ABSTRACT

Proceedings of the 5th USENIX Conference on File and Storage Technologies (FAST '07), February 13–16, 2007, San Jose, CA. Supercedes Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-06-108, September 2006.

//TRACE: Parallel Trace Replay with Approximate Causal Events

Michael Mesnier, Matthew Wachs, Raja R. Sambasivan, Julio Lopez, James Hendricks, Gregory R. Ganger

Department of Electrical and Computer Engineering
Carnegie Mellon University
Pittsburgh, PA 15213

http://www.pdl.cmu.edu/

//TRACE (pronounced parallel trace) is a new approach for extracting and replaying traces of parallel applications to recreate their I/O behavior. Its tracing engine automatically discovers inter-node data dependencies and inter-I/O compute times for each node (process) in an application. This information is reflected in per-node annotated I/O traces. Such annotation allows a parallel replayer to closely mimic the behavior of a traced application across a variety of storage systems. When compared to other replay mechanisms, //TRACE offers significant gains in replay accuracy. Overall, the average replay error for the parallel applications evaluated in this paper is below 6%.

KEYWORDS: I/O, I/O dependencies, parallel applications, storage benchmarking, throttling, trace replay

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