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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�
By: Abdullah, A.H.; Srivastava, N.; Magde, K.M.; Chalker, A.; Ahalt, S.; Boyle, P.; Guilfoos, B.; Humphrey, L.; Smith, H.B.; Samsi, S.; Elton, B.H.;
2009 / IEEE / 978-1-4244-5769-4
This item was taken from the IEEE Conference ' 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� ' 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.
High Performance Computing
Remote Test Facility
Signal Processing Algorithms
Distributed Memory Architecture System
Department Of Defense Supercomputer Resource Center
Radiofrequency Tomography Imaging
Air Force Research Laboratory
Distributed Memory Systems
Rf Tomography Code