A Scalability Study (as a Guide for HPC Operations at a Remote Test Facility) on DSRC HPC Systems of Radio Frequency Tomography Code Written for MATLAB® and Parallelized via Star-P®

B. Elton, S. Samsi, H. Smith, L. Humphrey, B. Guilfoos, S. Ahalt, A. Chalker, K. Magde, Niraj Srivastava, A. H. Abdullah, P. Boyle
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引用次数: 2

Abstract

A team of researchers at the Air Force Research Laboratory in Rome, NY is building a remote test facility for developing a radio frequency (RF) tomography imaging capability. While at the test site and via batch reservations, they plan on employing the Army Research Laboratory Department of Defense Supercomputer Resource Center MJM distributed memory architecture system, while conducting operations at the test site. We present a scalability study of example RF tomography code, written in the M language of MATLAB and parallelized via Star-P, on the MJM system. The team can use the study to help guide operations while at the remote test facility. We are not attempting to show that the RF tomography code scales well; indeed, it suffers from communication bottlenecks in parts of the algorithms. Nonetheless, this is the code the team uses and, for planning purposes, the team needs to know how long it takes to produce images of a given size for a given number of processors with the existing algorithms.
基于MATLAB®编写并通过Star-P®并行化的射频断层扫描代码的DSRC HPC系统的可扩展性研究(作为远程测试设施的HPC操作指南)
位于纽约州罗马的空军研究实验室的一组研究人员正在为开发射频(RF)断层成像能力建造一个远程测试设施。在测试现场,通过批量预订,他们计划采用陆军研究实验室国防部超级计算机资源中心MJM分布式内存体系结构系统,同时在测试现场进行操作。本文以MATLAB的M语言编写并通过Star-P在MJM系统上并行化的示例射频层析成像代码进行了可扩展性研究。团队可以使用该研究来帮助指导远程测试设备的操作。我们并不是试图证明射频断层扫描码的可伸缩性好;事实上,它在部分算法中存在通信瓶颈。尽管如此,这是团队使用的代码,并且出于规划目的,团队需要知道使用现有算法为给定数量的处理器生成给定大小的图像需要多长时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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