Proc. Asilomar Conference Signal, Systems and Computers,
Nov. 7-10, 2010,
Pacific Grove, CA USA.
Multi-core Sonar Beamforming with Computational Process Networks
John F. Bridgman,
Gregory E. Allen
Brian L. Evans
Electrical and Computer Engineering,
The University of Texas at Austin,
Austin, TX 78712 USA
Process Networks Research
at UT Austin
This paper evaluates the scalability with respect to processor cores
of a three-dimensional sonar beamforming kernel implemented on a
Beamforming is an example of an extremely parallelizable problem.
This implementation is instrumented with OpenMP to exploit multi-core
However, when executed on a 16-core machine, this kernel scales much
less than expected.
We implement this beamformer system within the scalable framework of
Computational Process Networks to achieve additional performance and
processor utilization for a larger number of cores.
On our benchmark machine, the implementation with Computational Process
Networks obtains a throughput speedup of more than two times over
OpenMP with the default settings, and 13% improvement in throughput
over OpenMP with optimized settings.
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