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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. The authors define the 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. Their methodology provides one 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.
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