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Optimizing rapidIO architectures for onboard processing

Optimizing rapidIO architectures for onboard processing In this article, we study optimization of a RapidIO network and FPGA-based computation engines to address the taxing requirements of a set of real-time Ground-Moving Target Indicators (GMTI) and Synthetic Aperture Radar (SAR) kernels for Space-Based Radar (SBR). By employing a RapidIO hardware testbed and validated simulation, we determine key trade-offs in design of reconfigurable systems for GMTI and SAR in terms of processing, memory, and network throughput. In addition, we study considerations for timely delivery of latency-sensitive control traffic present in many satellite applications. Based on our results, we propose architectural modifications to further improve performance of SBR systems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Embedded Computing Systems (TECS) Association for Computing Machinery

Optimizing rapidIO architectures for onboard processing

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References (30)

Publisher
Association for Computing Machinery
Copyright
The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc.
Subject
Signal processing systems
ISSN
1539-9087
DOI
10.1145/1698772.1698776
Publisher site
See Article on Publisher Site

Abstract

In this article, we study optimization of a RapidIO network and FPGA-based computation engines to address the taxing requirements of a set of real-time Ground-Moving Target Indicators (GMTI) and Synthetic Aperture Radar (SAR) kernels for Space-Based Radar (SBR). By employing a RapidIO hardware testbed and validated simulation, we determine key trade-offs in design of reconfigurable systems for GMTI and SAR in terms of processing, memory, and network throughput. In addition, we study considerations for timely delivery of latency-sensitive control traffic present in many satellite applications. Based on our results, we propose architectural modifications to further improve performance of SBR systems.

Journal

ACM Transactions on Embedded Computing Systems (TECS)Association for Computing Machinery

Published: Feb 1, 2010

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