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  1. Proceedings of the 2nd international workshop on Petascale data storage (PDSW '07)
  2. Towards an I/O tracing framework taxonomy
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On application-level approaches to avoiding TCP throughput collapse in cluster-based storage systems
Searching and navigating petabyte-scale file systems based on facets
A result-data offloading service for HPC centers
pNFS/PVFS2 over InfiniBand: early experiences
GIGA+: scalable directories for shared file systems
Characterizing the I/O behavior of scientific applications on the Cray XT
Integrated system models for reliable petascale storage systems
End-to-end performance management for scalable distributed storage
Towards an I/O tracing framework taxonomy
Scalable locking and recovery for network file systems
RADOS: a scalable, reliable storage service for petabyte-scale storage clusters
A data placement service for petascale applications

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Towards an I/O tracing framework taxonomy

Content Provider ACM Digital Library
Author Nunez, James Quist, Meghan Konwinski, Andy Bent, John
Abstract There is high demand for I/O tracing in High Performance Computing (HPC). It enables in-depth analysis of distributed applications and file system performance tuning. It also aids distributed application debugging. Finally, it facilitates collaboration within and between government, industrial, and academic institutions by enabling the generation of replayable I/O traces, which can be easily distributed and anonymized as necessary to protect confidential or sensitive information. As a response to this demand for tracing tools, various means of I/O trace generation exist. We first survey the I/O Tracing Framework landscape, exploring three popular such frameworks: LANL-Trace [3], Tracefs [1], and//TRACE [2]. We next develop an I/O Tracing Framework taxonomy. The purpose of this taxonomy is to assist I/O Tracing Framework users in formalizing their tracing requirements, and to provide the developers of I/O Tracing Frameworks a language to categorize the functionality and performance of them. The taxonomy categorizes I/O Tracing Framework features such as the type of data captured, trace replayability, and anonymization. The taxonomy also considers elapsed-time overhead and performance overhead. Finally, we provide a case study in the use of our new taxonomy, revisiting all three I/O Tracing Frameworks explored in our survey, to formally classify the features of each.
Starting Page 56
Ending Page 62
Page Count 7
File Format PDF
ISBN 9781595938992
DOI 10.1145/1374596.1374610
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2007-11-11
Publisher Place New York
Access Restriction Subscribed
Subject Keyword File systems Parallel Tracing
Content Type Text
Resource Type Article
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