Method for tuning state-based scheduling policies

Details Method for tuning state-based scheduling policies Method for tuning state-based scheduling policies

2007-11-06

2007-11-06

Vincent, David (Department: 2129)

Data processing: artificial intelligence

Knowledge processing system

Knowledge representation and reasoning technique

C718S104000, C718S105000

Reexamination Certificate

active

11045562

ABSTRACT:
One embodiment of the present invention provides a system that tunes state-based scheduling policies, wherein the system contains a number of central processing units (CPUs). During operation, the system recurrently estimates a long-term benefit to the system by feeding a system state as input to a parametric value function and computing an output from the parametric value function. The system makes scheduling decisions for the CPUs based on the estimated long-term benefit to the system. The system also tunes a parameter of the parametric value function based on current and previously estimated long-term benefit to the system, thereby facilitating more effective scheduling policies.

REFERENCES:
patent: 2002/0198854 (2002-12-01), Berenji et al.
A. T. Wong, L. Oliker, W. T. C. Kramer, T. L. Kaltz and D.H.Bailey, “System Utilization Benchmark on the Cray T3E and IBM SP”, 6thWorkshop on Job Scheduling Strategies for Parallel Processing, Apr. 2000 electronic copy can be found at http://citeseer.ist.psu.edu/298440.html.
Zomaya, A.Y. Clements, M. Olariu, S. “A framework for reinforcement-based scheduling in parallel processor systems” IEEE Transactions on Parallel and Distributed Systems, Mar. 1998 vol. 9, Issue. 3, pp. 249-260.
David Vengerov, Hamid R. Berenji, Alex Vengerov (“Emergent Coordination Among Fuzzy Reinforcement Learning Agents” 2002 A book chapter in Soft Computing Agents: A New Perspective for Dynamic Information Systems, International Series “Frontiers in Artificial Intelligence and Application” by IOS Press. Editor: V. Loia. ).
Stephen F. Smith and Dhirah K. Pathak (“Balancing Antagonistic Time and Resource Utilization Constraints in over-subscribed scheduling problems” IEEE 1992).

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