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T. Hoefler, D. Moor:

 Energy, Memory, and Runtime Tradeoffs for Implementing Collective Communication Operations

(Journal of Supercomputing Frontiers and Innovations. Vol 1, Nr. 2, pages 58--75, SuperFri Open Journal, Oct. 2014)


Collective operations are among the most important communication operations in shared- and distributed-memory parallel applications. In this paper, we analyze the tradeoffs between energy, mem- ory, and runtime of different algorithms that implement such operations. We show that existing algo- rithms have varying behavior and that no known algorithm is optimal in all three regards. We also demonstrate examples where of three different algorithms solving the same problem, each algorithm is best in a different metric. We conclude by posing the challenge to explore the resulting tradeoffs in a more structured manner.


download article:


  author={T. Hoefler and D. Moor},
  title={{Energy, Memory, and Runtime Tradeoffs for Implementing Collective Communication Operations}},
  journal={Journal of Supercomputing Frontiers and Innovations},
  publisher={SuperFri Open Journal},

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