Question

I’ve prepared a .pro file for use Qt and CUDA in a linux machine (64bits). When I run the application into the CUDA profiler, the app executes 12 times but before present the results i get the next error:

Error in profiler data file ‘/home/myusername/development/qtspace/bin/temp_compute_profiler_0_0.csv’ at line number 6 for column ‘memory transfer size.

The main.cpp file is as simple as

#include <QtCore/QCoreApplication> 
extern "C"
void runCudaPart();

int main(int argc, char *argv[])
{
    QCoreApplication a(argc, argv);
    runCudaPart();
    return 0;
}

The fact is that if i remove the “QCoreApplication a(argc, argv);” line the CUDA Visual Profiler works as excepted and show all the results.

I’ve checked that the cuda_profile.log is generated from the command line if i export the CUDA_PROFILE=1 environment variable. The comma-separated file is also generated if i export the COMPUTE_PROFILE_CSV=1 variale but the CUDA Visual Profiler crashes when i try to import that file.

Any hints about this issue? It seems something related to the CUDA visual Profiler application not with the code.

If you are wondering why i did a so simple main.cpp with Qt but without using Qt 😛 is that i would like improve the framework in the future to add a GUI.

// details of CUDA, GPU, OS, QT, and compiler versions

  Device"GeForce GTX 480"
  CUDA Driver Version:                           3.20
  CUDA Runtime Version:                          3.20
  CUDA Capability Major/Minor version number:    2.0
  OS: ubuntu 10.04 LTS
  QT_VERSION: 263682
  QT_VERSION_STR: 4.6.2
  gcc version 4.4.3
  nvcc compilation tool, release 3.2, V0.2.122

I’ve noticed that the problem is with the QCoreApplication construct. It does something with the arguments. If I modify the line as:

QCoreApplication a();

the Visual Profiler works as excepted. Hard to know what is happening and if this change will be a problem in the future. Any hints?

Regarding to the QCoreApplication construct the example also work if I call the cuda part before the QCoreApplication.

// this way the example works.
runCudaPart();
QCoreApplication a(argc, argv);

Thanks in advance.

Answer 1

I can’t reproduce this with CUDA 3.2 and QT4 on a 64 bit Ubuntu 10.04LTS system. I took this main:

#include <QtCore/QCoreApplication>

extern float cudamain();

int main(int argc, char *argv[])
{
    QCoreApplication a(argc, argv);

    float gflops = cudamain();

    return 0;
}

and a cudamain() containing this:

#include <assert.h>

#define blocksize 16
#define HM (4096) 
#define WM (4096) 
#define WN (4096)
#define HN WM 
#define WP WN   
#define HP HM  
#define PTH WM
#define PTW HM

__global__ void nonsquare(float*M, float*N, float*P, int uWM,int uWN)
{
    __shared__ float MS[blocksize][blocksize];
    __shared__ float NS[blocksize][blocksize];

    int tx=threadIdx.x, ty=threadIdx.y, bx=blockIdx.x, by=blockIdx.y;
    int rowM=ty+by*blocksize;
    int colN=tx+bx*blocksize;
    float Pvalue=0;

    for(int m=0; m<uWM; m+=blocksize){
        MS[ty][tx]=M[rowM*uWM+(m+tx)] ;
        NS[ty][tx]=M[colN + uWN*(m+ty)];
        __syncthreads();
        for(int k=0;k<blocksize;k++)
            Pvalue+=MS[ty][k]*NS[k][tx];
        __syncthreads();
    }
    P[rowM*WP+colN]=Pvalue;
}

inline void gpuerrorchk(cudaError_t state)
{
    assert(state == cudaSuccess);
}

float cudamain(){

    cudaEvent_t evstart, evstop;
    cudaEventCreate(&evstart);
    cudaEventCreate(&evstop);

    float*M=(float*)malloc(sizeof(float)*HM*WM);
    float*N=(float*)malloc(sizeof(float)*HN*WN);

    for(int i=0;i<WM*HM;i++)
        M[i]=(float)i;
    for(int i=0;i<WN*HN;i++)
        N[i]=(float)i;

