ACCELERATION OF MOLECULAR MODELING APPLICATIONS WITH GRAPHICS PROCESSORS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 在过去的几年中，图形处理器(GPU)的硬件和软件体系结构已经发展到 指出它们现在可以用于一般目的的科学计算。最先进的图形处理器包括 数百个单独的算术单元，每秒可执行高达5000亿次浮点运算， 性能远远超过当前一代CPU内核。该资源已经实现了几个GPU- 用于关键分子建模任务的加速计算内核，可实现10到1的性能级别 是传统处理器实施(http://www.ks.uiuc.edu/Research/gpu/).)的数百倍

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. 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/).