REF: Resource elasticity fairness with sharing incentives for multiprocessors
With the democratization of cloud and datacenter computing, users increasingly share large hardware platforms. In this setting, architects encounter two challenges: sharing fairly and sharing multiple resources. Drawing on economic game-theory, we rethink fairness in computer architecture. A fair allocation must provide sharing incentives (SI), envy-freeness (EF), and Pareto efficiency (PE). We show that Cobb-Douglas utility functions are well suited to modeling user preferences for cache capacity and memory bandwidth. And we present an allocation mechanism that uses Cobb-Douglas preferences to determine each user's fair share of the hardware. This mechanism provably guarantees SI, EF, and PE, as well as strategy-proofness in the large (SPL). And it does so with modest performance penalties, less than 10% throughput loss, relative to an unfair mechanism. Copyright © 2014 ACM.
International Conference on Architectural Support for Programming Languages and Operating Systems Asplos
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