Isotonic additive models in workload characterization

Details Isotonic additive models in workload characterization Isotonic additive models in workload characterization

2006-08-22

2006-08-22

Jones, Hugh (Department: 2128)

Data processing: structural design, modeling, simulation, and em

Simulating electronic device or electrical system

Software program

Reexamination Certificate

active

07096178

ABSTRACT:
A method for modeling a system configuration, including isotonizing an unconstrained additive model of a cache architecture to obtain an isotonic additive model for the cache architecture, wherein the isotonic additive model is of the same functional form as the unconstrained additive model, smoothing the isotonic additive model using a flat spot technique to obtain a characterization of the cache architecture, and modeling a system configuration using the characterization of the cache architecture.

REFERENCES:
Dykstra et al. “An Algorithm for Isotonic Regression for Two or More Independent Variables”.
Thiebaut et al. “Improving Disk Cache Hit-Ratios Though Cache Partitioning”.
“Modeling Under Order Restrictions” G. Salanti, K. Ulm. Technical University of Munich. Dec. 3, 2001.
“Applied Nonparametric Regression” Chapter 8.1, “Monotonic and Unimodal Smoothing”, Wolfgang Herdle, Andrew Chester. 1992.
“Measurement and Analysis of Workload Effects on Fault Latency in Real Time Systems”, Woodbury et al. Feb. 1990. IEEE. pp. 212-216.
Peter Bacchetti; “Additive Isotonic Models;” Journal of the American Statistical Association, Mar. 1989, pp. 289-294; vol. 84, No. 405; Theory and Methods.
Richard L. Dykstra and Tim Robertson; “An Algorithm For Isotonic Regression For Two Or More Independent Variables;” pp. 708-716; 1982, vol. 10, No. 3, The Annuals of Statistics, Department of Statistics and Actuarial Science, University of Iowa, Iowa City, IA, USA.

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