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ricardo a baratto coms e6118 spring 2004 n.
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Surplus Fair Scheduling PowerPoint Presentation
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Surplus Fair Scheduling

Surplus Fair Scheduling

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Surplus Fair Scheduling

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  1. Ricardo A. Baratto COMS E6118 – Spring 2004 Surplus Fair Scheduling

  2. Proportional-Share CPU Scheduling for Symmetric Multiprocessors

  3. What? Why? • Fair resource allocation • Proportional to application's share • WFQ [Demers et al.], [Parekh et al.], Stride [Waldspurger et al.] • SFQ [Goyal et al.] • SMART [Nieh et al.]

  4. The Problem • Unfeasible Weight Assignment: Starvation • Upper Bound on Assignment • Frequent Arrival – Departures: Unfairness • Burst Behavior

  5. Surplus Fair Scheduling • Weight Readjustment • Generalized Multiprocessor Sharing(Surplus Approximation)

  6. Weight Readjustment • Readjust threads violating feasibility constraint: • Optimal: • Number of threads • Weight change • Efficient • O(p)

  7. GMS and Surplus Approximation • Generalization of GPS [Parekh et al.] • φi: Readjusted weight • Ai(t1, t2): CPU service received • Si: Weighted CPU service = Si + q/φi • αi = Ai(0, t) - AiGMS(0, t)≈ (φi . Si) - (φi . v)

  8. SFS Algorithm • update Fi and compute Si • compute v: min(Si) • compute αi • schedule ti with min(αi) • If {t} changes: readjust weights

  9. Implementation and Complexity • Three ordered queues: • w: Weight readjustment • S: Virtual time • α: Next to schedule • Add thread: Insert + Readjust = O(t+p) • Delete thread: Delete + Readjust = O(p) • Schedule: Update surplus + Sort = O(t log t) [~ every p schedules]

  10. Evaluation: Weight Readjustment

  11. Evaluation: Short Jobs

  12. Evaluation: Application Isolation