Multiply Rectangular Matrices in CUDA

After the help of Ira, Ahmad, ram, and Oli Fly, I got the correct answer as follows:

#include    <wb.h>

#define wbCheck(stmt) do {                                 \
        cudaError_t err = stmt;                            \
        if (err != cudaSuccess) {                          \
            wbLog(ERROR, "Failed to run stmt ", #stmt);    \
            return -1;                                     \
        }                                                  \
    } while(0)

// Compute C = A * B
__global__ void matrixMultiply(float * A, float * B, float * C,
                   int numARows, int numAColumns,
                   int numBRows, int numBColumns,
                   int numCRows, int numCColumns) {
    //@@ Insert code to implement matrix multiplication here
    int Row = blockIdx.y * blockDim.y + threadIdx.y;
    int Col = blockIdx.x * blockDim.x + threadIdx.x;
    if (numAColumns != numBRows) return;
    if ((Row < numARows) && (Col < numBColumns)){
    float Cvalue = 0;
    for (int k = 0; k < numAColumns; ++k)
    Cvalue += A[Row*numAColumns + k] * B[k * numBColumns + Col];
    C[Row*numCColumns + Col] = Cvalue;
  }

}

int main(int argc, char ** argv) {
    wbArg_t args;
    float * hostA; // The A matrix
    float * hostB; // The B matrix
    float * hostC; // The output C matrix
    float * deviceA;
    float * deviceB;
    float * deviceC;
    int numARows; // number of rows in the matrix A
    int numAColumns; // number of columns in the matrix A
    int numBRows; // number of rows in the matrix B
    int numBColumns; // number of columns in the matrix B
    int numCRows; // number of rows in the matrix C (you have to set this)
    int numCColumns; // number of columns in the matrix C (you have to set this)

    args = wbArg_read(argc, argv);

    wbTime_start(Generic, "Importing data and creating memory on host");
    hostA = (float *) wbImport(wbArg_getInputFile(args, 0), &numARows, &numAColumns);
    hostB = (float *) wbImport(wbArg_getInputFile(args, 1), &numBRows, &numBColumns);
    //@@ Set numCRows and numCColumns  
    numCRows = 0;
    numCColumns = 0;
    numCRows = numARows;
    numCColumns = numBColumns;  
    //@@ Allocate the hostC matrix
    hostC = (float*) malloc(sizeof(float)*numCRows*numCColumns);  
    wbTime_stop(Generic, "Importing data and creating memory on host");

    wbLog(TRACE, "The dimensions of A are ", numARows, " x ", numAColumns);
    wbLog(TRACE, "The dimensions of B are ", numBRows, " x ", numBColumns);

    wbTime_start(GPU, "Allocating GPU memory.");
    //@@ Allocate GPU memory here
    cudaMalloc((void**)&deviceA ,sizeof(float)*numARows*numAColumns );
    cudaMalloc((void**)&deviceB , sizeof(float)*numBRows*numBColumns);
    cudaMalloc((void**)&deviceC , sizeof(float)*numCRows*numCColumns);  

    wbTime_stop(GPU, "Allocating GPU memory.");

    wbTime_start(GPU, "Copying input memory to the GPU.");
    //@@ Copy memory to the GPU here

    cudaMemcpy(deviceA, hostA, sizeof(float)*numARows*numAColumns, cudaMemcpyHostToDevice);
    cudaMemcpy(deviceB, hostB, sizeof(float)*numBRows*numBColumns, cudaMemcpyHostToDevice);
    wbTime_stop(GPU, "Copying input memory to the GPU.");

    //@@ Initialize the grid and block dimensions here

    dim3 DimGrid((numCColumns - 1) / 8 + 1, (numCRows - 1) / 8 + 1, 1);
    dim3 DimBlock(8 , 8, 1);

    wbTime_start(Compute, "Performing CUDA computation");

    //@@ Launch the GPU Kernel here
    matrixMultiply<<<DimGrid , DimBlock>>>(deviceA , deviceB , deviceC , numARows , numAColumns, numBRows ,numBColumns , numCRows , numCColumns);  

    cudaThreadSynchronize();
    wbTime_stop(Compute, "Performing CUDA computation");

    wbTime_start(Copy, "Copying output memory to the CPU");
    //@@ Copy the GPU memory back to the CPU here
    cudaMemcpy(hostC, deviceC, sizeof(float)*numCRows*numCColumns , cudaMemcpyDeviceToHost);  

    wbTime_stop(Copy, "Copying output memory to the CPU");

    wbTime_start(GPU, "Freeing GPU Memory");
    //@@ Free the GPU memory here

    cudaFree(deviceA);
    cudaFree(deviceB);
    cudaFree(deviceC);
    wbTime_stop(GPU, "Freeing GPU Memory");

    wbSolution(args, hostC, numCRows, numCColumns);

    free(hostA);
    free(hostB);
    free(hostC);

    return 0;
}