SI2-SSE: Development of a GPU Accelerated Gibbs Ensemble Monte Carlo Simulation Engine

Wayne State University, Detroit MI

Investigators

Abstract

This award supports the development of a general purpose Gibbs Ensemble Monte Carlo (GEMC) simulation engine that uses low-cost graphics processing units (GPU) for acceleration. The primary objectives of this work are to develop and implement: 1) GPU accelerated configurational-bias methods, 2) efficient algorithms for the computation of Ewald sums on the GPU and 3) automated tuning of the code for different GPUs. This work builds on the PIs? existing particle-based GPU-GEMC engine and will introduce functionality that enables the simulation of biological processes and adsorption in porous materials. The code will be written to maintain compatibility with the file formats used by the software packages NAMD and VMD, simplifying simulation setup and data analysis. The resulting simulation engine will be released under the GNU General Public License v3 (GPLv3) and made available to users via the Internet. The software tools developed with support from this award will enable high throughput computational screening of materials for CO2 sequestration, improved materials for the stabilization of drug dispersions, and provide molecular level insight to fundamental biological processes such as membrane fusion. The use of graphics processors for the bulk of the computational effort is expected to provide one to two orders of magnitude reduction in computational time compared to traditional serial, CPU bound code, which will allow for the simulation of systems of greater size and complexity than with existing tools. The development of the proposed GPU-accelerated Monte Carlo simulation engine will enhance the cyber-infrastructure of the biology chemistry, chemical engineering, materials science and physics communities. The GPU-GEMC simulation engine will be promoted through conference presentations at national and international meetings, via a dedicated website, and through publication in peer-reviewed literature. This award will enhance education at the graduate and undergraduate levels. Research topics from this work will be integrated into existing courses on GPU computing and molecular simulation. Graduate and undergraduate students will have the opportunity to work as part of a multidisciplinary team composed of engineers and computer scientists. Students will be recruited from groups traditionally underrepresented in STEM fields.