cuEquivarance and MACE under Windows 11

[husakm]

I was trying to install cuEquivariance support for MACE under Windows. It does not work and the responsible people on GitHub told me "Unfortunately, we see very few use cases in windows, so we are not planning to support that at the moment.
Depending on your setup, you might be able to use Windows Subsystem for Linux to use these wheels. Unfortunately, we cannot help more for now."
NVIDIA/cuEquivariance#187
Any idea what to do (our software using MACE and ACE is totally Windows targeted) ? I believe e.g. BIOVIA using MACE in its commercial Materials Studio product will not agree with "we see very few use cases in windows" statement.

[gabor1]

yes, I think you need to use a virtual machine or something similar. Biovia is indeed selling MACE as part of Materials Studio, but it doesn't have cuEquivariance acceleration - for multiple reasons.

[gabor1]

you can try Symmetrix, it is a plugin to lammps that can load MACE models, and supports both CPU and GPU. Does not require python

[husakm]

Generally I have no problem to use python. I run on Windows 11 under python multiple ML FF/ASE engines (MACE, FAIRCHEM, aim2NET). We had encoded a C# interface for our task (crystal structures verification) and it works OK even with cuda. I will try the cuda-mace code mentioned in the MACE article if cuEquivaraince is really not supported under Windows.
I have a licence for older BIOVIA Materials Studio than the one with MACE support. It will be interesting to know for me how MACE works inside the BIOVIA framework ... Especially whatever it is integrated inside Polymorph Predictor = potential revolution in crystal structure precondition technology.

[gabor1]

organic crystal structure polymorphs need exquisite accuracy, and special training for that. we are making mace models that deliver that kind of accuracy specifically for that task, but those are not yet in Materials Studio. it will get there eventually, but I am sure they will be available just as PyTorch models first.

[husakm]

I had tested the MACE OFF23 L force field on replication of the CSP7 structure prediction test (structure ranking).
https://journals.iucr.org/b/issues/2024/06/00/aw5094/index.html
The comparison was done with the correct result as well as with my result base don r2SCAN+MBD DFT. I can confirm MACE was able to give comparable result as the DFT = it is fully suitable for the first stage of CSP (structure generation) as well as for potential structure ranking (it it is done hierarchicaly , first MACE, than high-level DFT).
Generally do you wan to tell BIOVIA does not support PyTorch + CUDA acceleration now ? It is probably true, because thy do not mention GPU acceleration in their materials ...

[gabor1]

Try also mace-omol - I think it would do better than MACE-OFF, but curious to see your results.

yes, at present, biovia does not support cuda acceleration for mace. but since it's a major issue, we are working with them closely to achieve this.