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GPU performance comparison for accelerated radar data processing

Chris Fallen, Beau Bellamy, Greg Newby, Brent Watkins
Arctic Region Supercomputing Center
Symposium on Application Accelerators in High-Performance Computing (SAAHPC), 2011

@inproceedings{fallen2011gpu,

   title={GPU performance comparison for accelerated radar data processing},

   author={Fallen, CT and Bellamy, BVC and Newby, GB and Watkins, BJ},

   booktitle={Application Accelerators in High-Performance Computing (SAAHPC), 2011 Symposium on},

   pages={84–92},

   organization={IEEE}

}

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Radar is a data-intensive measurement technique often requiring significant processing to make full use of the received signal. However, computing capacity is limited at remote or mobile radar installations thereby limiting radar data products used for real-time decisions. We used graphics processing units (GPUs) to accelerate processing of high resolution phase-coded radar data from the Modular UHF Ionosphere Radar (MUIR) at the High-frequency Active Auroral Research Program (HAARP) facility in Gakona, Alaska. Previously, this data could not be processed on-site in sufficient time to be useful for decisions made during active experiment campaigns, nor could the data be uploaded for off-site processing to high-performance computing (HPC) resources at the Arctic Region Supercomputing Center (ARSC) in Fairbanks. In this paper, we present a radar data-processing performance comparison of a workstation equipped with dual NVIDIA GeForce GTX 480 GPU accelerator cards and a node from ARSC’s PACMAN cluster equipped with dual NVIDIA Tesla M2050 cards. Both platforms meet performance requirements, are relatively inexpensive and could operate effectively at remote observatories such as HAARP.
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