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Multi-Processor Look-Ahead Scheduling PDF

83 Pages·2016·1.54 MB·English
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Master’s Thesis Multi-Processor Look-Ahead Scheduling Hannes Weisbach February 3, 2016 Technische Universität Dresden Fakultät Informatik Institut für Systemarchitektur Professur Betriebssysteme Betreuender Hochschullehrer: Prof. Dr. rer. nat. Hermann Härtig Betreuender Mitarbeiter: Dr.-Ing. Michael Roitzsch Task Atlas, developed at the Operating Systems Chair, is an infrastructure to assign CPU time. Central goal of Atlas is to simplify development of real-time applications by relieving the programmer of the burden of providing period and execution time. Currently, the implementation of Atlas in the Linux operating sys- tem only supports uni-processor operation. The goal of this thesis is to add multi-processor support to the existing implementation. The scientific question of this thesis lies in the design and imple- mentation of a user space/kernel space interface for multi-processor Atlas. The programming paradigm of Atlas and the goal of us- ability should be maintained and, if necessary, extended with suitable primitives to support parallel execution. The evaluation should include a comparison of Atlas with an exist- ing Linux multi-processor scheduler, as well as determine the cost of a scheduling decision and the corresponding overhead for applications. Selbstständigkeitserklärung I hereby declare, that I have authored this thesis independently, mak- ing use only of the specified aids. Hiermit erkläre ich, dass ich diese Arbeit selbstständig erstellt und keine anderen als die angegebenen Hilfsmittel benutzt habe. Dresden, den 3. Februar 2016 Hannes Weisbach To my parents, Andrea and Udo Weisbach. Contents Background 13 Atlas on Uni-Processor Systems 29 Atlas on Multi-Processor Systems 41 Evaluation 55 Conclusion & Future Work 69 Bibliography 77

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The programming paradigm of Atlas and the goal of us- Page 6 Windows®, Apple® Mac OS®, Linux®, iOS®, and Android™ have .. √2 − 1 ≈ 0.41 for global static priority-driven scheduling algorithms.25 Another approach to schedule a task set on a multi-processor . 39 John Carpenter et al.
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