Pith. sign in

REVIEW

Recomputation Enabled Efficient Checkpointing

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1710.04685 v2 pith:BZFKI355 submitted 2017-09-18 cs.DC

Recomputation Enabled Efficient Checkpointing

classification cs.DC
keywords checkpointingoverheadenergyerrorreducestatedataefficient
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Systematic checkpointing of the machine state makes restart of execution from a safe state possible upon detection of an error. The time and energy overhead of checkpointing, however, grows with the frequency of checkpointing. Amortizing this overhead becomes especially challenging, considering the growth of expected error rates, as checkpointing frequency tends to increase with increasing error rates. Based on the observation that due to imbalanced technology scaling, recomputing a data value can be more energy efficient than retrieving (i.e., loading) a stored copy, this paper explores how recomputation of data values (which otherwise would be read from a checkpoint from memory or secondary storage) can reduce the machine state to be checkpointed, and thereby reduce the checkpointing overhead. Specifically, the resulting amnesic checkpointing framework AmnesiCHK can reduce the storage overhead by up to 23.91%; time overhead, by 11.92%; and energy overhead, by 12.53%, respectively, even in a relatively small scale system.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.