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Quickrelease Fair Scheduling # James H. Anderson, Aaron Block, and Anand Srinivasan
 

Summary: Quick­release Fair Scheduling #
James H. Anderson, Aaron Block, and Anand Srinivasan
Department of Computer Science
University of North Carolina at Chapel Hill
Abstract
In prior work on multiprocessor fairness, e#cient techniques with provable properties for reallocating spare
processing capacity have been elusive. In this paper, we address this shortcoming by proposing a new notion of
multiprocessor fairness, called quick­release fair (QRfair) scheduling, which is a derivative of Pfair scheduling
that allows e#cient allocation of spare capacity. Under QRfair scheduling, each task is specified by giving
both a minimum and a maximum weight (i.e., processor share). The goal is to schedule each task (as the
available spare capacity changes) at a rate that is (i) at least that implied by its minimum weight and (ii) at
most that implied by its maximum weight. Our contributions are fourfold. First, we present a quick­release
variant of the PD 2 Pfair scheduling algorithm called PD Q . Second, we formally prove that the allocations
of PD Q always satisfy (i) and (ii). Third, we consider the problem of defining maximum weights in a way
that encourages a fair distribution of spare capacity. Fourth, we present results from extensive simulation
experiments that show the e#cacy of PD Q in allocating spare capacity.
Keywords: Dynamic systems, fair scheduling, multiprocessors, Pfairness, work­conserving scheduling.
# Work supported by NSF grants CCR 9972211, CCR 9988327, ITR 0082866, and CCR 0204312.

1 Introduction

  

Source: Anderson, James - Department of Computer Science, University of North Carolina at Chapel Hill

 

Collections: Computer Technologies and Information Sciences