Embedded Files
In-house resources
Dr. Choudhuri's lecture notes (PDFs) on Statistical Mechanics
Dr. Choudhuri's recorded lectures on computational methods
HOWTO perform AIMD using VASP
Analysis and simulation codes used by our group
hardware and software
hardware and software
Group Mini Cluster: 1 head node (20 cores), 6 nodes (40 cores/node), CentOS
Group Workstation: 56 cores, NVIDIA RTX 6000 ADA GPU, Ubuntu
Alpine cluster, University of Colorado: 256 nodes (64 cores / node) and 10 GPU (RMACC access)
NMT's High Performance Computing cluster: 16 nodes (96 cores / node) and 2 GPU (under construction - funding from an NSF-MRI grant)
Licensed software: Vienna Ab initio Simulation Package (VASP), MedeA GUI and software suite
Open source software: LAMMPS (for classical MD), CP2K and Quantum Espresso (DFT and ab initio MD), Scikit-Learn, PyTorch
External resources
Official VASP website containing tutorials for advanced AIMD simulations, e.g., enhanced sampling, ML applications
Python codes for carrying out machine-learning tasks using Jupyter notebook. It mostly focuses on Scikit-learn
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