A Framework for Real-Time High-Throughput Signal and Image Processing on Workstations

Mr. Gregory Allen
UT Austin

Monday, August 9th, 10:00 AM, ENS 302

allen@ece.utexas.edu

Abstract

Real-time data-intensive systems such as sonar beamformers and synthetic aperture radar processors have traditionally required implementation in expensive custom hardware. Current systems use off-the-shelf programmable processors in customized configurations to reduce development cost. To reduce development cost and time further, we consider the use of workstations as the target architecture and design environment. We present a general approach for realizing real-time data-intensive systems in software on a multiprocessor workstation.

First, we present several dataflow models which are commonly used to describe signal processing systems. Second, we present a framework for developing scalable software implementations of signal processing systems on workstations. The framework models the concurrency and parallelism in these systems using Process Networks. The Process Networks model guarantees determinate execution of concurrent programs regardless of the scheduling algorithm being used. We employ a scheduling algorithm that always finds a bounded execution if one exists. Third, we implement the framework in C++ using lightweight real-time POSIX threads.

We use two case studies to evaluate the performance of our framework: a high-resolution 3-D sonar beamformer and a synthetic aperture radar processor. On a Sun Ultra Enterprise workstation, the 4-GFLOP beamformer exhibits near-linear speedup using 1 to 12 processors and executes in real time with 12 336-MHz UltraSPARC-II processors.

A list of Telecommunications and Signal Processing Seminars is available at from the ECE department Web pages under "Seminars". The Web address for the Telecommunications and Signal Processing Seminars is http://anchovy.ece.utexas.edu/seminars