Reflector: A fine-grained I/O tracker for HPC systems

Abdullah Al-Mamun, Jialin Liu, Tonglin Li, Quincey Koziol, Zhongyi Zhai, Junyan Qian, Haoting Shen, Dongfang Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present Reflector, to support both high-level and low-level I/O monitoring through user-defined interfaces such as HDF5 and NetCDF in addition to POSIX- and MPI-IO. We evaluate Reflector on both an on-premises 500-core HPC cluster and a leadership-class supercomputer at the Lawrence Berkeley National Laboratory. Preliminary results are promising as the system prototype incurs negligible performance overhead and clearly illustrates the I/O patterns and bottlenecks of multiple applications.

Original languageEnglish (US)
Title of host publicationPPoPP 2020 - Proceedings of the 2020 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
PublisherAssociation for Computing Machinery
Pages427-428
Number of pages2
ISBN (Electronic)9781450368186
DOIs
StatePublished - Feb 19 2020
Externally publishedYes
Event25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2020 - San Diego, United States
Duration: Feb 22 2020Feb 26 2020

Publication series

NameProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP

Conference

Conference25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2020
Country/TerritoryUnited States
CitySan Diego
Period2/22/202/26/20

ASJC Scopus subject areas

  • Software

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