The communication challenge for MPP: Intel Paragon and Meiko CS-2
Parallel Computing
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IEEE Parallel & Distributed Technology: Systems & Technology
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PDP '12 Proceedings of the 2012 20th Euromicro International Conference on Parallel, Distributed and Network-based Processing
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ACM SIGMETRICS Performance Evaluation Review
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With energy costs now accounting for nearly 30 % of a datacenter's operating expenses, energy consumption has become an important issue when designing and executing a parallel algorithm. This paper analyzes the energy consumption of MPI applications following the master---slave paradigm. The analytical model is derived for this paradigm and is validated over a master---slave matrix-multiplication. This analytical model is parameterized through architectural and algorithmic parameters, and it is capable of predicting the energy consumption for a given instance of the problem over a given architecture. We use an external, metered, power distribution unit that allows to easily measure the power consumption of computing nodes without the needing of dedicated hardware.