Chengkui Zhao
Chengkui Zhao
> I also use RTX4090. My driver version is 520.61.05, and the CUDA version is 11.8. In my case, I solved the problem by editing the Dockerfile in docker folder....
> I also use RTX4090. My driver version is 520.61.05, and the CUDA version is 11.8. In my case, I solved the problem by editing the Dockerfile in docker folder....
Bro, I just solve this problem several days ago. Change the Dockerfile from ARG CUDA=11.1.1 FROM nvidia/cuda:${CUDA}-cudnn8-runtime-ubuntu18.04 to ARG CUDA=11.8.0 FROM nvidia/cuda:${CUDA}-cudnn8-devel-ubuntu22.04 And re-build the docker. That will be OK.
> I tried to run AlphaFold latest version on a new machine with **GPU RTX4090, CUDA version 11.8 (downgraded from 12.2), Ubuntu 22.04 LTS.** I used anaconda3 to build the...
> > > I tried to run AlphaFold latest version on a new machine with **GPU RTX4090, CUDA version 11.8 (downgraded from 12.2), Ubuntu 22.04 LTS.** I used anaconda3 to...
> I tried to run AlphaFold latest version on a new machine with **GPU RTX4090, CUDA version 11.8 (downgraded from 12.2), Ubuntu 22.04 LTS.** I used anaconda3 to build the...
> So, I have an example **protein A** that is very similar to my **protein B** I aim to study. The **protein A** has a binder **A-binder**, and I use...
> > Alphafold Multimer LSI score > > Thanks! No, I am sorry I didn't try it, but I will try it as soon as possible. Because I can get...
> > > > Alphafold Multimer LSI score > > > > > > > > > Thanks! No, I am sorry I didn't try it, but I will try...
It takes me very long time when running "conda env create -f env/SE3nv.yml", staying in Solving environment. Any body knows the reason?