Abstract
We investigate new programming techniques for parallel tempering Monte Carlo simulations of an elementary bead-spring homopolymer model using graphics processing units (GPUs). For a precise estimation of statistical quantities, like the peak structure of the specific heat, a large number of conformations with substantial statistical data is needed. Therefore the advantage of gathering this data faster by improving the performance of Monte Carlo simulations cannot be overrated. With the huge computational capability of the large number of cores on GPUs, that can be exploited by means of multithreaded programming, we find significant increases in e_ciency compared to CPU-only simulations.
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