Valgrind and CUDA: Are reported leaks real?

问题:

I have a very simple CUDA component in my application. Valgrind reports a lot of leaks and still-reachables, all related to the cudaMalloc calls.

Are these leaks real? I call cudaFree for every cudaMalloc. Is this valgrind's inability to interpret GPU memory allocation? If these leaks are not real, can I suppress them and have valgrind only analyse the non-gpu part of the application?

extern "C"
unsigned int *gethash(int nodec, char *h_nodev, int len) {
    unsigned int *h_out = (unsigned int *)malloc(sizeof(unsigned int) * nodec);

    char *d_in;
    unsigned int *d_out;

    cudaMalloc((void**) &d_in, sizeof(char) * len * nodec);
    cudaMalloc((void**) &d_out, sizeof(unsigned int) * nodec);

    cudaMemcpy(d_in, h_nodev, sizeof(char) * len * nodec, cudaMemcpyHostToDevice);

    int blocks = 1 + nodec / 512;


    cube<<<blocks, 512>>>(d_out, d_in, nodec, len);

    cudaMemcpy(h_out, d_out, sizeof(unsigned int) * nodec, cudaMemcpyDeviceToHost);

    cudaFree(d_in);
    cudaFree(d_out);
    return h_out;

}

Last bit of the Valgrind output:

...
==5727== 5,468 (5,020 direct, 448 indirect) bytes in 1 blocks are definitely lost in loss record 506 of 523
==5727==    at 0x402B965: calloc (in /usr/lib/valgrind/vgpreload_memcheck-x86-linux.so)
==5727==    by 0x4843910: ??? (in /usr/lib/nvidia-319-updates/libcuda.so.319.60)
==5727==    by 0x48403E9: ??? (in /usr/lib/nvidia-319-updates/libcuda.so.319.60)
==5727==    by 0x498B32D: ??? (in /usr/lib/nvidia-319-updates/libcuda.so.319.60)
==5727==    by 0x494A6E4: ??? (in /usr/lib/nvidia-319-updates/libcuda.so.319.60)
==5727==    by 0x4849534: ??? (in /usr/lib/nvidia-319-updates/libcuda.so.319.60)
==5727==    by 0x48191DD: cuInit (in /usr/lib/nvidia-319-updates/libcuda.so.319.60)
==5727==    by 0x406B4D6: ??? (in /usr/lib/i386-linux-gnu/libcudart.so.5.0.35)
==5727==    by 0x406B61F: ??? (in /usr/lib/i386-linux-gnu/libcudart.so.5.0.35)
==5727==    by 0x408695D: cudaMalloc (in /usr/lib/i386-linux-gnu/libcudart.so.5.0.35)
==5727==    by 0x804A006: gethash (hashkernel.cu:36)
==5727==    by 0x804905F: chkisomorphs (bdd.c:326)
==5727== 
==5727== LEAK SUMMARY:
==5727==    definitely lost: 10,240 bytes in 6 blocks
==5727==    indirectly lost: 1,505 bytes in 54 blocks
==5727==      possibly lost: 7,972 bytes in 104 blocks
==5727==    still reachable: 626,997 bytes in 1,201 blocks
==5727==         suppressed: 0 bytes in 0 blocks

回答1:

It's a known issue that valgrind reports false-positives for a bunch of CUDA stuff. The best way to avoid seeing it would be to use valgrind suppressions, which you can read all about here: http://valgrind.org/docs/manual/manual-core.html#manual-core.suppress

If you want to jumpstart into something a little closer to your specific issue, an interesting post is this one on the Nvidia dev forums. It has a link to a sample suppression rule file. https://devtalk.nvidia.com/default/topic/404607/valgrind-3-4-suppressions-a-little-howto/

回答2:

To add to scarl3tt's answer, this may be overly general for some applications, but if you want to use valgrind while ignoring most of the cuda issues, use the option --suppressions=valgrind-cuda.supp where valgrind-cuda.supp is a file with the following rules:

{
   alloc_libcuda
   Memcheck:Leak
   match-leak-kinds: reachable,possible
   fun:*alloc
   ...
   obj:*libcuda.so*
   ...
}

{
   alloc_libcufft
   Memcheck:Leak
   match-leak-kinds: reachable,possible
   fun:*alloc
   ...
   obj:*libcufft.so*
   ...
}

{
   alloc_libcudaart
   Memcheck:Leak
   match-leak-kinds: reachable,possible
   fun:*alloc
   ...
   obj:*libcudart.so*
   ...
}

回答3:

Try using cuda-memcheck --leak-check full. Cuda-memcheck is a set of tools that provides similar functionality to Valgrind for CUDA applications. It is installed as part of the CUDA toolkit. You can get more documentation about how to use cuda-memcheck here : http://docs.nvidia.com/cuda/cuda-memcheck/

Note that cuda-memcheck is not a direct replacement for valgrind and can't be used to detect host side memory leaks or buffer overflows.

回答4:

I wouldn't trust valgrind or any other leak detector (like VLD) with CUDA. I'm sure they weren't designed with GPU allocations in mind. I don't know whether Nvidia's Nsight has the capability these days (I haven't done GPU programming for almost 6 months now), but that's the best thing I used for CUDA debugging, and to be quite honest, it was buggy as hell.

The code you've posted shouldn't create a leak.

回答5:

Since I don't have 50 reputation, I cannot leave a comment on @Vyas 's answer.

I feel strange that cuda-memcheck cannot observe cuda memory leakage.

I just write a very simple code with a cuda memory leakage, but when using cuda-memcheck --leak-check full it give no leakage. It is:

#include <iostream>
#include <cuda_runtime.h>

using namespace std;

int main(){
    float* cpu_data;
    float* gpu_data;
    int buf_size = 10 * sizeof(float);

    cpu_data = (float*)malloc(buf_size);
    for(int i=0; i<10; i++){
        cpu_data[i] = 1.0f * i;
    }

    cudaError_t cudaStatus = cudaMalloc(&gpu_data, buf_size);

    cudaMemcpy(gpu_data, cpu_data, buf_size, cudaMemcpyHostToDevice);

    free(cpu_data);
    //cudaFree(gpu_data);

    return 0;
}

Note the commented line of code, which make this program a cuda memory leakage, I think. However, when execuing cuda-memcheck ./a.out it gives:

========= CUDA-MEMCHECK
========= ERROR SUMMARY: 0 errors