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Goal

To port a shared-memory implementation of MapReduce to the StarSs programming model.

Description

MapReduce was originally created by Google in order to support distributed computing on clusters of computers.

A Stanford University researchers team implemented MapReduce for shared-memory systems in a project named "Phoenix" (http://mapreduce.stanford.edu/), and published a paper regarding it in the 2007 Symposium on High Performance Computer Architecture (HPCA). Phoenix contains a programming API that requires implementation of 3-5 functions by the programmer (the implementation of the desired application), and contains a runtime environment which runs theses functions and handles parallelization and concurrency automatically. By that, Phoenix is an easy and stable parallel programing tool.

StarSs is a parallel programming model based on DataFlow programming.

Our goal is to port the implementation of Phoenix and/or other libraries which followed Phenix and were inspired by it, to the StarSs programming model while reserving the performance of the library.

Table of Contents

  1. Bibliography
  2. Install ompss environment how-to
  3. quickstart guide
  4. A rolling todo.
  5. ...

Previous Welcome note. (For editing purposes.)

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