MapReduce is a simple and flexible parallel programming model proposed by Google for large scale data processing in a distributed computing environment. We have developed a design and implementation of MapReduce for the Cell processor architecture.
The runtime is available for public download here. The package includes an application suite that demonstrates usage of the runtime. Applications include a word count application, distributed sort, the kmeans clustering algorithm, and several other applications.
If you use this work in your own work, or develop on top of this work, we would appreciate you letting us know. If you want to cite MapReduce for Cell in your research writings, please refer to the paper “MapReduce for the Cell B.E. Architecture.” by M. de Kruijf and K. Sankaralingam, University of Wisconsin Computer Sciences Technical Report CS-TR-2007-1625, October 2007.