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Title: McrEngine: A Scalable Checkpointing System Using Data-Aware Aggregation and Compression

High performance computing (HPC) systems use checkpoint-restart to tolerate failures. Typically, applications store their states in checkpoints on a parallel file system (PFS). As applications scale up, checkpoint-restart incurs high overheads due to contention for PFS resources. The high overheads force large-scale applications to reduce checkpoint frequency, which means more compute time is lost in the event of failure. We alleviate this problem through a scalable checkpoint-restart system, mcrEngine. McrEngine aggregates checkpoints from multiple application processes with knowledge of the data semantics available through widely-used I/O libraries, e.g., HDF5 and netCDF, and compresses them. Our novel scheme improves compressibility of checkpoints up to 115% over simple concatenation and compression. Our evaluation with large-scale application checkpoints show that mcrEngine reduces checkpointing overhead by up to 87% and restart overhead by up to 62% over a baseline with no aggregation or compression.
Authors:
 [1] ;  [2] ;  [1] ;  [2] ;  [2] ;  [1]
  1. School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA
  2. Lawrence Livermore National Laboratory, Livermore, CA, USA
Publication Date:
OSTI Identifier:
1197891
Grant/Contract Number:
AC52-07NA27344
Type:
Published Article
Journal Name:
Scientific Programming
Additional Journal Information:
Journal Volume: 21; Journal Issue: 3-4; Related Information: CHORUS Timestamp: 2016-08-23 03:56:50; Journal ID: ISSN 1058-9244
Publisher:
Hindawi Publishing Corporation
Sponsoring Org:
USDOE
Country of Publication:
Egypt
Language:
English