Comparing Implementations of Near-Data Computing with In-Memory MapReduce Workloads

@article{Pugsley2014ComparingIO,
  title={Comparing Implementations of Near-Data Computing with In-Memory MapReduce Workloads},
  author={Seth H. Pugsley and Jeffrey Jestes and Rajeev Balasubramonian and Vijayalakshmi Srinivasan and Alper Buyuktosunoglu and Al Davis and Feifei Li},
  journal={IEEE Micro},
  year={2014},
  volume={34},
  pages={44-52}
}
The emergence of 3D stacking and the imminent release of Micron's Hybrid Memory Cube (HMC) device have made it more practical to move computation near memory. This work presents a detailed analysis of in-memory MapReduce in the context of near-data computing (NDC). MapReduce is a good fit for NDC because it is embarrassingly parallel and has highly localized memory accesses. This article considers two NDC architectures: one that exploits HMC devices and one that does not. It thus provides… CONTINUE READING
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