AlphaFold 3本地部署配置求助，会涉及到一些较大的蛋白

wqm

求助一下各位前辈，AlphFold网页版我怕有泄密的风险，如果部署到本地有泄密的风险吗？部署到本地需要什么配置呢？会涉及到一些较大的蛋白

yzh

本地部署需要硬件要求比较高，只扫显存24GB以上吧，我记得

student0618

官方github repo写了：

https://github.com/google-deepmi ... ocs/installation.md

Installation and Running Your First Prediction
You will need a machine running Linux; AlphaFold 3 does not support other operating systems. Full installation requires up to 1 TB of disk space to keep genetic databases (SSD storage is recommended) and an NVIDIA GPU with Compute Capability 8.0 or greater (GPUs with more memory can predict larger protein structures). We have verified that inputs with up to 5,120 tokens can fit on a single NVIDIA A100 80 GB, or a single NVIDIA H100 80 GB. We have verified numerical accuracy on both NVIDIA A100 and H100 GPUs.

Especially for long targets, the genetic search stage can consume a lot of RAM – we recommend running with at least 64 GB of RAM.

We provide installation instructions for a machine with an NVIDIA A100 80 GB GPU and a clean Ubuntu 22.04 LTS installation, and expect that these instructions should aid others with different setups. If you are installing locally outside of a Docker container, please ensure CUDA, cuDNN, and JAX are correctly installed; the JAX installation documentation is a useful reference for this case. Please note that the Docker container requires that the host machine has CUDA 12.6 installed.

https://github.com/google-deepmi ... ocs/known_issues.md

Numerical performance for CUDA Capability 7.x GPUs
All CUDA Capability 7.x GPUs (e.g. V100) produce obviously bad output, with lots of clashing residues (the clashes cause a ranking score of -99 or lower), unless the environment variable XLA_FLAGS is set to include --xla_disable_hlo_passes=custom-kernel-fusion-rewriter.

woxun

一般50万左右的机器就能装了吧