Greetings. I am contemplating buying a desktop with the following specs to enhance the performance of molecular dynamic simulations (GROMACS) and other computational works (e.g., homology modeling, energy optimization using Gaussian, etc.). Could this desktop significantly improve the MD and reduce the simulation time? Using the current laptop, I needed around 5 days to run a 30 ns simulation, which is extremely slow.
I7-14thgen
32GB ram
1TB SSD
RTX 3050
Windows 11 pro
Chun Hoe Tan
The GPU would be good for the MD simulations, while you would use the CPU cores for the Gaussian simulations.
I currently have desktop computers in my lab with RTX3060 (12GB) cards, 16 GB RAM and Ryzen 5 CPUs which perform quite well for some systems we get approximately 80 - 100ns a day using Amber as the MD engine.
Just ensure that for the MD you make use of windows subsystem for Linux (WSL) to get full access to the graphics card for your MD.
@Chun Hoe Tan: Previously, I used desktop workstations with Intel CPUs, but more recently, I have found AMD Threadripper Pro CPUs to have better performance with MD simulations and protein folding. However, GPU acceleration is of paramount importance for these applications -- I recommend using an Nvidia GPU with high values for onboard RAM and clock speed. CPU RAM of 32GB is probably fine. A main NVME SSD of 1TB should suffice, but if you do many MD simulations, you will want to offload the trajectory files to an additional high-capacity disk for longer-term storage. Finally, for running simulations, I suggest using Linux rather than Windows as the operating system.
Dear Rudy J Richardson , thank you for your constructive input, it is very helpful!
Yes, but performance gains will be moderate. For GROMACS, AMD Ryzen 9 or Intel i9 (more cores), high-speed RAM (DDR5), and a higher-end GPU (RTX 4070+ for CUDA acceleration) would be better. Consider Linux for better MD performance.
All of which can we easily done at mdsim360.com, a new platform that lets you run MD simulations entirely online without local installation.
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