We adapt population annealing , a simulation scheme originating from Monte Carlo simulations , to all-atom molecular dynamics simulations . We demonstrate its excellent performance in computer simulations of biopolymers by investigating the folding of the penta-peptide met-enkephalin, a common test protein . The method is compared to the well established parallel tempering approach of accelerating simulations, and it is found to yield a similar broadening of the accessible configuration space compared to canonical simulations . In contrast to parallel tempering , however, population annealing scales to a nearly arbitrary number of parallel processors and it is thus able to tap into the massively parallel computing power available in petaflop and future exaflop machines .
Population annealing is a powerful tool for large-scale Monte Carlo simulations . We adapt this method to molecular dynamics simulations and demonstrate its excellent accelerating effect by simulating the folding of a short peptide commonly used to gauge the performance of algorithms . The method is compared to the well established parallel tempering approach and is found to yield similar performance for the same computational resources . In contrast to other methods , however, population annealing scales to a nearly arbitrary number of parallel processors and it is thus a unique tool that enables molecular dynamics to tap into the massively parallel computing power available in supercomputers that is so much needed for a range of difficult computational problems .
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performance in computer simulations of biopolymers by investigating
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the penta-peptide met-enkephalin, a common test protein
a short peptide commonly used to gauge the performance of algorithms
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of accelerating simulations, and it
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a similar broadening of the accessible configuration space compared to canonical simulations
similar performance for the same computational resources
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parallel tempering
other methods
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able
a unique tool that enables molecular dynamics
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petaflop and future exaflop machines
supercomputers that is so much needed for a range of difficult computational problems