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VERSION:2.0
PRODID:icalendar-ruby
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DTSTAMP:20260622T105753Z
UID:44e3c583-9b81-4705-8f1b-f9e25a8ecd4c
DTSTART:20130529T090000Z
DTEND:20130530T173000Z
DESCRIPTION:Course description: The course aims to give a general overview 
 of the SPRINT package for performing large-scale statistical analysis in p
 arallel. SPRINT provides an easy access mechanism to high performance comp
 uting for the analysis of high throughput post genomic data using the stat
 istical programming language R. The course will cover the basics of the R 
 programming language\, then move on to explain how to benefit from the par
 allel features of SPRINT.Learning outcome: Ability to use the R language i
 n parallel for large-scale statistical analysis\; An understanding of whic
 h R functions can benefit from parallelisation.Pre-requisites: Programming
  ability in any high-level language. Understanding of statistics.Timetable
 Day 1\, 29 May 2013\n09:30 An introduction to High Performance Computing C
 oncepts\n10:30 An introduction to HECToR architecture\n11:00 COFFEE\n11:30
  Running a job on HECToR (An Imaging Processing Example)\n12:15 An introdu
 ction and overview of the SPRINT project\n13:00 LUNCH\n14:00 Running a SPR
 INT job on HECToR\n14:30 Description of existing SPRINT functionality\n15:
 15 Doing the SPRINT tutorial on HECToR\n15:30 COFFEE\n16:00 Doing the SPRI
 NT tutorial on HECToR (continued)\n16:30 Installing SPRINT on your own Lin
 ux/Mac laptop\n17:30 CLOSE Day 2\, 30 May 2013\n09:30 Completion of SPRIN
 T tutorial on HECToR or own machine and attendees experimenting with SPRIN
 T\n10:30 How to Interact with the SPRINT team\n11:00 COFFEE\n11:30 SPRINT 
 case-study (“Time-shifted correlation patterns in interferon gamma activ
 ated macrophages”)\n12:30 LUNCH\n13:30 Workshop/hands-on session on:\n 
     - Hands-on help with Linux/ OSX laptop installations\n     - 
 Sprint team available to discuss new use-cases/functionality\, user reques
 ts and potential collaborations.\n 15:00 CLOSE\n \n\nhttps://events.prac
 e-ri.eu/event/149/
SUMMARY:Statistical Analysis for Post-Genomic Data: Parallel Computing with
  R @ EPCC
URL;VALUE=URI:https://events.prace-ri.eu/event/149/
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