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curand_sobol32_lognormal_example.cpp
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curand_sobol32_lognormal_example.cpp
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/*
* 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 = float;
void run_on_device(const int &n, const data_type &mean, const data_type &stddev,
const unsigned long long &offset,
const unsigned int &num_dimensions,
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_SOBOL32));
/* 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(
curandGenerateLogNormal(gen, d_data, h_data.size(), mean, stddev));
/* 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));
}
void run_on_host(const int &n, const data_type &mean, const data_type &stddev,
const unsigned long long &offset,
const unsigned int &num_dimensions,
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_SOBOL32));
/* 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 host */
CURAND_CHECK(
curandGenerateLogNormal(gen, h_data.data(), h_data.size(), mean, stddev));
/* 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_SOBOL32;
curandOrdering_t order = CURAND_ORDERING_QUASI_DEFAULT;
const int n = 12;
const unsigned long long offset = 0ULL;
const unsigned int num_dimensions = 1;
const data_type mean = 1.0f;
const data_type stddev = 2.0f;
/* Create stream */
CUDA_CHECK(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
/* Allocate n floats on host */
std::vector<data_type> h_data(n, 0);
run_on_host(n, mean, stddev, offset, num_dimensions, order, rng, stream, gen,
h_data);
printf("Host\n");
print_vector(h_data);
printf("=====\n");
run_on_device(n, mean, stddev, offset, num_dimensions, 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;
}