Tools for Analyzing Parallel I/O

Parallel application I/O performance often does not meet user expectations. Additionally, slight access pattern modifications may lead to significant changes in performance due to complex interactions between hardware and software. These issues call for sophisticated tools to capture, analyze, understand, and tune application I/O.

[1]  L. Berkeley Deploying Server-side File System Monitoring at NERSC , 2009 .

[2]  Joseph K. Bradley,et al.  Spark SQL: Relational Data Processing in Spark , 2015, SIGMOD Conference.

[3]  Stephen A. Jarvis,et al.  Parallel File System Analysis Through Application I/O Tracing , 2013, Comput. J..

[4]  Julian M. Kunkel,et al.  The SIOX Architecture - Coupling Automatic Monitoring and Optimization of Parallel I/O , 2014, ISC.

[5]  Ethan L. Miller,et al.  Usage behavior of a large-scale scientific archive , 2012, 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.

[6]  Andreas J. Peters,et al.  EOS as the present and future solution for data storage at CERN , 2015 .

[7]  Robert Latham,et al.  Understanding and improving computational science storage access through continuous characterization , 2011, MSST.

[8]  Bo Hong,et al.  File System Workload Analysis For Large Scientific Computing Applications , 2004, MSST.

[9]  Carsten Karbach,et al.  A highly configurable and efficient simulator for job schedulers on supercomputers , 2013 .

[10]  Karthik Vijayakumar,et al.  Scalable I/O tracing and analysis , 2009, PDSW '09.

[11]  Thomas Ludwig,et al.  Analysis of the MPI-IO Optimization Levels with the PIOViz Jumpshot Enhancement , 2007, PVM/MPI.

[12]  Michael Wagner,et al.  Open Trace Format 2: The Next Generation of Scalable Trace Formats and Support Libraries , 2011, PARCO.

[13]  Surendra Byna,et al.  Boosting Application-Specific Parallel I/O Optimization Using IOSIG , 2012, 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012).

[14]  Dirk Schmidl,et al.  Score-P: A Joint Performance Measurement Run-Time Infrastructure for Periscope, Scalasca, TAU, and Vampir , 2011, Parallel Tools Workshop.

[15]  Wolfgang Frings,et al.  Scalable Control and Monitoring of Supercomputer Applications Using an Integrated Tool Framework , 2011, 2011 40th International Conference on Parallel Processing Workshops.

[16]  Emilio Luque,et al.  Modeling Parallel Scientific Applications through their Input/Output Phases , 2012, 2012 IEEE International Conference on Cluster Computing Workshops.

[17]  Emilio Luque,et al.  Analyzing the Parallel I/O Severity of MPI Applications , 2017, 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID).

[18]  Julian M. Kunkel,et al.  Real-Time I/O-Monitoring of HPC Applications with SIOX, Elasticsearch, Grafana and FUSE , 2017, ISC Workshops.

[19]  Emilio Luque Fadón,et al.  A new approach for analyzing I/O in parallel scienti , 2012 .

[20]  Andreas J. Peters,et al.  Exabyte Scale Storage at CERN , 2011 .

[21]  Ethan L. Miller,et al.  Analysis of Workload Behavior in Scientific and Historical Long-Term Data Repositories , 2012, TOS.

[22]  Kevin Harms,et al.  UMAMI: a recipe for generating meaningful metrics through holistic I/O performance analysis , 2017, PDSW-DISCS@SC.

[23]  Robert Latham,et al.  24/7 Characterization of petascale I/O workloads , 2009, 2009 IEEE International Conference on Cluster Computing and Workshops.

[24]  Aleksandar Jemcov,et al.  OpenFOAM: A C++ Library for Complex Physics Simulations , 2007 .

[25]  Ming Zhang,et al.  Understanding data center traffic characteristics , 2010, CCRV.

[26]  Allen D. Malony,et al.  Instrumentation and Measurement Strategies for Flexible and Portable Empirical Performance Evaluation , 2001 .

[27]  Kevin Harms,et al.  TOKIO on ClusterStor: Connecting Standard Tools to Enable Holistic I/O Performance Analysis , 2018 .

[28]  André Brinkmann,et al.  Analysis of the ECMWF Storage Landscape , 2015, FAST.

[29]  Emilio Luque,et al.  PIOM-PX: A Framework for Modeling the I/O Behavior of Parallel Scientific Applications , 2017, ISC Workshops.