Cuda-gdb aborted

1553725576 · November 20, 2024, 2:20am

version

exec: /usr/local/cuda/bin/cuda-gdb-python3.10-tui --version

NVIDIA (R) cuda-gdb 12.6

Based on GNU gdb 13.2

License GPLv3+: GNU GPL version 3 or later http://gnu.org/licenses/gpl.html

This is free software: you are free to change and redistribute it.

There is NO WARRANTY, to the extent permitted by law.

code

include <cuda.h>
include <stdio.h>

// compute vector sum C = A + B
// each thread peforms one pair-wise addition
global void vecAddKernel(float *A, float *B, float *C, int n) {
int i = threadIdx.x + blockDim.x * blockIdx.x;
if (i < n) {
C[i] = A[i] + B[i];
}
}

// What is the canonical way to check for errors using the CUDA runtime API? - Stack Overflow
define gpuErrchk(ans) { gpuAssert((ans), FILE, LINE); }
inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort = true) {
if (code != cudaSuccess) {
fprintf(stderr, “GPUassert: %s %s %d\n”, cudaGetErrorString(code), file, line);
if (abort) {
exit(code);
}
}
}

inline unsigned int cdiv(unsigned int a, unsigned int b) {
return (a + b - 1) / b;
}

void vecAdd(float *A, float *B, float *C, int n) {
float *A_d, *B_d, *C_d;
size_t size = n * sizeof(float);

cudaMalloc((void **)&A_d, size);
cudaMalloc((void **)&B_d, size);
cudaMalloc((void **)&C_d, size);

cudaMemcpy(A_d, A, size, cudaMemcpyHostToDevice);
cudaMemcpy(B_d, B, size, cudaMemcpyHostToDevice);

const unsigned int numThreads = 256;
unsigned int numBlocks = cdiv(n, numThreads);

vecAddKernel<<<numBlocks, numThreads>>>(A_d, B_d, C_d, n);
gpuErrchk(cudaPeekAtLastError());
gpuErrchk(cudaDeviceSynchronize());

cudaMemcpy(C, C_d, size, cudaMemcpyDeviceToHost);

cudaFree(A_d);
cudaFree(B_d);
cudaFree(C_d);
}

int main() {
const int n = 1000;
float A[n];
float B[n];
float C[n];

// generate some dummy vectors to add
for (int i = 0; i < n; i += 1) {
A[i] = float(i);
B[i] = A[i] / 1000.0f;
}

vecAdd(A, B, C, n);

// print result
for (int i = 0; i < n; i += 1) {
if (i > 0) {
printf(“, “);
if (i % 10 == 0) {
printf(”\n”);
}
}
printf(“%8.3f”, C[i]);
}
printf(“\n”);
return 0;
}

compile

nvcc -g -G vector_add.cu -o vector_add

device

±----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
±----------------------------------------------------------------------------------------+

debug

cuda-gdb vector_add

error info

NVIDIA (R) cuda-gdb 12.6

Based on GNU gdb 13.2

License GPLv3+: GNU GPL version 3 or later http://gnu.org/licenses/gpl.html

This is free software: you are free to change and redistribute it.

There is NO WARRANTY, to the extent permitted by law.

Type “show copying” and “show warranty” for details.

This CUDA-GDB was configured as “x86_64-pc-linux-gnu”.

Type “show configuration” for configuration details.

For bug reporting instructions, please see:

https://forums.developer.nvidia.com/c/developer-tools/cuda-developer-tools/cuda-gdb.

Find the CUDA-GDB manual and other documentation resources online at:

https://docs.nvidia.com/cuda/cuda-gdb/index.html.

For help, type “help”.

Type “apropos word” to search for commands related to “word”…

Reading symbols from vector_addition…

(cuda-gdb) b main

Breakpoint 1 at 0xae0a: file /root/lectures/lecture_002/vector_addition/vector_addition.cu, line 53.

(cuda-gdb) run

Starting program: /root/lectures/lecture_002/vector_addition/vector_addition

warning: Error disabling address space randomization: Operation not permitted

[Thread debugging using libthread_db enabled]

Using host libthread_db library “/usr/lib/x86_64-linux-gnu/libthread_db.so.1”.

Breakpoint 1, main () at /root/lectures/lecture_002/vector_addition/vector_addition.cu:53

Fatal signal: Segmentation fault

----- Backtrace -----

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0xffffffffffffffff ???

A fatal error internal to GDB has been detected, further

debugging is not possible. GDB will now terminate.

This is a bug, please report it. For instructions, see:

https://forums.developer.nvidia.com/c/developer-tools/cuda-developer-tools/cuda-gdb.

Segmentation fault (core dumped)

veraj · November 21, 2024, 3:38am

Hi, @1553725576

Have you tried to run the sample without cuda-gdb ? Can it run to end successfully ?

veraj · November 21, 2024, 5:40am

Hi, @1553725576

We can’t reproduce your issue.

$ /usr/local/cuda-12.6/bin/cuda-gdb-python3.10-tui ./vector_add
NVIDIA (R) cuda-gdb 12.6
Portions Copyright (C) 2007-2024 NVIDIA Corporation
Based on GNU gdb 13.2
Copyright (C) 2023 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later http://gnu.org/licenses/gpl.html
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.
Type “show copying” and “show warranty” for details.
This CUDA-GDB was configured as “x86_64-pc-linux-gnu”.
Type “show configuration” for configuration details.
For bug reporting instructions, please see:
https://forums.developer.nvidia.com/c/developer-tools/cuda-developer-tools/cuda-gdb.
Find the CUDA-GDB manual and other documentation resources online at:
https://docs.nvidia.com/cuda/cuda-gdb/index.html.

For help, type “help”.
Type “apropos word” to search for commands related to “word”…
Reading symbols from ./vector_add…
(cuda-gdb) b main
Breakpoint 1 at 0xae0a: file /home/test/daniel/forum/20241121/vector_add.cu, line 53.
(cuda-gdb) r
Starting program: /home/test/daniel/forum/20241121/vector_add
[Thread debugging using libthread_db enabled]
Using host libthread_db library “/lib/x86_64-linux-gnu/libthread_db.so.1”.

Breakpoint 1, main () at /home/test/daniel/forum/20241121/vector_add.cu:53
53 int main() {
(cuda-gdb) n
54 const int n = 1000;

1553725576 · November 21, 2024, 6:36am

yes, it can run successfully.

veraj · November 21, 2024, 6:49am

From the warning message

warning: Error disabling address space randomization: Operation not permitted

This seems related with your set up. Please check if gdb can’t work also.
If yes, please try
$echo 0 | sudo tee /proc/sys/kernel/yama/ptrace_scope

1553725576 · November 21, 2024, 10:35am

cuda-gdb work now, thanks.

veraj · November 22, 2024, 2:07am

Good to know about this !

veraj · November 24, 2024, 2:08am

This topic was automatically closed 2 days after the last reply. New replies are no longer allowed.

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