System Maintenance:
There may be intermittent impact on performance while updates are in progress. We apologize for the inconvenience.
By Topic

Diagnosing arbitrarily connected parallel computers with high probability

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Rangarajan, S. ; UMIACS, Maryland Univ., College Park, MD, USA ; Fussell, D.

A practical model for probabilistic fault diagnosis is presented. Unlike PMC-based models, the model allows testers to conduct multiple tests on the same processor. This allows the design of efficient probabilistic diagnosis algorithms with good asymptotic behavior, with minimal constraints on the connection structure of the multiprocessor system, in contrast to other deterministic and probabilistic approaches. In practical cases, the number of immediate neighbors of any processor need be no greater than two, which implies that the algorithm can be applied to any practical homogeneous parallel architecture. It is also shown how to make efficient use of tests by allowing the number of testing processors, and the number of tests performed by a processor to be traded off in achieving asymptotically accurate diagnosis

Published in:

Computers, IEEE Transactions on  (Volume:41 ,  Issue: 5 )