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Comprehensive Measurement and Analysis of the User-Perceived I/O Performance in a Production Leadership-Class Storage System

Conference ·
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  1. ORNL
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With the increase of the scale and intensity of the parallel I/O workloads generated by those scientific applications running on high performance computing facilities, understanding the I/O dynamics, especially the root cause of the I/O performance variability and degradation in HPC environment, have become extremely critical to the HPC community. In this paper, we run extensive I/O measuring tests on a production leadership-class storage system to capture the performance variabilities of large-scale parallel I/O. Analyzing these results and its statistic correlation revealed some valuable insights into the characteristics of the storage system and the root cause of I/O performance variability. Further, we leverage these findings and propose an I/O middleware design refactoring which can improve the performance of the parallel I/O by optimizing the data striping and placement. Our preliminary evaluation results demonstrate the proposed approach can reduce the average per-process write latency by at least 80% and the maximum per-process write latency by at least 20%.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE; USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
DOE Contract Number:
AC05-00OR22725
OSTI ID:
1474694
Country of Publication:
United States
Language:
English

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