SC Conference - Activity Details

Characterizing and Predicting the I/O Performance of HPC Applications using a Parameterized Synthetic Benchmark

Hongzhang Shan  (Lawrence Berkeley National Laboratory)
John Shalf  (Lawrence Berkeley National Laboratory)
Katie Antypas  (Lawrence Berkeley National Laboratory)
Papers Session
I/O Performance
Thursday,  11:00AM - 11:30AM
Room Ballroom E
The unprecedented parallelism of new supercomputing platforms poses tremendous challenges to achieving scalable performance for I/O intensive applications. Performance assessments using traditional I/O system and component benchmarks are difficult to relate back to application I/O requirements. However, the complexity of full applications motivates development of simpler synthetic I/O benchmarks as proxies to the full application. In this paper we examine the I/O requirements of a range of HPC applications and describe how the LLNL IOR synthetic benchmark was chosen as suitable proxy for the diverse workload. We show a procedure for selecting IOR parameters to match the I/O patterns of the selected applications and show it can accurately predict the I/O performance of the full applications. We conclude that IOR is an effective replacement for full-application I/O benchmarks and can bridge the gap of understanding that typically exists between stand-alone benchmarks and the full applications they intend to model.
The full paper can be found in the IEEE Xplore Digital Library and ACM Digital Library
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