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UID:b5cfa63b-c4a2-429b-b7e4-57c6b288f4ba@support.access-ci.org
DTSTAMP:20250606T115722Z
DTSTART:20250918T180000Z
DTEND:20250918T193000Z
SUMMARY:COMPLECS: Data Transfer
DESCRIPTION:SummaryWhether analyzing experimental data collected from devic
 es in the field on a laptop or generating simulated data from large-scale 
 numerical calculations performed on high-performance computing (HPC) syste
 ms, 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 the
 re are many ways to transfer data between the data storage and the file sy
 stems you interact with. However, which transfer method is right for you w
 ill depend on the answers to a few key questions about the data: Where is 
 the data located? How is the data organized? How much data is there? And w
 here is the data going? In this first part of our series on Data Manageme
 nt, we introduce you to the essential concepts and command-line tools you 
 should learn when you first begin transferring data to and from HPC (or an
 y remote) systems regularly. You will learn how to check the integrity of 
 your data after a transfer has completed, how to utilize file compression,
  and how to choose the right data transfer tool for different situations. 
 We also introduce you to the common data storage and file systems your dat
 a may encounter, their advantages and limitations, and how their different
  characteristics may affect data transfer performance on one end or the ot
 her. Additional topics about data transfer will be covered as time permits
 .InstructorMarty Kandes is a Computational and Data Science Research Speci
 alist in the High-Performance Computing User Services Group at SDSC. He cu
 rrently helps manage user support for Comet — SDSC’s largest supercomp
 uter. Marty obtained his Ph.D. in Computational Science in 2015 from the C
 omputational Science Research Center at San Diego State University, where 
 his research focused on studying quantum systems in rotating frames of ref
 erence through the use of numerical simulation. He also holds an M.S. in P
 hysics from San Diego State University and a B.S. in Applied Mathematics a
 nd Physics from the University of Michigan, Ann Arbor. His current researc
 h interests include problems in Bayesian statistics, combinatorial optimiz
 ation, nonlinear dynamical systems, and numerical partial differential equ
 ations.See a full list of SDSC's upcoming training and events here.--- CO
 MPLECS (COMPrehensive Learning for end-users to Effectively utilize Cyberi
 nfraStructure) is a new SDSC program where training will cover non-program
 ming skills needed to effectively use supercomputers. Topics include paral
 lel computing concepts, Linux tools and bash scripting, security, batch co
 mputing, how to get help, data management and interactive computing. Each 
 session offers 1 hour of instruction followed by a 30-minute Q&A. COMPLECS
  is supported by NSF award 2320934.
URL:https://support.access-ci.org/events/8044
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