Towards accelerating molecular modeling via multi-scale approximation on a GPU

—Research efforts to analyze biomolecular properties contribute towards our understanding of biomolecular function. Calculating non-bonded forces (or in our case, electrostatic surface potential) is often a large portion of the computational complexity in analyzing biomolecular properties. Therefore, reducing the computational complexity of these force calculations, either by improving the computational algorithm or by improving the underlying hardware on which the computational algorithm runs, can help to accelerate the discovery process. Traditional approaches seek to parallelize the electrostatic calculations to run on large-scale supercomputers, which are expensive and highly contended resources. Leveraging our multi-scale approximation algorithm for calculating electrostatic surface potential, we present a novel mapping and optimization of this algorithm on the graphics processing unit (GPU) of a desktop personal computer (PC). Our mapping and optimization of the algorithm resul...

• Type: Journal
• Year: 2011
• Where: ICCABS
• Authors: Mayank Daga, Wu-chun Feng, Thomas Scogland
• Keywords: Algorithm, Applied Computing, Biomolecular Properties, Electrostatic Surface Potential, ICCABS 2011