2199 research outputs found
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Workforce Development, Grant ceremony, 2001
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/17068/86764-thumbnail.jpg$1 Million grant ceremony</p
Workforce Development, Grant ceremony, 2001
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/17069/86765-thumbnail.jpg$1 million grant ceremony</p
Timings for Associative Operations on the MASC Model
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/17399/87325-thumbnail.jpgThe MASC (Multiple Associative Computing) model is a generalized associative-style computational model that naturally supports massive data-parallelism and also control-parallelism. A wide range of applications has been developed on this model. Recent research has compared its power to the power of other popular parallel models such as the PRAM and MMB models using simulations. However, the simulation of MMB has identified some important issues regarding the cost of certain basic MASC operations required for associative computing such as broadcasts, reductions, and associative searches. This paper investigates these issues and gives background information and an analysis of timings for these operations, based on implementation techniques and comparison fairness with respect to other models. It aims to provide justification and clarify arguments on the timings for these constant-time or nearly constant-time basic MASC operations.</p
TechKNOW Volume 7, Issue 2
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/techknow/27/thumbnail.jp
The Burr Spring 2001
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/theburr/30/thumbnail.jp
TechKNOW Volume 7, Issue 1
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/techknow/26/thumbnail.jp
The Burr Fall 2001
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/theburr/31/thumbnail.jp
Canto 2001
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/18336/88347-thumbnail.jpgCo-Editors: Melanie Cattrell and Carolyn Adelman
Art Editor: Chad Kessler
Assistant Art Editor: Alison Miltner
Faculty Advisor: Jayne A. Moneysmith
Art Department Faculty Advisor: Jack McWhorter
Desktop Publishing: Allison Farnsworth
Professional Photography: Donald Selby</p
Predictability for Real-Time Command and Control
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/16804/87479-thumbnail.jpgThis paper describes a new and different paradigm for real-time command and control that we show can provide a static, polynomial-time scheduling algorithm. Current efforts in real-time scheduling have been unable to predict system performance, and use a unpredictable "dynamic" scheduling algorithm. The Nation’s Air Traffic Control (ATC) System has been unable to satisfy performance requirements, and is extremely expensive. An editorial in "USA Today" (4-19-1999) cites expenditures in ATC at $41 billion. But, current multiprocessor technology cannot do the job.
The FAA wisely required a “proof of concept” study before the (AAS) contract. But that study, after expending a billion dollars, was abandoned, and production moved forward. AAS was canceled in 1995 exactly in line with real-time scheduling theory predictions. Garey, Graham, and Johnson state: "For these scheduling problems, no efficient optimization algorithm has yet been found, and indeed, none is expected.”[9]. Stankovic et. al. state: "… complexity results show most real-time multiprocessing scheduling is NP-hard.” [6]. We offer a completely different approach, that has been shown to overcome the severe limitations of multiprocessing. Additionally, we show that real-time parallel-processing techniques can be statically scheduled to solve the set of tasks making up the ATC problem for a worst-case environment. </p
TechKNOW Volume 7, Issue 4
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/techknow/29/thumbnail.jp