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RAM usage #5
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That's weird; I've tested the example on a Linux system with 32G of memory and it runs fine. Although memory requirements will scale with the length of your target sequence, the included example is fairly small and should be able to run without requiring too many resources. From that output it looks like the memory leak is occurring in the neural network code. What operating system and versions of Python and various Python packages you are using? The output of |
Thanks for the quick response! Here's my
This is running on ubuntu 20.04 |
Hmmm, I can't reproduce this on a CentOS 7 system. A few things to try/check: |
I tried deleting the pycache dir but still ran into the same issue. And I'm not running a virtual machine. These are the versions of the dependencies I've installed in case its relevant: Here's the contents of the test directory.
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I must say I'm stumped. I cannot work out what's going wrong. I notice that your test directory contains PSIBLAST output files that shouldn't be created for the test job. If you ran the example in a different running mode, that should be fine. The file sizes all look correct. This is the point where I'd try the code on a different system or with a fresh Anaconda/Miniconda install (not just a new environment). While trying to match your package list I did find differences in the dependencies that PyTorch etc. pick up, though I think it's unlikely that that's what's causing the problem. Worth a try though. |
Thanks for your help! I'll probably give it a shot on another system and see if it goes better |
I installed DeepMetaPSICOV locally, and it appears to be running correctly. However, it steadily consumes my RAM until all RAM and swap are in use and my system kills the process. I have 64GB of RAM on my local machine. Do you have an idea of the system requirements for the tool? I can try running on my cluster as well, but that will make installation more challenging.
Output as follows:
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