An energy complexity model for algorithms
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
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For a given algorithm, the energy consumed in executing the algorithm has a nonlinear relationship with performance. In case of parallel algorithms, energy use and performance are functions of the structure of the algorithm. We define the \emph{asymptotic energy complexity} of algorithms which models the minimum energy required to execute a parallel algorithm for a given execution time as a function of input size. Our methodology provides us with a way of comparing the orders of (minimal) energy required for different algorithms and can be used to define energy complexity classes of parallel algorithms.