Scalably Scheduling Power-Heterogeneous Processors
Anupam Gupta, Ravishankar Krishnaswamy, Kirk Pruhs
TL;DR
This paper demonstrates that a straightforward online scheduling algorithm effectively manages power-heterogeneous processors to optimize weighted flow and energy consumption, ensuring scalability in complex systems.
Contribution
It introduces and analyzes a natural online algorithm that is scalable for scheduling on heterogeneous processors with arbitrary power functions.
Findings
The algorithm achieves scalability for weighted flow plus energy.
It handles arbitrary power functions in heterogeneous multiprocessors.
Provides theoretical guarantees for online scheduling performance.
Abstract
We show that a natural online algorithm for scheduling jobs on a heterogeneous multiprocessor, with arbitrary power functions, is scalable for the objective function of weighted flow plus energy.
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