SCHEDULE: NOV 16-22, 2013
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CSinParallel: Using Map-Reduce to Teach Data-Intensive Scalable Computing Across the CS Curriculum
SESSION: CSinParallel: Using Map-Reduce to Teach Data-Intensive Scalable Computing Across the CS Curriculum
EVENT TYPE: HPC Interconnections, HPC Educator Program
TIME: 1:30PM - 5:00PM
SESSION CHAIR: Thomas Hacker
Presenter(s):Richard A. Brown, Elizabeth Shoop, Joel C. Adams
ROOM:702/704/706
ABSTRACT:
Map-reduce, the cornerstone computational framework for cloud computing applications, has star appeal to draw students to the study of parallelism. Participants will carry out hands-on exercises designed for students at CS1/intermediate/advanced levels that introduce data-intensive scalable computing concepts, using WebMapReduce (WMR), a simplified open-source interface to the widely used Hadoop map-reduce programming environment, and using Hadoop itself. These hands-on exercises enable students to perform data-intensive scalable computations carried out on the most widely deployed map-reduce framework, used by Facebook, Microsoft, Yahoo, and other companies. WMR supports programming in a choice of languages (including Java, Python, C++, C#, Scheme); participants will be able to try exercises with languages of their choice. Workshop includes brief introduction to direct Hadoop programming, and information about access to cluster resources supporting WMR. Workshop materials will reside on csinparallel.org, along with WMR software. Intended audience: CS instructors. Laptop required (Windows, Mac, or Linux).
Chair/Presenter Details:
Thomas Hacker (Chair) - Purdue University
Richard A. Brown - St. Olaf College
Elizabeth Shoop - Macalester College
Joel C. Adams - Calvin College
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