    float*P=(float*)malloc(sizeof(float)*HP*WP);

    float *Md,*Nd,*Pd;
    gpuerrorchk( cudaMalloc((void**)&Md,HM*WM*sizeof(float)) );
    gpuerrorchk( cudaMalloc((void**)&Nd,HN*WN*sizeof(float)) );
    gpuerrorchk( cudaMalloc((void**)&Pd,HP*WP*sizeof(float)) );

    gpuerrorchk( cudaMemcpy(Md,M,HM*WM*sizeof(float),cudaMemcpyHostToDevice) );
    gpuerrorchk( cudaMemcpy(Nd,N,HN*WN*sizeof(float),cudaMemcpyHostToDevice) );

    dim3 dimBlock(blocksize,blocksize);//(tile_width , tile_width);
    dim3 dimGrid(WN/dimBlock.x,HM/dimBlock.y);//(width/tile_width , width/tile_witdh);

    gpuerrorchk( cudaEventRecord(evstart,0) );

    nonsquare<<<dimGrid,dimBlock>>>(Md,Nd,Pd,WM, WN);
    gpuerrorchk( cudaPeekAtLastError() );

    gpuerrorchk( cudaEventRecord(evstop,0) );
    gpuerrorchk( cudaEventSynchronize(evstop) );
    float time;
    cudaEventElapsedTime(&time,evstart,evstop);

    gpuerrorchk( cudaMemcpy(P,Pd,WP*HP*sizeof(float),cudaMemcpyDeviceToHost) );

    cudaFree(Md);
    cudaFree(Nd);
    cudaFree(Pd);

    float gflops=(2.e-6*WM*WM*WM)/(time);

    cudaThreadExit();

    return gflops;

}

(pay no attention to the actual code other than it doing memory transactions and running a kernel, it is nonsense otherwise).

Compiling the code like this:

cuda:~$ nvcc -arch=sm_20 -c -o cudamain.o cudamain.cu 
cuda:~$ g++ -o qtprob -I/usr/include/qt4 qtprob.cc cudamain.o -L $CUDA_INSTALL_PATH/lib64 -lQtCore -lcuda -lcudart
cuda:~$ ldd qtprob
        linux-vdso.so.1 =>  (0x00007fff242c8000)
        libQtCore.so.4 => /opt/cuda-3.2/computeprof/bin/libQtCore.so.4 (0x00007fbe62344000)
        libcuda.so.1 => /usr/lib/libcuda.so.1 (0x00007fbe61a3d000)
        libcudart.so.3 => /opt/cuda-3.2/lib64/libcudart.so.3 (0x00007fbe617ef000)
        libstdc++.so.6 => /usr/lib/libstdc++.so.6 (0x00007fbe614db000)
        libm.so.6 => /lib/libm.so.6 (0x00007fbe61258000)
        libgcc_s.so.1 => /lib/libgcc_s.so.1 (0x00007fbe61040000)
        libc.so.6 => /lib/libc.so.6 (0x00007fbe60cbd000)
        libz.so.1 => /lib/libz.so.1 (0x00007fbe60aa6000)
        libgthread-2.0.so.0 => /usr/lib/libgthread-2.0.so.0 (0x00007fbe608a0000)
        libglib-2.0.so.0 => /lib/libglib-2.0.so.0 (0x00007fbe605c2000)
        librt.so.1 => /lib/librt.so.1 (0x00007fbe603ba000)
        libpthread.so.0 => /lib/libpthread.so.0 (0x00007fbe6019c000)
        libdl.so.2 => /lib/libdl.so.2 (0x00007fbe5ff98000)
        /lib64/ld-linux-x86-64.so.2 (0x00007fbe626c0000)
        libpcre.so.3 => /lib/libpcre.so.3 (0x00007fbe5fd69000)

produces an executable which profiles without error as many times as I care to run it with the CUDA 3.2 release profiler.

All I can suggest is try my repro case and see whether it works or not. If it fails, then perhaps you have either a broken CUDA or QT installation. If it doesn’t fail (and I suspect it won’t), then you either have a problem with the way you are building the QT project or the actual CUDA code you are running itself.