PARALLEL COMPUTING OF ESR LINE SHAPES FROM BIOLOGICAL SYSTEMS

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 我们将并行计算技术应用于慢运动ESR数据的光谱模拟和拟合。 我们计划安装一个16-18节点的新集群来实现并行计算任务。 这将满足我们所面临的越来越多的计算挑战时，我们的缓慢松弛局部结构（SRLS）模型被应用到更复杂的生物系统，如各向异性脂膜和蛋白质的任一/两者的扩散倾斜或/和笼倾斜。 它还将允许我们包括更多的动态模式，以更好地近似这些系统中的旋转动力学。我们现正在校园内多个现有的联网上测试并行代码，这将有助于我们决定哪种联网最适合我们的特殊需要，视乎是否有合适的资金来源而定。

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. We are applying parallel computing techniques to the spectral simulations and fittings of slow motional ESR data. We are planning on installing a new cluster of 16-18 nodes to implement the parallel computing tasks. This will meet the increasing computational challenges we are facing when our slowly relaxing local structure (SRLS) model is applied to more complex biological systems, such as anisotropic lipid membranes and protein either/both diffusion tilts or/and cage tilts. It will also allow us to include more dynamic modes to better approximate the rotational dynamics in these systems. We are now testing our parallelized codes on a number of existing clusters on campus, which will help us to decide what kind of cluster best meets our special needs, contingent on the availability of suitable funding sources.