PARALLEL COMPUTING OF ESR LINE SHAPES FROM BIOLOGICAL SYSTEMS

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 我们正在将并行计算技术应用于慢运动ESR数据的谱模拟和拟合。我们计划安装一个由16-18个节点组成的新集群来执行并行计算任务。当我们的缓慢松弛局部结构(SRLS)模型应用于更复杂的生物系统时，这将满足我们面临的日益增长的计算挑战，例如各向异性脂膜和蛋白质或/或两者的扩散倾斜或/和笼形倾斜。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。我们现在正在校园中的一些现有集群上测试我们的并行化代码，这将帮助我们根据是否有合适的资金来源来决定哪种集群最能满足我们的特殊需求。

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.