Proceedings of Phoenix Conference on Computers and Communications
DOI: 10.1109/pccc.1993.344462
|View full text |Cite
|
Sign up to set email alerts
|

An object-oriented approach for implementing algorithm-based fault tolerance

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
5
0

Publication Types

Select...
2
1
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(5 citation statements)
references
References 12 publications
0
5
0
Order By: Relevance
“…Prata et al compared ABFT with result checking based on error coverage, overhead and ease of use [8]. In [2], ABFT for detection only was compared to detection and correction in terms of error coverage, memory size and execution time.…”
Section: Previous Workmentioning
confidence: 99%
See 3 more Smart Citations
“…Prata et al compared ABFT with result checking based on error coverage, overhead and ease of use [8]. In [2], ABFT for detection only was compared to detection and correction in terms of error coverage, memory size and execution time.…”
Section: Previous Workmentioning
confidence: 99%
“…The manifestation was that one or more elements of the resultant matrix could be erroneous. The ABFT experiments performed in [2] used FERRARI to emulate transient bit flips at execution time within the address space of a program. In [12], the fault model used was a bit flip in a data entry during the execution.…”
Section: Fault Injectionmentioning
confidence: 99%
See 2 more Smart Citations
“…Algorithm based fault tolerance (ABFT), proposed by Huang and Abraham (1984), is a fault tolerance scheme that uses Concurrent Error Detection (techniques at a functional level). System level applications of ABFT techniques have also been investigated (Acree, Ullah, Karia, Rahmeh, & Abraham, 1993;Banerjee, Rahmeh, Stunkel, Nair, Roy, & Abraham, 1990). These techniques assume a general fault model which allows any single module in the system to be faulty (Huang & Abraham, 1984).…”
Section: Introductionmentioning
confidence: 99%