A Comparison of Trace Compression Methods for Massively Parallel Applications in Context of the SIOX Project

Alvaro Aguilera (), Holger Mickler, Julian Kunkel, Michaela Zimmer, Marc Wiedemann and Ralph Müller-Pfefferkorn
Additional contact information
Alvaro Aguilera: Technische Universität Dresden
Holger Mickler: Technische Universität Dresden
Julian Kunkel: Deutsches Klimarechenzentrum
Michaela Zimmer: Universität Hamburg
Marc Wiedemann: Universität Hamburg
Ralph Müller-Pfefferkorn: Technische Universität Dresden

Chapter Chapter 8 in Tools for High Performance Computing 2013, 2014, pp 91-105 from Springer

Abstract: Abstract The analysis and optimization of HPC I/O is a daunting task that is still unaddressed at large. The SIOX project aims to help HPC users and system administrators alike to improve the I/O performance of the applications by gaining awareness of the I/O operations taking place on the system and launching corrective measures when a problem is encountered. Given the size of modern HPC clusters and the corresponding amount of I/O they generate, the SIOX project faces a series of scalability challenges that need to be resolved. Beyond presenting the architecture and functioning of the SIOX system, this paper examines one of its biggest challenges, namely the transmission and management of large amount of event-based I/O trace information as well as the benefits the use of the trace compression techniques like ScalaTrace and C3G may convey.

Keywords: Compression Ratio; High Performance Computing; Function Call; Parallel Application; Trace Data (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-08144-1_8

Ordering information: This item can be ordered from
http://www.springer.com/9783319081441

DOI: 10.1007/978-3-319-08144-1_8

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().