[PDF][PDF] Scheduling constrained dynamic applications on clusters
Proceedings of the 1999 ACM/IEEE conference on Supercomputing, 1999•dl.acm.org
There is an emerging class of computationally demanding multimedia applications involving
vision, speech and interaction with the real world (eg, CRL's Smart Kiosk). These
applications are highly parallel and require low latencies for good performance. They are
well-suited for implementation on clusters of SMP's, but they require efficient scheduling of
application tasks. General purpose schedulers produce high latencies because they lack
knowledge of the dependencies between tasks. Previous research in optimal scheduling …
vision, speech and interaction with the real world (eg, CRL's Smart Kiosk). These
applications are highly parallel and require low latencies for good performance. They are
well-suited for implementation on clusters of SMP's, but they require efficient scheduling of
application tasks. General purpose schedulers produce high latencies because they lack
knowledge of the dependencies between tasks. Previous research in optimal scheduling …
Abstract
There is an emerging class of computationally demanding multimedia applications involving vision, speech and interaction with the real world (eg, CRL’s Smart Kiosk). These applications are highly parallel and require low latencies for good performance. They are well-suited for implementation on clusters of SMP’s, but they require efficient scheduling of application tasks. General purpose schedulers produce high latencies because they lack knowledge of the dependencies between tasks. Previous research in optimal scheduling has been limited to static problems. In contrast, our application is highly dynamic as the optimal schedule depends upon the behavior of the kiosk’s customers. We observe that the dynamism of our application class is constrained, in that there are a small number of operating regimes which are determined by the state of the application. We present a framework for optimal scheduling of constrained dynamic applications. The results of an experimental comparison with a hand-tuned schedule are promising.
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