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100 nanoseconds a day. 100 nanoseconds a day. 100 nanoseconds a day
That is amazing. I used to get supercomputing time to do 100 ns simulations during my PhD and those used to last days, but that’s exactly what NAMD has achieved recently. A recent review article by the folks at D.E. Shaw Research lays down the state of protein simulations.
To put the 100 ns in context. That simulation was done on 300 cores. Given that you can get 1000 cores increasingly easily, that’s 1000 ns in 3.3. days assuming linear scaling. So when D.E. Shaw and co write that microsecond simulations are getting practical (increasingly feasible would be a better statement), they’re not just saying that. I think if access to 3000 cores and these compute scales becomes commoditized (not difficult looking at the kinds of trends I am seeing), then we are in business and it is indeed practical.
NAMD, Gromacs, Desmond. For the first time in a long time, I really want to do MD again. Now to make the entire MD ecosystem more practical. I would love to see services around such codes that make it easier to run large jobs, include system preparation, and perhaps even analysis.
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2 Comments
The computing power is an important advance, but I'd be more worried about the forcefields, etc. Admittedly, it's been a while since I was doing MD, but protein simulations of any length had a tendency to start coming apart at the seams. Of course, if you can run millisecond simulations at 1/day, you stand a much better chance of refining a model to the point where it will stand up to milliseconds of simulation time.
John
Completely agree. The physics could be improved greatly. Simulations today do tend to stay together, cause you are using explicit waters and better implicit models, but in general there are three challenges; compute power, force fields and programming models. We've got #1 in good shape, and #3 is better than before. #2 we need to work on.