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What is the difference between ACEMD 3 and ACEMD 4?
A key new feature is the integration of machine learning into molecular simulations. Specifically, we are implementing a new method called NNP/MM.
What is NNP/MM?
NNP/MM is a hybrid simulation method combining neural network potentials (NNP) and molecular mechanics (MM). NNP can model the molecular interactions more accurately than the conventional force fields in MM, but it still is not as fast as MM. Thus, only the important part of a molecular system is simulated with NNP, while the rest part is using MM. You can read more in a pre-print of the NNP/MM article: https://arxiv.org/abs/2201.08110
How much more accurate is NNP?
You can read a pre-print of the TorchMD-NET article: https://arxiv.org/abs/2202.02541
What are software/hardware requirements for ACEMD 4?
Pretty much the same as for ACEMD 3. Only the significant change is the size of the software stack. ACEMD 3 and all its dependencies need just 1 GB, while for ACEMD 4 that has increased to 3 GB, notably due to PyTorch (https://pytorch.org). Also, at the moment, there are just the Linux version for CUDA >=11.2 available.
When will ACEMD 3 be replaced by ACEMD 4?
Within a few months, we will release ACEMD 4 officially and ACEMD 3 will be deprecated. For a moment, the apps will coexist and you will receive WUs for both of them.
What will happen next?
We have already sent several WUs to test the deployment of ACEMD 4 and will continue this week. Let us know, if you notice some irregularities. Next week, we are aiming to start sending production WUs.
Happy computing,
Raimondas
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