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

SI2-SSE：GPU 加速吉布斯集成蒙特卡罗仿真引擎的开发

• 批准号: 1148168
• 负责人: Jeffrey Potoff
• 金额: $ 32万
• 依托单位: Wayne State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1148168&HistoricalAwards=false
• 关键词: SI2; SSE; Development; GPU; Accelerated

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.

该奖项支持通用Gibbs Ensemble Monte Carlo（GEMC）仿真引擎的开发，该引擎使用低成本图形处理单元（GPU）进行加速。 这项工作的主要目标是开发和实现：1）GPU加速的配置偏置方法，2）在GPU上计算Ewald和的有效算法，3）针对不同GPU的代码自动调整。 这项工作建立在PI的基础上？GEMC引擎的基础上，将引入功能，使生物过程和多孔材料中的吸附模拟。 编写的代码将保持与软件包NAMD和VMD使用的文件格式的兼容性，简化模拟设置和数据分析。 由此产生的模拟引擎将在GNU通用公共许可证v3（GPL v3）下发布，并通过互联网提供给用户。 在该奖项的支持下开发的软件工具将能够对CO2封存材料进行高通量计算筛选，改善药物分散体稳定性的材料，并为膜融合等基本生物过程提供分子水平的见解。 与传统的串行、CPU绑定代码相比，使用图形处理器进行大量的计算工作预计将在计算时间上减少一到两个数量级，这将允许模拟比现有工具更大尺寸和复杂度的系统。 建议的GPU加速蒙特卡罗模拟引擎的开发将增强生物化学，化学工程，材料科学和物理社区的网络基础设施。 GPU-GEMC模拟引擎将通过在国家和国际会议上的会议演示、通过专门的网站以及通过同行评审文献的出版来推广。该奖项将加强研究生和本科生的教育。 这项工作的研究课题将整合到GPU计算和分子模拟的现有课程中。 研究生和本科生将有机会作为由工程师和计算机科学家组成的多学科团队的一部分工作。 学生将从传统上在STEM领域代表性不足的群体中招募。