This thesis covers comparison between different computer platforms of high performance computing while performing molecular dynamics simulations, which falls under very complex problems and needs lots of processing power. Our goal was to critically evaluate different platforms while solving molecular dynamics, so we used 1 to 16 processor cores on a computer cluster and one and two graphics processing units (GPU) for simulations. The results will be used while planning on buying new computer hardware for biomolecular simulations.
We used time needed for simulations and platform scalability as our benchmarks. For comparing speed in biomolecular simulations we used ns/day for comparison. Ns/day tells us how many nanoseconds is a system capable of simulating in one day.
For this thesis we simulated a large hydrated MAO B protein with endogen phenylethylamine substrate. The simulated system is extremely important for neuroscience, since it regulates levels of biogenic amines, which have an essential part in neuro signal transmitting.
The results have shown us that the use of GPUs is significantly faster than regular processors when it comes to molecular dynamics. Moreover it is also the most cost effective platform for classical molecular dynamics. From the perspective of scalability it makes sense to only use one GPU at the time, since the speed-up when using two GPUs is lower than expected.
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