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Energy efficient biomolecular simulations with FPGA-based reconfigurable computing

Ananth Nallamuthu, Melissa C. Smith, Scott Hampton, Pratul K. Agarwal, Sadaf R. Alam
Clemson University, Clemson, SC, USA
In Proceedings of the 7th ACM international conference on Computing frontiers (2010), pp. 83-84

@conference{nallamuthu2010energy,

   title={Energy efficient biomolecular simulations with FPGA-based reconfigurable computing},

   author={Nallamuthu, A. and Smith, M.C. and Hampton, S. and Agarwal, P.K. and Alam, S.R.},

   booktitle={Proceedings of the 7th ACM international conference on Computing frontiers},

   pages={83–84},

   year={2010},

   organization={ACM}

}

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Reconfigurable computing (RC) is being investigated as a hardware solution for improving time-to-solution for biomolecular simulations. A number of popular molecular dynamics (MD) codes are used to study various aspects of biomolecules. These codes are now capable of simulating nanosecond time-scale trajectories per day on conventional microprocessor-based hardware, but biomolecular processes often occur at the microsecond time-scale or longer. A wide gap exists between the desired and achievable simulation capability; therefore, there is considerable interest in alternative algorithms and hardware for improving the time-to-solution of MD codes. The fine-grain parallelism provided by Field Programmable Gate Arrays (FPGA) combined with their low power consumption make them an attractive solution for improving the performance of MD simulations. In this work, we use an FPGA-based coprocessor to accelerate the compute-intensive calculations of LAMMPS, a popular MD code, achieving up to 5.5 fold speed-up on the non-bonded force computations of the particle mesh Ewald method and up to 2.2 fold speed-up in overall time-to-solution, and potentially an increase by a factor of 9 in power-performance efficiencies for the pair-wise computations. The results presented here provide an example of the multi-faceted benefits to an application in a heterogeneous computing environment.
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