Persistent Link:
http://hdl.handle.net/10150/611423
Title:
Concurrent Telemetry Processing Techniques
Author:
Clark, Jerry
Affiliation:
Lockheed Martin Telemetry & Instrumentation
Issue Date:
1996-10
Rights:
Copyright © International Foundation for Telemetering
Collection Information:
Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
Publisher:
International Foundation for Telemetering
Journal:
International Telemetering Conference Proceedings
Abstract:
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.
Keywords:
Parallel Computing; Processing Elements (PEs); Efficiently Mapped; Dependence; Vector; Systolic Array
Sponsors:
International Foundation for Telemetering
ISSN:
0884-5123; 0074-9079
Additional Links:
http://www.telemetry.org/

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleConcurrent Telemetry Processing Techniquesen_US
dc.contributor.authorClark, Jerryen
dc.contributor.departmentLockheed Martin Telemetry & Instrumentationen
dc.date.issued1996-10-
dc.rightsCopyright © International Foundation for Telemeteringen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
dc.publisherInternational Foundation for Telemeteringen
dc.description.abstractImproved 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.en
dc.subjectParallel Computingen
dc.subjectProcessing Elements (PEs)en
dc.subjectEfficiently Mappeden
dc.subjectDependenceen
dc.subjectVectoren
dc.subjectSystolic Arrayen
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.identifier.issn0884-5123-
dc.identifier.issn0074-9079-
dc.identifier.urihttp://hdl.handle.net/10150/611423-
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.typetexten
dc.typeProceedingsen
dc.relation.urlhttp://www.telemetry.org/en
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