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

Journal Article · Tue Jan 01 00:00:00 EST 2013 · Scientific Programming

DOI:https://doi.org/10.1155/2013/341672· OSTI ID:1197891

Islam, Tanzima Zerin ^[1]; Mohror, Kathryn ^[2]; Bagchi, Saurabh ^[1]; Moody, Adam ^[2]; de Supinski, Bronis R. ^[2]; Eigenmann, Rudolf ^[1]

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1. School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA
2. Lawrence Livermore National Laboratory, Livermore, CA, USA

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.

• Sponsoring Organization: USDOE
• Grant/Contract Number: AC52-07NA27344
• OSTI ID: 1197891
• Journal Information: Scientific Programming, Journal Name: Scientific Programming Vol. 21 Journal Issue: 3-4; ISSN 1058-9244
• Publisher: Hindawi Publishing Corporation
• Country of Publication: Egypt
• Language: English