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DTSTART;TZID=America/Denver:20231112T093500
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UID:submissions.supercomputing.org_SC23_sess419_ws_prot105@linklings.com
SUMMARY:Enabling Agile Analysis of I/O Performance Data with PyDarshan
DESCRIPTION:Jakob Luettgau (French Institute for Research in Computer Scie
 nce and Automation (INRIA)); Shane Snyder (Argonne National Laboratory (AN
 L)); Tyler Reddy and Nikolaus Awtrey (Los Alamos National Laboratory (LANL
 )); Kevin Harms (Argonne National Laboratory (ANL)); Jean Bez (Lawrence Be
 rkeley National Laboratory (LBNL)); and Rui Wang, Rob Latham, and Philip C
 arns (Argonne National Laboratory (ANL))\n\nModern scientific applications
  utilize numerous software and hardware layers to efficiently access data.
  This approach poses a challenge for I/O optimization because of the need 
 to instrument and correlate information across those layers. The Darshan c
 haracterization tool seeks to address this challenge by providing efficien
 t, transparent, and compact runtime instrumentation of many common I/O int
 erfaces. It also includes command-line tools to generate actionable insigh
 ts and summary reports.  However, the extreme diversity of today's scienti
 fic applications means that not all applications are well served by one-si
 ze-fits-all analysis tools.  \n\nIn this work, we present PyDarshan, a Pyt
 hon-based library that enables agile analysis of I/O performance data.  Py
 Darshan caters to both novice and advanced users by offering ready-to-use 
 HTML reports as well as a rich collection of APIs to facilitate custom ana
 lyses.  We present the design of PyDarshan and demonstrate its effectivene
 ss in four diverse real-world analysis use cases.\n\nTag: Performance Meas
 urement, Modeling, and Tools, Programming Frameworks and System Software\n
 \nRegistration Category: Workshop Reg Pass\n\nSession Chairs: David Boehme
  (Lawrence Livermore National Laboratory (LLNL)), Anthony Danalis (AMD), a
 nd Josef Weidendorfer (Dresden University of Technology)\n\n
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