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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Concurrent Telemetry Processing Techniques

Clark, Jerry 10 1900 (has links)
International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / Improved processing techniques, particularly with respect to parallel computing, are the underlying focus in computer science, engineering, and industry today. Semiconductor technology is fast approaching device physical limitations. Further advances in computing performance in the near future will be realized by improved problem-solving approaches. An important issue in parallel processing is how to effectively utilize parallel computers. It is estimated that many modern supercomputers and parallel processors deliver only ten percent or less of their peak performance potential in a variety of applications. Yet, high performance is precisely why engineers build complex parallel machines. Cumulative performance losses occur due to mismatches between applications, software, and hardware. For instance, a communication system's network bandwidth may not correspond to the central processor speed or to module memory. Similarly, as Internet bandwidth is consumed by modern multimedia applications, network interconnection is becoming a major concern. Bottlenecks in a distributed environment are caused by network interconnections and can be minimized by intelligently assigning processing tasks to processing elements (PEs). Processing speeds are improved when architectures are customized for a given algorithm. Parallel processing techniques have been ineffective in most practical systems. The coupling of algorithms to architectures has generally been problematic and inefficient. Specific architectures have evolved to address the prospective processing improvements promised by parallel processing. Real performance gains will be realized when sequential algorithms are efficiently mapped to parallel architectures. Transforming sequential algorithms to parallel representations utilizing linear dependence vector mapping and subsequently configuring the interconnection network of a systolic array will be discussed in this paper as one possible approach for improved algorithm/architecture symbiosis.

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