CSC352 Class Page 2010

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

Cloud Computing

Literature

• 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

• University of Washington: Problem Solving on Large Scale Clusters:

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

• 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