30 April 1992 Proteus: a reconfigurable computational network for computer vision
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The Proteus architecture is a highly parallel MIMD, multiple instruction, multiple-data machine, optimized for large granularity tasks such as machine vision and image processing The system can achieve 20 Giga-flops (80 Giga-flops peak). It accepts data via multiple serial links at a rate of up to 640 megabytes/second. The system employs a hierarchical reconfigurable interconnection network with the highest level being a circuit switched Enhanced Hypercube serial interconnection network for internal data transfers. The system is designed to use 256 to 1,024 RISC processors. The processors use one megabyte external Read/Write Allocating Caches for reduced multiprocessor contention. The system detects, locates, and replaces faulty subsystems using redundant hardware to facilitate fault tolerance. The parallelism is directly controllable through an advanced software system for partitioning, scheduling, and development. System software includes a translator for the INSIGHT language, a parallel debugger, low and high level simulators, and a message passing system for all control needs. Image processing application software includes a variety of point operators neighborhood, operators, convolution, and the mathematical morphology operations of binary and gray scale dilation, erosion, opening, and closing.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert M. Haralick, Arun K. Somani, Craig M. Wittenbrink, Robert Johnson, Kenneth Cooper, Linda G. Shapiro, Ihsin T. Phillips, Jenq Neng Hwang, William Cheung, Yung Hsi Yao, Chung-Ho Chen, Larry Yang, Brian Daugherty, Bob Lorbeski, Kent Loving, Tom Miller, Larye Parkins, Steven L. Soos, "Proteus: a reconfigurable computational network for computer vision", Proc. SPIE 1659, Image Processing and Interchange: Implementation and Systems, (30 April 1992); doi: 10.1117/12.58396; https://doi.org/10.1117/12.58396


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