Abstract

We investigate the benefits that an energy-aware implementation of the runtime in charge of the concurrent execution of ILUPACK—a sophisticated preconditioned iterative solver for sparse linear systems—produces on the time-power-energy balance of the application. Furthermore, to connect the experimental results with the theory, we propose several simple yet accurate power models that capture the variations of average power that result from the introduction of the energy-aware strategies as well as the impact of the P-states into ILUPACK’s runtime, at high accuracy, on two distinct platforms based on multicore technology from AMD and Intel.

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