Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Run Environmental #3

Open
WuZihao12 opened this issue Dec 25, 2023 · 12 comments
Open

Run Environmental #3

WuZihao12 opened this issue Dec 25, 2023 · 12 comments

Comments

@WuZihao12
Copy link

Thank you for your excellent work. I would like to ask if your operating environment is ubuntu20.04 or 18.04?

@qdLMF
Copy link
Owner

qdLMF commented Dec 25, 2023

Thank you for your attention. Ubuntu-18.04, ROS Melodic.

@WuZihao12
Copy link
Author

Which version of cuda are you using? I ran your job successfully using 11.0. But serious drift occurred on the MH01 data set.

@WuZihao12
Copy link
Author

image

@qdLMF
Copy link
Owner

qdLMF commented Dec 25, 2023

CUDA 11.0

@qdLMF
Copy link
Owner

qdLMF commented Dec 25, 2023

What is your GPU's compute ability?

@WuZihao12
Copy link
Author

My graphics card is the 3060 on my laptop, with a computing power of 86.

@WuZihao12
Copy link
Author

Restart the computer and the following problem occurs after re-running (cuda:11.0):
image

@qdLMF
Copy link
Owner

qdLMF commented Dec 25, 2023

It might be a problem with atomic add.
My GPU is only 5.2. If your GPU's compute capability is >= 6.0, your may have to do some changes to MyAtomicAdd() in device_utils.cu as "How To Build" section in README instructs.
Or, check if your enviroment has the macro __CUDA_ARCH__ defined, if it is defined and >= 600, compiler should generate a specialized version of MyAtomicAdd() using CUDA's atomicAdd(). I don't have a GPU with compute capability >= 6.0, so I never tested if it works.
Anyway, for details info about MyAtomicAdd(), please check it's implementation in device_utils.cu.

@WuZihao12
Copy link
Author

Although my computing power exceeds 60, I put The #if CUDA_ARCH < 600 macro is commented out, but the current one is still used. But it still gives the following error:
image

@qdLMF
Copy link
Owner

qdLMF commented Dec 25, 2023

I'm sorry that I cannot think of any solution for now. Debugging really have exhausted me when I was building this implementation. When I was debugging it, I just used the most naive way, that is, printing out all elements of all matrices along the way to txt files and check if there's any NAN.

@WuZihao12
Copy link
Author

Still want to thank you for your great work!

@qdLMF
Copy link
Owner

qdLMF commented Dec 25, 2023

Thank you for your attention.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants