Difference between revisions of "CSC352 Class Page 2010"
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===Literature=== | ===Literature=== | ||
| + | * [[Image:hadoopOReilly.jpg | right |100px]] [http://www.amazon.com/Hadoop-Definitive-Guide-Tom-White/dp/0596521979 Hadoop, the definitive guide], Tim White, O'Reilly Media, June 2009, ISBN 0596521979 | ||
* Dean, J., and S. Ghemawat, [http://labs.google.com/papers/mapreduce-osdi04.pdf MapReduce: Simplified Data Processing on Large Clusters], Dec. 2004, ([[media:MapReduce1204.pdf|cached copy]]) | * Dean, J., and S. Ghemawat, [http://labs.google.com/papers/mapreduce-osdi04.pdf MapReduce: Simplified Data Processing on Large Clusters], Dec. 2004, ([[media:MapReduce1204.pdf|cached copy]]) | ||
* Czajkowski G., [http://googleblog.blogspot.com/2008/11/sorting-1pb-with-mapreduce.html Sorting 1 PB with MapReduce], Nov. 2008, ([[media:Sorting1PBWithMapReduce.pdf|cached copy]]) | * Czajkowski G., [http://googleblog.blogspot.com/2008/11/sorting-1pb-with-mapreduce.html Sorting 1 PB with MapReduce], Nov. 2008, ([[media:Sorting1PBWithMapReduce.pdf|cached copy]]) | ||
* Armbrust M, ''et al'', [http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdf Above the Clouds: A Berkeley View of Cloud Computing], Tech Rep. CB/EECS-2009-28, Feb. 2009 ([[media:AboveTheCloudsBerkeley.pdf|cached copy]]) | * Armbrust M, ''et al'', [http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdf Above the Clouds: A Berkeley View of Cloud Computing], Tech Rep. CB/EECS-2009-28, Feb. 2009 ([[media:AboveTheCloudsBerkeley.pdf|cached copy]]) | ||
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===Class Material=== | ===Class Material=== | ||
* [http://code.google.com/edu/submissions/uwspr2007_clustercourse/listing.html University of Washington: Problem Solving on Large Scale Clusters]: | * [http://code.google.com/edu/submissions/uwspr2007_clustercourse/listing.html University of Washington: Problem Solving on Large Scale Clusters]: | ||
Revision as of 11:12, 3 December 2009
Contents
Python Threads
XGrid Programming
Cloud Computing
References & Bibliography
Parallel Processing/Good background information
- Asanovic K. et al, The Landscape of Parallel Computing Research: A View from Berkeley, Dec. 2006. (cached copy)
- Mauer, R., Xen Virtualization and Linux Clustering, Linux Journal January 12th, 2006
- Barham P., et al., Xen and the Art of Virtualization, University of Cambridge Computer Laboratory 15 JJ Thomson Avenue, Cambridge, UK, CB3 0FD
- AMD News
- Hardwidge, B., AMD plans supercomputer with 1,000 GPUs, Jan. 2009, bit-tech.net (or graphics goes to the clouds!)
- Halfacree G., AMD supercomputer tops TOP500 list, November 2009, bit-tech.net (or Intel gets a black eye!)
Python
- Norman Matloff and Francis Hsu's Tutorial on Python Threads (University of California, Davis) (cached copy)
- Understanding Threading in Python, Krishna G Pai, Linux Gazette, Oct. 2004
- Thread Objects from Python.Org
XGrid
Cloud Computing
Literature
- Hadoop, the definitive guide, Tim White, O'Reilly Media, June 2009, ISBN 0596521979
- Dean, J., and S. Ghemawat, MapReduce: Simplified Data Processing on Large Clusters, Dec. 2004, (cached copy)
- Czajkowski G., Sorting 1 PB with MapReduce, Nov. 2008, (cached copy)
- Armbrust M, et al, Above the Clouds: A Berkeley View of Cloud Computing, Tech Rep. CB/EECS-2009-28, Feb. 2009 (cached copy)
Class Material
- The University of Washington ran an upper-division course on Distributed Computing with MapReduce in Spring 2007. Below you'll find the materials that were used for the class: five lectures in powerpoint format, as well as four lab exercises designed which were completed by students over the duration of the course, using a cluster running Hadoop.
Software/Web Links
- The Hadoop Wiki, the authoritative source on working with Hadoop
- Hadoop at Google:
- Setting up a Hadoop cluster can be an all day job. However, if you want to experiment with the platform right now, [Google] has created a virtual machine image with a preconfigured single node instance of Hadoop
- Guide for setting up IBM's Eclipse Tools for Hadoop (go to bottom of page)
- The IBM MapReduce Tools for Eclipse Plug-in is a robust plug-in that brings Hadoop support to the Eclipse platform. Features include server configuration, support for launching MapReduce jobs and browsing the distributed file system. This setup assumes that you are running Eclipse (version 3.3 or above) on your computer.
- A video from Cloudera on setting up Hadoop... not easy to follow...
