A Map-Reduce Based Framework for Heterogeneous Processing Element Cluster Environments

@article{Tan2012AMB,
  title={A Map-Reduce Based Framework for Heterogeneous Processing Element Cluster Environments},
  author={Yu Shyang Tan and Bu-Sung Lee and Beixin Julie He and Roy H. Campbell},
  journal={2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)},
  year={2012},
  pages={57-64}
}
In this paper, we present our design of a Processing Element (PE) Aware MapReduce base framework, Pamar. Pamar is designed for supporting distributed computing on clusters where node PE configurations are asymmetric on different nodes. Pamar's main goal is to allow users to seamlessly utilize different kinds of processing elements (e.g., CPUs or GPUs) collaboratively for large scale data processing. To show proof of concept, we have incorporated our designs into the Hadoop framework and tested… CONTINUE READING

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