Small question about function call

Hi, I just got into CUDA 10.2, and I am learning the example (0_simple\VectorAdd), now I just type “printf” to see what happened, but it seems like the main function never calls this “global void vectorAdd”

I am using VIsual Studio 2019 to open the .sln file, and it built, but just can not use this printf.

Thank you!

Make sure you have a call to cudaDeviceSynchronize() at the end of your program. The output of printf() is typically buffered, which is also true of CUDA’s device-side printf. cudaDeviceSynchronize() causes the buffer to be flushed, just like one would use fflush(stdout) for the same purpose for host-side printf.

Since you haven’t shown the entire program, there may be other issues with the code that we can’t see.

Thank you njuffa, I am not quite understanding about calling cudaDeviceSynchronize().

The code is as follows

/**

  • Copyright 1993-2015 NVIDIA Corporation. All rights reserved.
  • Please refer to the NVIDIA end user license agreement (EULA) associated
  • with this source code for terms and conditions that govern your use of
  • this software. Any use, reproduction, disclosure, or distribution of
  • this software and related documentation outside the terms of the EULA
  • is strictly prohibited.

*/

/**

  • Vector addition: C = A + B.
  • This sample is a very basic sample that implements element by element
  • vector addition. It is the same as the sample illustrating Chapter 2
  • of the programming guide with some additions like error checking.
    */

#include <stdio.h>

// For the CUDA runtime routines (prefixed with “cuda_”)
#include <cuda_runtime.h>

#include <helper_cuda.h>
/**

  • CUDA Kernel Device code

  • Computes the vector addition of A and B into C. The 3 vectors have the same

  • number of elements numElements.
    */
    global void
    vectorAdd(const float *A, const float *B, float *C, int numElements)
    {
    int i = blockDim.x * blockIdx.x + threadIdx.x;
    printf("%d \n", i);
    if (i < numElements)
    {
    C[i] = A[i] + B[i];

    }
    }

/**

  • Host main routine
    */
    int
    main(void)
    {
    // Error code to check return values for CUDA calls
    cudaError_t err = cudaSuccess;

    // Print the vector length to be used, and compute its size
    int numElements = 50000;
    size_t size = numElements * sizeof(float);
    printf("[Vector addition of %d elements]\n", numElements);

    // Allocate the host input vector A
    float *h_A = (float *)malloc(size);

    // Allocate the host input vector B
    float *h_B = (float *)malloc(size);

    // Allocate the host output vector C
    float *h_C = (float *)malloc(size);

    // Verify that allocations succeeded
    if (h_A == NULL || h_B == NULL || h_C == NULL)
    {
    fprintf(stderr, “Failed to allocate host vectors!\n”);
    exit(EXIT_FAILURE);
    }

    // Initialize the host input vectors
    for (int i = 0; i < numElements; ++i)
    {
    h_A[i] = rand()/(float)RAND_MAX;
    h_B[i] = rand()/(float)RAND_MAX;
    }

    // Allocate the device input vector A
    float *d_A = NULL;
    err = cudaMalloc((void **)&d_A, size);

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to allocate device vector A (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    // Allocate the device input vector B
    float *d_B = NULL;
    err = cudaMalloc((void **)&d_B, size);

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to allocate device vector B (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    // Allocate the device output vector C
    float *d_C = NULL;
    err = cudaMalloc((void **)&d_C, size);

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to allocate device vector C (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    // Copy the host input vectors A and B in host memory to the device input vectors in
    // device memory
    printf(“Copy input data from the host memory to the CUDA device\n”);
    err = cudaMemcpy(d_A, h_A, size, cudaMemcpyHostToDevice);

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to copy vector A from host to device (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    err = cudaMemcpy(d_B, h_B, size, cudaMemcpyHostToDevice);

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to copy vector B from host to device (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    // Launch the Vector Add CUDA Kernel
    int threadsPerBlock = 256;
    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
    printf(“CUDA kernel launch with %d blocks of %d threads\n”, blocksPerGrid, threadsPerBlock);
    vectorAdd<<<blocksPerGrid, threadsPerBlock>>>(d_A, d_B, d_C, numElements);
    err = cudaGetLastError();

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to launch vectorAdd kernel (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    // Copy the device result vector in device memory to the host result vector
    // in host memory.
    printf(“Copy output data from the CUDA device to the host memory\n”);
    err = cudaMemcpy(h_C, d_C, size, cudaMemcpyDeviceToHost);

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to copy vector C from device to host (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    // Verify that the result vector is correct
    for (int i = 0; i < numElements; ++i)
    {
    if (fabs(h_A[i] + h_B[i] - h_C[i]) > 1e-5)
    {
    fprintf(stderr, “Result verification failed at element %d!\n”, i);
    exit(EXIT_FAILURE);
    }
    }

    printf(“Test PASSED\n”);

    // Free device global memory
    err = cudaFree(d_A);

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to free device vector A (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    err = cudaFree(d_B);

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to free device vector B (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    err = cudaFree(d_C);

    if (err != cudaSuccess)
    {
    fprintf(stderr, “Failed to free device vector C (error code %s)!\n”, cudaGetErrorString(err));
    exit(EXIT_FAILURE);
    }

    // Free host memory
    free(h_A);
    free(h_B);
    free(h_C);

    printf(“Done\n”);
    return 0;
    }

Have a look at this section of the Programming Guide:
https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#formatted-output

Thank you rs277, I cannot believe that I restarted my computer, and it is good now.