@inproceedings{eb470d60ca7e41009ec8dccbe2dd570c,
title = "Recorder 2.0: Efficient parallel I/O tracing and analysis",
abstract = "Recorder is a multi-level I/O tracing tool that captures HDF5, MPI-I/O, and POSIX I/O calls. In this paper, we present a new version of Recorder that adds support for most metadata POSIX calls such as stat, link, and rename. We also introduce a compressed tracing format to reduce trace file size and run time overhead incurred from collecting the trace data. Moreover, we add a set of post-mortem and visualization routines to our new version of Recorder that manage the compressed trace data for users. Our experiments with four HPC applications show a file size reduction of over 2× and reduced post-processing time by 20% when using our new compressed trace file format.",
keywords = "Compressed I/O Traces, MPI-I/O, Parallel I/O",
author = "Chen Wang and Jinghan Sun and Marc Snir and Kathryn Mohror and Elsa Gonsiorowski",
note = "Funding Information: Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 (LLNL-CONF-802986). Funding Information: This research was partly supported by NSF SHF award 1763540 and was performed under the auspices of the U.S. Publisher Copyright: {\textcopyright} 2020 IEEE.; 34th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 ; Conference date: 18-05-2020 Through 22-05-2020",
year = "2020",
month = may,
doi = "10.1109/IPDPSW50202.2020.00176",
language = "English (US)",
series = "Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1052--1059",
booktitle = "Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020",
address = "United States",
}