Power modeling of embedded memories

This thesis describes a methodology for the generation of models of the power consumption of embedded memories. Memories have a special importance among the system blocks as it is forecast that more than 90% of the area of newly developed systems will be occupied by memory within ten years. In addition to the requirements on models, like accuracy, speed and mathematically closed form the presented approach specifically adresses the requirements on the modeling procedure. These are mainly the protection of intellectual property and low modeling costs. As a key point of the approach a method for the generation of nonlinear (signomial) models from empirical data is presented. This regression based method allows the generation of piecewise model functions, which can be used for optimisation through geometric programs. The presented models reduce the prediction error by up to 95% compared to existing approaches.

Level thesis:degree_level

thesis.doctoral

Grantor dc:publisher

Universität Oldenburg

Year

2003

Author dc:creator

• Schmidt, Eike

• [Keine Schlagwörter von Autor/in vergeben.]

Repository record source_url

http://oops.uni-oldenburg.de/250

OAI identifier oai:identifier

oai:oops.uni-oldenburg.de:250