
std::vector<data_type> h_data(n, 0);
run_on_host(n, offset, num_dimensions, lambda, order, rng, stream, gen,
h_data);
printf("Host\n");
print_vector(h_data);
printf("=====\n");
run_on_device(n, offset, num_dimensions, lambda, order, rng, stream, gen,
h_data);
printf("Device\n");
print_vector(h_data);
printf("=====\n");
/* Cleanup */
CUDA_CHECK(cudaStreamDestroy(stream));
CUDA_CHECK(cudaDeviceReset());
return EXIT_SUCCESS;
}