我已经编写了一段代码来调用gpugem3
中的内核但我得到的结果是一堆负数而不是前缀扫描。我想知道我的内核调用是错还是gpugem3代码有问题?
这是我的代码:
#include <stdio.h>
#include <sys/time.h>
#include <cuda.h>
__global__ void kernel(int *g_odata, int *g_idata, int n, int dim)
{
extern __shared__ int temp[];// allocated on invocation
int thid = threadIdx.x;
int offset = 1;
temp[2*thid] = g_idata[2*thid]; // load input into shared memory
temp[2*thid+1] = g_idata[2*thid+1];
for (int d = n>>1; d > 0; d >>= 1) // build sum in place up the tree
{
__syncthreads();
if (thid < d)
{
int ai = offset*(2*thid+1)-1;
int bi = offset*(2*thid+2)-1;
temp[bi] += g_idata[ai];
}
offset *= 2;
}
if (thid == 0) { temp[n - 1] = 0; } // clear the last element
for (int d = 1; d < n; d *= 2) // traverse down tree & build scan
{
offset >>= 1;
__syncthreads();
if (thid < d)
{
int ai = offset*(2*thid+1)-1;
int bi = offset*(2*thid+2)-1;
int t = temp[ai];
temp[ai] = temp[bi];
temp[bi] += t;
}
}
__syncthreads();
g_odata[2*thid] = temp[2*thid]; // write results to device memory
g_odata[2*thid+1] = temp[2*thid+1];
}
void Initialize(int *h_in,int num_items)
{
int j;
for(j=0;j<num_items;j++)
h_in[j]=j;
printf(" input: ");
printf("\n\n");
}
int main(int argc, char** argv)
{
int num_items = 512;
int* h_in = new int[num_items];
// Initialize problem
Initialize(h_in, num_items);
int *d_in = NULL;
cudaMalloc((void**)&d_in, sizeof(int) * num_items);
if(cudaSuccess!= cudaMemcpy(d_in, h_in, sizeof(int) * num_items, cudaMemcpyHostToDevice)) fprintf(stderr,"could not copy to gpu");
// Allocate device output array
int *d_out = NULL;
cudaMalloc((void**)&d_out, sizeof(int) * (num_items+1));
kernel<<<1,256,num_items*sizeof(int)>>>(d_out, d_in,num_items, 2);
int* h_out= new int[num_items+1];
if( cudaSuccess !=cudaMemcpy(h_out,d_out,sizeof(int)*(num_items+1),cudaMemcpyDeviceToHost))fprintf(stderr,"could not copy back");
int i;
printf(" \n");
for(i=0;i<num_items;i++)
printf(" ,%d ",h_out[i]);
// Cleanup
if (h_in) delete[] h_in;
if (h_out) delete[] h_out;
if (d_in) cudaFree(d_in);
if (d_out) cudaFree(d_out);
printf("\n\n");
return 0;
}
答案 0 :(得分:4)
您似乎在将GPU Gems 3 chapter中的代码转录到内核中时至少出现了1次错误。这一行不正确:
temp[bi] += g_idata[ai];
它应该是:
temp[bi] += temp[ai];
当我对您现在发布的代码进行一次更改时,似乎为我打印出正确的(独占扫描)前缀总和。我还会提到其他一些事情:
即使没有这种改变,我也会得到一些接近正确的结果。因此,如果您获得了大量不同的内容(例如负数),则可能是您的计算机设置或CUDA安装存在问题。我建议使用比你现在更严格的cuda error checking(尽管在你的一张支票中应该显示机器设置问题。)
精心制作的例程会有一些限制。它只能在单个线程块中使用,它在共享内存访问时会产生冲突,并且数据集大小会受限于单个线程块可以处理的内容(此例程每个线程产生两个输出元素,因此数据集大小预计等于线程数的两倍)。如前所述,动态共享内存分配需要与数据集大小一样大(即,线程大小的两倍,元素数量)。
这可能对学习很有用,但如果你想要一个健壮,快速的前缀扫描,建议你使用thrust或cub的例程而不是你自己的代码,甚至如果来自这篇(旧)文章。
以下代码与您的代码类似,但它修复了上述问题,并且我已经将内核模板化以用于各种数据类型:
#include <stdio.h>
#define DSIZE 512
#define cudaCheckErrors(msg) \
do { \
cudaError_t __err = cudaGetLastError(); \
if (__err != cudaSuccess) { \
fprintf(stderr, "Fatal error: %s (%s at %s:%d)\n", \
msg, cudaGetErrorString(__err), \
__FILE__, __LINE__); \
fprintf(stderr, "*** FAILED - ABORTING\n"); \
exit(1); \
} \
} while (0)
typedef int mytype;
template <typename T>
__global__ void prescan(T *g_odata, T *g_idata, int n)
{
extern __shared__ T temp[]; // allocated on invocation
int thid = threadIdx.x;
int offset = 1;
temp[2*thid] = g_idata[2*thid]; // load input into shared memory
temp[2*thid+1] = g_idata[2*thid+1];
for (int d = n>>1; d > 0; d >>= 1) // build sum in place up the tree
{
__syncthreads();
if (thid < d)
{
int ai = offset*(2*thid+1)-1;
int bi = offset*(2*thid+2)-1;
temp[bi] += temp[ai];
}
offset *= 2;
}
if (thid == 0) { temp[n - 1] = 0; } // clear the last element
for (int d = 1; d < n; d *= 2) // traverse down tree & build scan
{
offset >>= 1;
__syncthreads();
if (thid < d)
{
int ai = offset*(2*thid+1)-1;
int bi = offset*(2*thid+2)-1;
T t = temp[ai];
temp[ai] = temp[bi];
temp[bi] += t;
}
}
__syncthreads();
g_odata[2*thid] = temp[2*thid]; // write results to device memory
g_odata[2*thid+1] = temp[2*thid+1];
}
int main(){
mytype *h_i, *d_i, *h_o, *d_o;
int dszp = (DSIZE)*sizeof(mytype);
h_i = (mytype *)malloc(dszp);
h_o = (mytype *)malloc(dszp);
if ((h_i == NULL) || (h_o == NULL)) {printf("malloc fail\n"); return 1;}
cudaMalloc(&d_i, dszp);
cudaMalloc(&d_o, dszp);
cudaCheckErrors("cudaMalloc fail");
for (int i = 0 ; i < DSIZE; i++){
h_i[i] = i;
h_o[i] = 0;}
cudaMemset(d_o, 0, dszp);
cudaCheckErrors("cudaMemset fail");
cudaMemcpy(d_i, h_i, dszp, cudaMemcpyHostToDevice);
cudaCheckErrors("cudaMemcpy 1 fail");
prescan<<<1,DSIZE/2, dszp>>>(d_o, d_i, DSIZE);
cudaDeviceSynchronize();
cudaCheckErrors("kernel fail");
cudaMemcpy(h_o, d_o, dszp, cudaMemcpyDeviceToHost);
cudaCheckErrors("cudaMemcpy 2 fail");
mytype psum = 0;
for (int i =1; i < DSIZE; i++){
psum += h_i[i-1];
if (psum != h_o[i]) {printf("mismatch at %d, was: %d, should be: %d\n", i, h_o[i], psum); return 1;}
}
return 0;
}