Affiliation:
1. Duke University, NC, USA
2. Google, Duke University, NC, USA
Abstract
Ensuring fairness in a system with scarce, preferred resources requires time sharing. We consider a heterogeneous system with a few “big” and many “small” processors. We allocate heterogeneous processors using a novel token mechanism, which frames the allocation problem as a repeated game. At each round, users request big processors and spend a token if their request is granted. We analyze the game and optimize users’ strategies to produce an equilibrium. In equilibrium, allocations balance performance and fairness. Our mechanism outperforms classical, fair mechanisms by 1.7×, on average, in performance gains, and is competitive with a performance maximizing mechanism.
Funder
Semiconductor Research Corporation program
MARCO and DARPA
STARnet
NSF
Publisher
Association for Computing Machinery (ACM)
Subject
Hardware and Architecture,Information Systems,Software
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