Using State-of-the-Art GPGPU's for Molecular Simulation : Optimizing Massively Parrallelized N-Body programs using NVIDIA Tesla

Computation and simulation as a tool for discovering new knowledge is still marred by problems that are intractable, combinatoric, or simply plagued by the so called curse of dimensionality. The algorithm used for molecular simulation of polyelectrolytes is one of those areas in computational chemistry and science suffering from the curse of dimensionality. Much of the problems, though, have been claimed to be solvable with the advent of more sophisticated and powerful computers and related technologies. This paper attempts to substantiate the claim. In this paper, a state-of-the-art NVIDIA Tesla C870 has been utilized to massively parallelize the algorithm for the molecular simulation of polyelectrolytes. In particular, this paper attempts to optimize the portion of the code involving the computation of electrostatic interaction using the new technology. It has been shown that tapping this new line of technology poses great advantage in winning the war against the curse of dimensionality