ACCELERATION OF MOLECULAR MODELING APPLICATIONS WITH GRAPHICS PROCESSORS

使用图形处理器加速分子建模应用

• 批准号: 8363650
• 负责人: John H Stone
• 金额: $ 3.32万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2012-09-09
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8363650
• 关键词: Acceleration; Architecture; Bioinformatics; Computer software; Funding; Generations; Grant; Individual; Modeling; Molecular Models; National Center for Research Resources; Performance; Principal Investigator; Process; Research; Research Infrastructure; Resources; Source; Time; United States National Institutes of Health; cost; molecular modeling; operation

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Over the past several years, the hardware and software architecture of graphics processing units (GPUs) has evolved to the point that they can now be used for general purpose scientific computations. State-of-the-art graphics processors include hundreds of individual arithmetic units and can perform up to 500 billion floating point operations per second, a level of performance far above that available with current generation CPU cores. The Resource has implemented several GPU-accelerated computational kernels for key molecular modeling tasks which achieve performance levels of ten to one hundred times that of traditional CPU implementations (http://www.ks.uiuc.edu/Research/gpu/).

该子项目是利用资源的众多研究子项目之一 由 NIH/NCRR 资助的中心拨款提供。子项目的主要支持 并且子项目的主要研究者可能是由其他来源提供的， 包括其他 NIH 来源。 子项目可能列出的总成本 代表子项目使用的中心基础设施的估计数量， NCRR 赠款不直接向子项目或子项目工作人员提供资金。 过去几年，图形处理的软硬件架构 单元（GPU）已经发展到现在可以用于通用目的 科学计算。 最先进的图形处理器包括数百个独立的 算术单元，每秒可执行多达 5000 亿次浮点运算， 性能水平远远高于当前一代 CPU 内核的性能水平。 这 Resource 已针对关键分子实现了多个 GPU 加速的计算内核 建模任务的性能水平是现有任务的十到一百倍 传统 CPU 实现 (http://www.ks.uiuc.edu/Research/gpu/)。