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UID:f8617fe4-049f-4c5d-8cf6-f53074ad5dbb@support.access-ci.org
DTSTAMP:20250102T133249Z
DTSTART:20250306T190000Z
DTEND:20250306T203000Z
SUMMARY:COMPLECS: Data Transfer
DESCRIPTION:Whether analyzing experimental data collected from devices in t
 he field on a laptop or generating simulated data from large-scale numeric
 al calculations performed on high-performance computing (HPC) systems, how
  you move your data to where you need it, when you need it, is one of the 
 most important aspects of creating your research workflows. And there are 
 many ways to transfer data between the data storage and file systems you i
 nteract with. But which transfer method is right for you will depend on th
 e answers to a few key questions about the data, namely: Where is the data
  located? How is the data organized? How much data is there? And where is 
 the data going?In this first part of our series on Data Management, we int
 roduce you to the essential concepts and command-line tools you should lea
 rn when you first begin transferring data to and from HPC (or any remote) 
 systems regularly. You will learn how to check the integrity of your data 
 after a transfer has been completed, how to utilize file compression, and 
 how to choose the right data transfer tool for different situations. We al
 so introduce you to the common data storage and file systems your data may
  encounter, their advantages and limitations, and how their different char
 acteristics may affect data transfer performance on one end or the other. 
 Additional topics about data transfer will be covered as time permits.Inst
 ructorMarty Kandes is a Computational and Data Science Research Specialist
  in the High-Performance Computing User Services Group at SDSC. He current
 ly helps manage user support for Comet — SDSC’s largest supercomputer.
  Marty obtained his Ph.D. in Computational Science in 2015 from the Comput
 ational Science Research Center at San Diego State University, where his r
 esearch focused on studying quantum systems in rotating frames of referenc
 e through the use of numerical simulation. He also holds an M.S. in Physic
 s from San Diego State University and B.S. degrees in both Applied Mathema
 tics and Physics from the University of Michigan, Ann Arbor. His current r
 esearch interests include problems in Bayesian statistics, combinatorial o
 ptimization, nonlinear dynamical systems, and numerical partial differenti
 al equations.See a full list of SDSC's upcoming training and events here.C
 OMPLECS (COMPrehensive Learning for end-users to Effectively utilize Cyber
 infraStructure) is a new SDSC program where training will cover non-progra
 mming skills needed to effectively use supercomputers. Topics include para
 llel computing concepts, Linux tools and bash scripting, security, batch c
 omputing, how to get help, data management and interactive computing. Each
  session offers 1 hour of instruction followed by a 30-minute Q&A. COMPLEC
 S is supported by NSF award 2320934.
URL:https://support.access-ci.org/events/7720
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