Display GPU Memory Value when Debugging with CUDA-GDB in VSCode

Debugging GPU code can be a challenging task, especially for those who are new to GPU programming. CUDA-GDB is a powerful tool that can help you debug your CUDA applications. In this article, we will show you how to display the GPU memory value when debugging with CUDA-GDB in VSCode.

Prerequisites

Before we begin, you need to make sure that you have the following prerequisites:

• A CUDA-enabled GPU
• CUDA Toolkit installed
• VSCode installed
• CUDA extension for VSCode installed

Setting up CUDA-GDB in VSCode

To set up CUDA-GDB in VSCode, you need to follow these steps:

1. Open VSCode and create a new CUDA file.
2. Open the integrated terminal by clicking on the "View" menu and selecting "Terminal".
3. Type "nvcc --version" to check if the CUDA compiler is installed correctly.
4. Type "which cuda-gdb" to locate the CUDA-GDB executable.
5. Type "cuda-gdb --version" to check if the CUDA-GDB is installed correctly.
6. Add the following lines to your CUDA file:

   #include <stdio.h>
   
   __global__ void add(int *a, int *b, int *c) {
     int index = threadIdx.x + blockIdx.x \* blockDim.x;
     c[index] = a[index] + b[index];
   }
   
   int main(void) {
     int *a, *b, *c;
     int size = 256;
     a = (int *)malloc(size \* sizeof(int));
     b = (int *)malloc(size \* sizeof(int));
     c = (int *)malloc(size \* sizeof(int));
     for (int i = 0; i < size; i++) {
       a[i] = i;
       b[i] = i;
     }
     add<<<1, 256>>(a, b, c);
     for (int i = 0; i < size; i++) {
       printf("c[%d] = %d
   ", i, c[i]);
     }
     free(a);
     free(b);
     free(c);
     return 0;
   }

   This is a simple CUDA program that adds two arrays and prints the result.

7. Set a breakpoint on the line where the addition is performed by clicking on the left margin of the editor.
8. Open the integrated terminal and type "cuda-gdb ./a.out" to start the debugging session.
9. Type "run" to start the execution of the program.
10. Type "info threads" to display the threads that are running.
11. Type "thread 1" to switch to the thread that is running on the GPU.
12. Type "info registers" to display the registers that are used by the thread.
13. Type "print c" to display the value of the array "c" that is stored in the GPU memory.

Debugging GPU code can be a challenging task, but with the help of CUDA-GDB, you can make it easier. In this article, we have shown you how to display the GPU memory value when debugging with CUDA-GDB in VSCode. By following the steps, you can get the value of the GPU memory and debug your CUDA application more efficiently.

References