SCHEDULE: NOV 10-16, 2012
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McrEngine - A Scalable Checkpointing System Using Data-Aware Aggregation and Compression
SESSION: Checkpointing
EVENT TYPE: Papers, Best Student Paper Finalists
TIME: 1:30PM - 2:00PM
SESSION CHAIR: Frank Mueller
AUTHOR(S):Tanzima Z. Islam, Kathryn Mohror, Saurabh Bagchi, Adam Moody, Bronis R. de Supinski, Rudolf Eigenmann
ROOM:255-EF
ABSTRACT:
High performance computing (HPC) systems use checkpoint and restart for tolerating 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 overloaded PFS resources. The high overheads force large-scale applications to reduce checkpoint frequency, which means more compute time is lost in the event of a failure.
To alleviate these problems, we demonstrate 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. Experimental results with large-scale application checkpoints show that mcrEngine reduces checkpointing overhead by up to 87% and recovery overhead by up to 62% over a baseline with no aggregation or compression.
Chair/Author Details:
Frank Mueller (Chair) - North Carolina State University
Tanzima Z. Islam - Purdue University
Kathryn Mohror - Lawrence Livermore National Laboratory
Saurabh Bagchi - Purdue University
Adam Moody - Lawrence Livermore National Laboratory
Bronis R. de Supinski - Lawrence Livermore National Laboratory
Rudolf Eigenmann - Purdue University
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McrEngine - A Scalable Checkpointing System Using Data-Aware Aggregation and Compression
SESSION: Checkpointing
EVENT TYPE: , Best Student Paper Finalists
TIME: 1:30PM - 2:00PM
SESSION CHAIR: Frank Mueller
AUTHOR(S):Tanzima Z. Islam, Kathryn Mohror, Saurabh Bagchi, Adam Moody, Bronis R. de Supinski, Rudolf Eigenmann
ROOM:255-EF
ABSTRACT:
High performance computing (HPC) systems use checkpoint and restart for tolerating 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 overloaded PFS resources. The high overheads force large-scale applications to reduce checkpoint frequency, which means more compute time is lost in the event of a failure.
To alleviate these problems, we demonstrate 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. Experimental results with large-scale application checkpoints show that mcrEngine reduces checkpointing overhead by up to 87% and recovery overhead by up to 62% over a baseline with no aggregation or compression.
Chair/Author Details:
Frank Mueller (Chair) - North Carolina State University
Tanzima Z. Islam - Purdue University
Kathryn Mohror - Lawrence Livermore National Laboratory
Saurabh Bagchi - Purdue University
Adam Moody - Lawrence Livermore National Laboratory
Bronis R. de Supinski - Lawrence Livermore National Laboratory
Rudolf Eigenmann - Purdue University
Click here to download .ics calendar file