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DTSTAMP:20260629T151657Z
UID:a38ee368-794f-47a9-a197-76dbc8d7aabb
DTSTART:20160314T093000Z
DTEND:20160315T173000Z
DESCRIPTION:Whether you're undertaking very data-intensive HPC computations
  or working with large files that need to be transferred on or off a remot
 e supercomputer\, a good understanding of data management best practices w
 ill help you to make the most of available resources.\n\nDetails\n\nThis c
 ourse covers best practice for data management using the UK's National Sup
 ercomputer service\, ARCHER\, and its associated RDF data archive and Data
  Analytics Cluster as specific examples.\n\nDay 1 will cover best practice
 s for working with your files on ARCHER. It will describe ARCHER's local f
 ile systems and the relationship between ARCHER and the Research Data Faci
 lity\, the associated system for long-term archiving. It will introduce to
 ols such as GridFTP for moving large amounts of data on and off ARCHER and
  the RDF. We will also cover how to do data analysis and visualisation on 
 the Data Analytics Cluster attached to the RDF.\n\nDay 2 will introduce fi
 le formats that have associated libraries for high-performance IO (such as
  HDF5 and NetCDF). We then cover ways to achieve good IO performance on pa
 rallel systems using these formats and the lower-level MPI-IO library. We 
 conclude with general advice on how to develop practical data management p
 lans for your own research that are useful and address the requirements of
  research funding bodies.\n\nThis course is free to all academics.\n\nPre-
 requisites\n\nAttendees are expected to have experience of using desktop c
 omputers\, but no programming\, Linux or HPC experience is necessary.\n\nh
 ttps://events.prace-ri.eu/event/482/
SUMMARY:Data Storage and Management @ EPCC
URL;VALUE=URI:https://events.prace-ri.eu/event/482/
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