CUDA - Why isn't my device data being transferred to the host? - arrays

Question

I am currently having exceptional difficulty with CUDA programming--more specifically, in copying and reading an array which the device sends back to the host. When I attempt to read the data which I am supposed to have returned to me, all I get is junk data. Could anyone take a look at my code snippets and tell me what I'm doing wrong? Thank you very much!
struct intss {
u_int32_t one;
u_int32_t two;
};
int main()
{
int block_size = 3;
int grid_size = 1;
intss *device_fb = 0;
intss *host_fb = 0;
int num_bytes_fb = (block_size*grid_size)*sizeof(intss);
host_fb = (intss*)malloc(num_bytes_fb);
cudaMalloc((void **)&device_fb, num_bytes_fb);
....
render2<<<block_size,grid_size>>>(device_fb, device_pixelspercore, samples, obj_list_flat_dev, numOpsPerCore, lnumdev, camdev, lightsdev, uranddev, iranddev);
....
cudaMemcpy(host_fb, device_fb, num_bytes_fb, cudaMemcpyDeviceToHost);
printf("output %d ", host_fb[0].one);
printf("output %d ", host_fb[1].one);
printf("output %d ", host_fb[2].one);
//Note that I'm only looking at elements the 3 elements 0-2 from host_fb. I am doing this because block_size*grid_size = 3. Is this wrong?
cudaFree(device_fb);
free(host_fb);
}
__global__ void render2(intss *device_fb, struct parallelPixels *pixelsPerCore, int samples, double *obj_list_flat_dev, int numOpsPerCore, int lnumdev, struct camera camdev, struct vec3 *lightsdev, struct vec3 *uranddev, int *iranddev) //SPECIFY ARGUMENTS!!!
{
int index = blockIdx.x * blockDim.x + threadIdx.x; //DETERMINING INDEX BASED ON WHICH THREAD IS CURRENTLY RUNNING
....
//computing data...
device_fb[index].one = (((u_int32_t)(MIN(r, 1.0) * 255.0) & 0xff) << RSHIFT |
((u_int32_t)(MIN(g, 1.0) * 255.0) & 0xff) << GSHIFT |
((u_int32_t)(MIN(b, 1.0) * 255.0) & 0xff) << BSHIFT);
}
EDIT:
Thanks to a suggestion, I have implemented the CudaErrorCheck function in my program, and there seems to be a pattern in which functions are giving me errors.
In my program, I have a bunch of global host arrays(obj_list, lights, urand, irand). Whenever I attempt to use cudaMemCpy to copy these host arrays to device arrays, I receive the following error:
"Cuda error in file 'cudatrace.cu' in line x : invalid argument."
obj_list and lights are filled in the following function, load_scene():
void load_scene(FILE *fp) {
char line[256], *ptr, type;
obj_list = (sphere *)malloc(sizeof(struct sphere));
obj_list->next = 0;
objCounter = 0;
while((ptr = fgets(line, 256, fp))) {
int i;
struct vec3 pos, col;
double rad, spow, refl;
while(*ptr == ' ' || *ptr == '\t') ptr++;
if(*ptr == '#' || *ptr == '\n') continue;
if(!(ptr = strtok(line, DELIM))) continue;
type = *ptr;
for(i=0; i<3; i++) {
if(!(ptr = strtok(0, DELIM))) break;
*((double*)&pos.x + i) = atof(ptr);
}
if(type == 'l') {
lights[lnum++] = pos;
continue;
}
if(!(ptr = strtok(0, DELIM))) continue;
rad = atof(ptr);
for(i=0; i<3; i++) {
if(!(ptr = strtok(0, DELIM))) break;
*((double*)&col.x + i) = atof(ptr);
}
if(type == 'c') {
cam.pos = pos;
cam.targ = col;
cam.fov = rad;
continue;
}
if(!(ptr = strtok(0, DELIM))) continue;
spow = atof(ptr);
if(!(ptr = strtok(0, DELIM))) continue;
refl = atof(ptr);
if(type == 's') {
objCounter++;
struct sphere *sph = (sphere *)malloc(sizeof(*sph));
sph->next = obj_list->next;
obj_list->next = sph;
sph->pos = pos;
sph->rad = rad;
sph->mat.col = col;
sph->mat.spow = spow;
sph->mat.refl = refl;
} else {
fprintf(stderr, "unknown type: %c\n", type);
}
}
}
urand and irand are filled in main as follows:
/* initialize the random number tables for the jitter */
for(i=0; i<NRAN; i++) urand[i].x = (double)rand() / RAND_MAX - 0.5;
for(i=0; i<NRAN; i++) urand[i].y = (double)rand() / RAND_MAX - 0.5;
for(i=0; i<NRAN; i++) irand[i] = (int)(NRAN * ((double)rand() / RAND_MAX));
I don't think the invalid argument could be caused by the device array, since the cudaMalloc call creating the device array before the cudaMemcpy call did not have a CudaError message. For example, in the following lines of code:
cudaErrorCheck(cudaMalloc((void **)&lightsdev, MAX_LIGHTS*sizeof(struct vec3)) );
cudaErrorCheck( cudaMemcpy(&lightsdev, &lights, sizeof(struct vec3) * MAX_LIGHTS, cudaMemcpyHostToDevice) );
cudaMalloc did not produce an error, but cudaMemcpy did.
If I have not provided enough information on my code, I have pasted the entire code to: http://pastebin.com/UgzABPgH
(Note that in the pastebin version, I took out the CudaErrorCheck functions on the CudaMemcpy's which were producing the errors.)
Thank you very much!
EDIT:
Actually, I just tried to see what would happen if urand and irand were not global, and if they were initialized alongside the device arrays uranddev and iranddev. I'm still getting the same "invalid argument" error, so the whether or not a variable is global must not relate to the problem.

Answer 1

It is absolutely impossible to say anything when you have posted incomplete, uncompilable code with no proper description of the actual problem. You will get better answers by asking better questions on StackOverflow.
Having said that. the most likely problem isn't that the data is not being copied to or from the device, it is that the kernel itself is not running. Every CUDA runtime API call returns a status code, and you should be checking all of them. You can define an error checking macro like this one:
#include <stdio.h>
#define cudaErrorCheck(call) { cudaAssert(call,__FILE__,__LINE__) }
void cudaAssert(const cudaError err, const char *file, const int line)
{
if( cudaSuccess != err) {
fprintf(stderr, "Cuda error in file '%s' in line %i : %s.\n",
file, line, cudaGetErrorString(err) );
exit(1);
}
}
and wrap every API call in it, like this:
cudaErrorCheck( cudaMemcpy(host_fb, device_fb, num_bytes_fb, cudaMemcpyDeviceToHost) );
For the kernel launch, itself you can check for a launch failure or runtime error like this:
kernel<<<....>>>();
cudaErrorCheck( cudaPeekAtLastError() ); // Checks for launch error
cudaErrorCheck( cudaThreadSynchronize() ); // Checks for execution error
My suggestion is add thorough error checking to your code and then come back and edit your question with the results you get. Then someone might be able to offer concrete suggestions about what is happening.

Answer 2

I think you're not using the <<< >>> syntax correctly.
Here's a kernel invocation from the CUDA Programming Guide:
MatAdd<<<numBlocks, threadsPerBlock>>>(A, B, C);
which would mean that the grid size should go first.
There's also a limitation on the maximum size for the arguments to a kernel. See this. If you go above it, I'm not sure whether the compiler complains or just goes on to do nasty things.
If I remove all the arguments but device_fb, and just set device_fb[index]=index in the kernel, I can read the values successfully.