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University of Illinois at Urbana-Champaign
Compiling Fast Partial Derivatives of Functions Given by Algorithms
Abstract
dc:descriptionIf the gradient of the function y = f(x(,1),...,x(,n)) is desired where f is given by an algorithm Af(x,n,y), most numerical analysts will use numerical differencing. This is a sampling scheme that approximates derivatives by the slope of secants in closely spaced points. Symbolic methods that make full use of the program text of Af should be able to come up with a better way to evaluate the gradient of f. The system "Jake" described in this thesis produces gradients significantly faster than numerical differencing. A system sketch of Jake is presented below:
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2014
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Speelpenning, Bert
Subjects
dc:subject × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (UMI)AAI8017989
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/66437