Title
Hybrid Message Pessimistic Logging. Improving current pessimistic message logging protocols.
Abstract
With the growing scale of HPC applications, there has been an increase in the number of interruptions as a consequence of hardware failures. The remarkable decrease of Mean Time Between Failures (MTBF) in current systems encourages the research of suitable fault tolerance solutions. Message logging combined with uncoordinated checkpoint compose a scalable rollback-recovery solution. However, message logging techniques are usually responsible for most of the overhead during failure-free executions. Taking this into consideration, this paper proposes the Hybrid Message Pessimistic Logging (HMPL) which focuses on combining the fast recovery feature of pessimistic receiver-based message logging with the low failure-free overhead introduced by pessimistic sender-based message logging. The HMPL manages messages using a distributed controller and storage to avoid harming systems scalability. Experiments show that the HMPL is able to reduce overhead by 34% during failure-free executions and 20% in faulty executions when compared with a pessimistic receiver-based message logging. A low overhead Hybrid Message Pessimistic Logging (HMPL) protocol is presented.The HMPL focus on providing fast recovery with low failure-free overhead.A temporal buffer in senders is used to reduce penalties in critical paths.A detailed comparison of the HMPL with a classic receiver-based logging is presented.Overhead reductions up to 34% in failure-free and 20% in faulty executions.
Year
DOI
Venue
2017
10.1016/j.jpdc.2017.02.003
J. Parallel Distrib. Comput.
Keywords
Field
DocType
Fault tolerance,Availability,Scalability,Performance,MPI,Message logging
Mean time between failures,Control theory,Message logging,Computer science,Parallel computing,Communication source,Fault tolerance,Scalability,Logging,Distributed computing
Journal
Volume
Issue
ISSN
104
C
0743-7315
Citations 
PageRank 
References 
1
0.35
16
Authors
5
Name
Order
Citations
PageRank
Hugo Meyer1143.08
Ronal Muresano2113.56
Marcela Castro-León310.69
Dolores Rexachs419543.20
Emilio Luque51097176.18