PARALLEL COMPUTING OF ESR LINE SHAPES FROM BIOLOGICAL SYSTEMS

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。 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. 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. 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.