The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Oct. 05, 2004
Filed:
Jun. 02, 2000
Steven Hurlock, Wynnewood, PA (US);
Unisys Corporation, Blue Bell, PA (US);
Abstract
A code evaluation algorithm is used to determine optimal cache parameters. In evaluating the code, the algorithm uses a set of code characteristics the presence of which, or the degree of presence of which, impact the proper selection of cache parameters. Once the code characteristics have been selected, the algorithm uses boolean truth state tables or fuzzy logic membership set definitions to specify whether and when each code characteristic is true or false (i.e., present or absent) for a given set of code instructions. Programs are classified as having the following characteristics: 1) arithmetic intensive; 2) logic/decision intensive; 3) reference intensive; and/or 4) array/vector/table processing. To evaluate the code, the degree of presence or absence of these characteristics is described in logical fashion, using fuzzy logic. To logically evaluate and relate such “fuzzy” concepts, the algorithm uses fuzzy logic membership functions to determine the degree to which there exist a small number, medium number or large number of instances of a particular class of operator in the code analyzed. Next, the algorithm defines a fuzzy logic rule base which relates (e.g., by implication) the presence or absence (i.e., truth or falsehood) of the condition impacting proper selection of cache parameters to conclusions regarding the selection of cache parameters. The algorithm then determines (evaluates) the conclusions regarding the proper selection of cache parameters by evaluating the conditions impacting the conclusions while applying the rule base rules. In particular, the algorithm uses the “Mandani Product” inference engine for computational simplicity. The center of gravity of the fuzzy outcomes is computed and the result is discretized yielding a crisp, meaningful result representing an optimal cache parameter choice.