Probabilistic job symbiosis modeling for SMT processor scheduling

Symbiotic job scheduling boosts simultaneous multithreading (SMT) processor performance by co-scheduling jobs that have ‘compatible’ demands on the processor’s shared resources. Existing approaches however require a sampling phase, evaluate a limited number of possible co-schedules, use heuristics to gauge symbiosis, are rigid in their optimization target, and do not preserve systemlevel priorities/shares. This paper proposes probabilistic job symbiosis modeling, which predicts whether jobs will create positive or negative symbiosis when co-scheduled without requiring the co-schedule to be evaluated. The model, which uses per-thread cycle stacks computed through a previously proposed cycle accounting architecture, is simple enough to be used in system software. Probabilistic job symbiosis modeling provides six key innovations over prior work in symbiotic job scheduling: (i) it does not require a sampling phase, (ii) it readjusts the job co-schedule continuously, (iii) it evaluat...

• Type: Conference
• Year: 2010
• Where: ASPLOS
• Authors: Stijn Eyerman, Lieven Eeckhout
• Keywords: ASPLOS 2010, Job Symbiosis Modeling, Probabilistic Job Symbiosis, Programming Languages, Symbiotic Job Scheduling