Asilomar Conference on Signals, Signals, and Computers

Real-Time High-Throughput Sonar Beamforming Kernels Using Native Signal Processing and Memory Latency Hiding Techniques

Gregory E. Allen (1), Brian L. Evans (2), and Lizy K. John (2)

(1) Applied Research Laboratories, The University of Texas at Austin, P.O. Box 8029, Austin, TX 78713-8029 USA

(2) Department of Electrical and Computer Engineering, Engineering Science Building, The University of Texas at Austin, Austin, TX 78712-1084 USA


Software Release

Process Networks Research at UT Austin


We evaluate the use of native signal processing with loop unrolling and software prefetching to achieve high-performance digital signal processing on general-purpose processors. We apply these techniques to minimize the number of processors necessary for real-time implementation of a 3-D sonar beamformer. Because our beamforming kernels operate on high-throughput (~100 MB/s) input/output streams, memory latency hiding techniques are key for maximum performance. On the Sun UltraSPARC-II processor, we find speedups of 2.4 for hand loop unrolling, 1.46 for the Visual Instruction Set over floating-point arithmetic in C, and 1.33 for software prefetching.

The full paper is available in PDF format.

Slides for the lecture presentation

Greg Allen's Beamforming Web Page.

Last Updated 05/21/14.