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https://doi.org/10.1109/ipdps....
Article . 2007 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2023
Data sources: DBLP
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A Fault Tolerance Protocol with Fast Fault Recovery

Authors: Sayantan Chakravorty; Laxmikant V. Kalé;

A Fault Tolerance Protocol with Fast Fault Recovery

Abstract

Fault tolerance is an important issue for large machines with tens or hundreds of thousands of processors. Checkpoint-based methods, currently used on most machines, rollback all processors to previous checkpoints after a crash. This wastes a significant amount of computation as all processors have to redo all the computation from that checkpoint onwards. In addition, recovery time is bound by the time between the last checkpoint and the crash. Protocols based on message logging avoid the problem of rolling back all processors to their earlier state. However, the recovery time of existing message logging protocols is no smaller than the time between the last checkpoint and crash. We present a fault tolerance protocol, in this paper, that provides fast restarts by using the ideas of message logging and object-based processor virtualization. We evaluate our implementation of the protocol in the Charm++/adaptive MPI runtime system. We show that our protocol provides fast restarts and, for many applications, has low fault-free overhead.

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    popularity
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    Average
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
35
Average
Top 10%
Top 10%