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#include <iostream>
#include <unistd.h>
#include <sys/mman.h>
#include <string>
#include <omp.h>
#include <cuda.h>
#include <cuda_runtime.h>
#define UVM
#ifndef NDEBUG
#define cudaCheck(x) x
#else
#include <cstdio>
#define cudaCheck(x) _cudaCheck(x, #x ,__FILE__, __LINE__)
#endif
template<typename T>
void _cudaCheck(T e, const char *func, const char *call, const int line) {
if (e != cudaSuccess) {
printf("\"%s\" at %d in %s\n\treturned %d\n-> %s\n", func, line, call, (int) e, cudaGetErrorString(e));
exit(EXIT_FAILURE);
}
}
#define GIG (1024ul*1024*1024)
#define VOLUME (2ul*GIG)
// Real values is in the ~65536, only use half of it to be safe
// sysctl vm.max_map_count
#define MAXMMAPS 32768
__global__ void
cudacpy(long *src, long *dst, long len) {
long st = len / gridDim.x;
long ed = min(st * (blockIdx.x + 1), len);
st = st * blockIdx.x;
st += threadIdx.x;
for (; st < ed; st += blockDim.x)
dst[st] = src[st];
}
int main(int argc, char **argv) {
auto page_size = sysconf(_SC_PAGESIZE);
std::cout << "The system have a page size of " << page_size << std::endl;
// Src is using anonymous mapping
long nmaps = 1024;
if (argc > 1) {
nmaps = std::stoi(argv[1]);
if (VOLUME / page_size % nmaps != 0) {
std::cout << "nmaps is not perfect multiple, quit" << std::endl;
return 0;
}
}
long mmap_sz = VOLUME / nmaps;
std::cout << "Each mapped region is of size(pages) " << mmap_sz / page_size << std::endl;
auto dst = (long *) malloc(VOLUME);
uint8_t *hint = (uint8_t *) 0x600000000000UL;
hint -= VOLUME;
auto src = (long *) hint;
for (long i = 0; i < nmaps; ++i) {
auto r = mmap(hint, mmap_sz, PROT_READ | PROT_WRITE, MAP_ANON | MAP_PRIVATE, -1, 0);
if (r == MAP_FAILED || r != hint)
printf("MMAP failed somehow\n");
hint += mmap_sz;
}
#pragma omp parallel for
for (long i = 0; i < VOLUME / sizeof(long); ++i) {
src[i] = i;
dst[i] = 0;
}
auto hostcpy = [&](long *src, long *dst) -> void {
#pragma omp parallel for
for (long i = 0; i < VOLUME / sizeof(long); ++i)
dst[i] = src[i];
};
auto hostbench = [&](int ITER, long *src, long *dst, std::string desc) -> void {
double st = omp_get_wtime();
hostcpy(src, dst);
for (int t = 0; t < ITER; ++t)
hostcpy(src, dst);
st = (omp_get_wtime() - st) / ITER;
printf("%s (host)\nAverage time(s) %f\n", desc.c_str(), st);
printf("Average throughput(GB/s) %f\n\n", VOLUME * 2 / st * 1e-9);
};
auto devcpy = [&](long *src, long *dst) -> void {
cudacpy << < 1024, 256 >> > (src, dst, VOLUME / sizeof(float));
};
auto devbench = [&](int ITER, long *src, long *dst, std::string desc) -> void {
float elapsed;
cudaEvent_t c_0, c_1;
cudaEventCreate(&c_0);
cudaEventCreate(&c_1);
devcpy(src, dst);
cudaEventRecord(c_0);
for (int t = 0; t < ITER; ++t)
devcpy(src, dst);
cudaEventRecord(c_1);
cudaEventSynchronize(c_1);
cudaEventElapsedTime(&elapsed, c_0, c_1);
double st = elapsed / 1000 / ITER;
printf("%s (device)\nAverage time(s) %f\n", desc.c_str(), st);
printf("Average throughput(GB/s) %f\n\n", VOLUME * 2 / st * 1e-9);
cudaEventDestroy(c_0);
cudaEventDestroy(c_1);
};
hostbench(100, src, dst, "CPU -> CPU");
#ifdef UVM
CUdevice device = 0;
CUcontext pctx;
cudaCheck((cudaError_t) cudaSetDevice(device));
cudaCheck((cudaError_t) cuCtxCreate(&pctx, CU_CTX_SCHED_AUTO | CU_CTX_MAP_HOST, device));
cudaCheck(cudaMemAdvise(dst, VOLUME, cudaMemAdviseSetPreferredLocation, device));
cudaMemPrefetchAsync(dst, VOLUME, device);
cudaCheck(cudaMemAdvise(dst, VOLUME, cudaMemAdviseSetPreferredLocation, cudaCpuDeviceId));
cudaMemPrefetchAsync(dst, VOLUME, cudaCpuDeviceId);
devbench(300, src, dst, "GPU -> CPU");
hostbench(100, src, dst, "GPU -> CPU");
devbench(300, dst, src, "CPU -> GPU");
hostbench(100, dst, src, "CPU -> GPU");
cudaCheck(cudaMemAdvise(src, VOLUME, cudaMemAdviseSetPreferredLocation, device));
cudaMemPrefetchAsync(src, VOLUME, device);
devbench(1000, src, dst, "GPU -> GPU");
hostbench(100, src, dst, "GPU -> GPU");
#endif
return 0;
}
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