Grouped Distributed Queues: Distributed Queue, Proportional Share Multiprocessor Scheduling

Bogdan Caprita, Jason Nieh, Clifford Stein

Department of Computer Science, Columbia University Technical Report , CUCS-004-06, February 2006

Abstract

We present Grouped Distributed Queues (GDQ ), the first proportional share scheduler for multiprocessor systems that, by using a distributed queue architecture, scales well with a large number of processors and processes. GDQ achieves accurate proportional fairness scheduling with only O(1) scheduling overhead. GDQ takes a novel approach to distributed queuing: instead of creating per-processor queues that need to be constantly balanced to achieve any measure of proportional sharing fairness, GDQ uses a simple group- ing strategy to organize processes into groups based on similar processor time allocation rights, and then assigns processors to groups based on aggregate group shares. Group membership of processes is static, and fairness is achieved by dynamically migrating processors among groups. The set of processors work- ing on a group use simple, low-overhead round-robin queues, while processor reallocation among groups is achieved using a new multiprocessor adaptation of the well-known Weighted Fair Queuing (WFQ ) algorithm. By commoditizing processors and decoupling their allocation from process scheduling, GDQ provides, with only constant scheduling cost, fairness within a constant of the ideal generalized processor sharing model for process weights with a fixed upper bound. We have implemented GDQ in Linux and measured its performance. Our experimental results show that GDQ has low overhead and scales well with the number of processors.

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Columbia University Department of Computer Science