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

Problem excecuting ani_quicktest.py with Geforce RTX 3080 #38

Open
TeruoHIRAKAWA opened this issue Jan 12, 2021 · 6 comments
Open

Problem excecuting ani_quicktest.py with Geforce RTX 3080 #38

TeruoHIRAKAWA opened this issue Jan 12, 2021 · 6 comments

Comments

@TeruoHIRAKAWA
Copy link

TeruoHIRAKAWA commented Jan 12, 2021

Hello!

Thanks very much for this open-source project. It has been a great experience.

I would like to ask you fever.
Recently, I have bought a new PC with one component, Nvidia Geforce RTX 3080.
When I was running ani_quicktest.py after I installed ASE_ANI and related essential software, I got an error:

python ani_quicktest.py

ERROR: CUDA throw detected! Attempting to shut down nicely!
CUDA Error -- "invalid device symbol"
13 in location -- /home/jujuman/Gits/NeuroChem/src-aevlib/cuda_aev/cuaev_compute.cu:1939
in function -- cuaev_compute_base()

Traceback (most recent call last):
File "ani_quicktest.py", line 21, in
mol.set_calculator(ANIENS(aniensloader('../ani_models/ani-1ccx_8x.info',0)))
File "/home/micro/local/ASE_ANI/lib/ase_interface.py", line 1038, in aniensloader
return ensemblemolecule(cnstfile, saefile, nnfdir, Nn, gpu)
File "/home/micro/local/ASE_ANI/lib/ase_interface.py", line 477, in init
self.ncl = [pync.molecule(cnstfile, saefile, nnfprefix + str(i+net_start_id) + '/networks/', 1, gpuid, sinet) for i in
File "/home/micro/local/ASE_ANI/lib/ase_interface.py", line 477, in
self.ncl = [pync.molecule(cnstfile, saefile, nnfprefix + str(i+net_start_id) + '/networks/', 1, gpuid, sinet) for i in
RuntimeError: unidentifiable C++ exception

I assumed that it may be due to Nvidia Geforce RTX 3080 having a new device symbol,
however, I could not solve the problem by myself.

Would you have some ideas to solve it?
Any help would be much appreciated.

Let me inform you of an overview of the PC:

Operating system: Ubuntu Desktop 18.04.5
Nvidia driver version: Driver Version: 460.32.03
CUDA toolkit version: 9.2
Python version: 3.8.5

CPU: Intel(R) Core(TM) i9-10900F CPU @ 2.80GHz
Memory: 64 GB
GPU: Nvidia Geforce RTX 3080 (10GB)

Best regards,

Teruo.

@isayev
Copy link
Owner

isayev commented Jan 12, 2021

Dear Teruo:
Thanks for reporting that. CUDA 9 is way too old for RTX 3080. Could you please try CUDA10/Python 3.6 branch: https://github.com/isayev/ASE_ANI/tree/centos_cuda10_py36
If not, we probably need to update the code. Unfortunately, I do not have a 3 series card to test real quick.

@Jussmith01
Copy link
Collaborator

Jussmith01 commented Jan 12, 2021

This has to do with what compute architecture the binary was built for, which is CUDA compute 8.6 for the GTX 3080 I think. None of the current binaries are built for this, so it cannot be fixed without recompiling the code. I will try to upload a new set of binaries soon.

@TeruoHIRAKAWA
Copy link
Author

Dear Prof. Isayev and Dr. Smith,

I truly appreciate your quick reply.

Firstly, I tried to use ASE_ANI on CUDA10/Python 3.6 Branch,
however, I got the same error:

% python ani_quicktest.py

ERROR: CUDA throw detected! Attempting to shut down nicely!
CUDA Error -- "invalid device symbol"
13 in location -- /home/jujuman/Gits/NeuroChem/src-aevlib/cuda_aev/cuaev_compute.cu:1939
in function -- cuaev_compute_base()

Traceback (most recent call last):
File "ani_quicktest.py", line 21, in
mol.set_calculator(ANIENS(aniensloader('../ani_models/ani-1ccx_8x.info',0)))
File "/home/micro/local/ASE_ANI/lib/ase_interface.py", line 1038, in aniensloader
return ensemblemolecule(cnstfile, saefile, nnfdir, Nn, gpu)
File "/home/micro/local/ASE_ANI/lib/ase_interface.py", line 477, in init
self.ncl = [pync.molecule(cnstfile, saefile, nnfprefix + str(i+net_start_id) + '/networks/', 1, gpuid, sinet) for i in
File "/home/micro/local/ASE_ANI/lib/ase_interface.py", line 477, in
self.ncl = [pync.molecule(cnstfile, saefile, nnfprefix + str(i+net_start_id) + '/networks/', 1, gpuid, sinet) for i in
RuntimeError: unidentifiable C++ exception

Let me inform you of an overview of the PC:

Operating system: Ubuntu Desktop 18.04.5
Nvidia Driver Version: 460.32.03
CUDA toolkit version: 10.0
Python version: 3.8.5

CPU: Intel(R) Core(TM) i9-10900F CPU @ 2.80GHz
Memory: 64 GB
GPU: Nvidia Geforce RTX 3080 (10GB)

This has to do with what compute architecture the binary was built for, which is CUDA compute 8.6 for the GTX 3080 I think. None of the current binaries are built for this, so it cannot be fixed without recompiling the code. I will try to upload a new set of binaries soon.

Thank you very much for your prompt attention to this matter.
That would really help me if it’s not too much trouble for you.

If there is anything else I could do to help you then please do ask, like an operation test for the recompiled ASE_ANI.
I have bought two PCs, each of which has Geforce RTX 3080/3090.

Best regards,

@turboresearcher
Copy link

Dear @TeruoHIRAKAWA, have you solved the problem you described (related to usage of RTX3080 with CUDA10)? If so, I'd be grateful if you could share the details about it since I'm having the same trouble.
Best regards!

@aydinmirac
Copy link

Hello,

I'm also having the same issue. I tried to run the code with different CUDA versions such as 9.2, 10.0 and 10.2. But I was not able to solve the issue. It always throws "ERROR: CUDA throw detected! Attempting to shut down nicely!"

Do you have any suggestion for this problem?

Thanks for your help.
Best regards

@isayev
Copy link
Owner

isayev commented Apr 5, 2022

Hey @miracaydin1, this code is now legacy, as it was customarily compiled for specific CUDA and Nvidia architectures. I strongly encourage you to use TorchANI https://github.com/aiqm/torchani instead.

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

5 participants