Optimal rate-based scheduling on multiprocessors
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Fast scheduling of periodic tasks on multiple resources
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
A proportional share resource allocation algorithm for real-time, time-shared systems
RTSS '96 Proceedings of the 17th IEEE Real-Time Systems Symposium
Elastic Task Model for Adaptive Rate Control
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Mixed Pfair/ERfair Scheduling of Asynchronous Periodic Tasks
ECRTS '01 Proceedings of the 13th Euromicro Conference on Real-Time Systems
RTAS '01 Proceedings of the Seventh Real-Time Technology and Applications Symposium (RTAS '01)
FUNDAMENTAL DESIGN PROBLEMS OF DISTRIBUTED SYSTEMS FOR THE HARD-REAL-TIME ENVIRONMENT
FUNDAMENTAL DESIGN PROBLEMS OF DISTRIBUTED SYSTEMS FOR THE HARD-REAL-TIME ENVIRONMENT
Surplus fair scheduling: a proportional-share CPU scheduling algorithm for symmetric multiprocessors
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Euromicro-RTS'00 Proceedings of the 12th Euromicro conference on Real-time systems
Real Time Scheduling Theory: A Historical Perspective
Real-Time Systems
Task Reweighting on Multiprocessors: Efficiency versus Accuracy
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 2 - Volume 03
Locking under Pfair scheduling
ACM Transactions on Computer Systems (TOCS)
Optimal rate-based scheduling on multiprocessors
Journal of Computer and System Sciences
Memory performance attacks: denial of memory service in multi-core systems
SS'07 Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium
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In prior work on multiprocessor fairness, ef拢cient techniqueswith provable properties for reallocating spare processingcapacity have been elusive. In this paper, weaddress this shortcoming by proposing a new notion ofmultiprocessor fairness, called quick-release fair (QRfairscheduling. Under QRfair scheduling, each task is speci拢ed by giving both a minimum and a maximum weight (i.e., processor share. The goal is to schedule each task (as thespare capacity changes at a rate that is (i) at least that impliedby its minimum weight and (ii) at most that implied byits maximum weight. We present a quick-release variant ofthe PD2 Pfair scheduling algorithm called PDQ and provethat the allocations of PDQ always satisfy (i and (ii . Also,we present results from simulation experiments that showthe ef拢cacy of PDQ.