Graduate Thesis Or Dissertation
 

Parallel and high performance matrix function computations

Public Deposited

Downloadable Content

Download PDF
Request Accessible Version
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/hx11xj687

Descriptions

Attribute NameValues
Creator
Abstract
  • Computing eigenpairs of a matrix corresponding to a specific geometry in the complex plane is an important topic in real time signal processing, pattern recognition, spectral analysis, systems theory, radar, sonar, and geophysics. We have studied the matrix sign and matrix sector function iterations to extract the eigenpairs belonging to various geometries without resorting to computationally expensive eigenanalysis methods. We propose a parallelization of an existing matrix sign function algorithm, which was implemented on a Meiko CS-2 multiprocessor. We obtain a fast and stable algorithm for computing the matrix sector functions using Halley's generalized iteration formula for solving nonlinear equations. We propose a parallel iterative algorithm to compute the principal nth root of a positive definite matrix using Gauss-Legendre integration formula. Furthermore computing functions of square matrices is also an important topic in linear algebra, engineering, and applied mathematics. A parallelization of Parlett's algorithm for computing arbitrary functions of upper triangular matrices is introduced. We propose a block-recursive and a parallel algorithm for fast and efficient computation of functions of triangular matrices. The parallel complexity and cache efficiency of these algorithms for computers with two levels of memory are also analyzed.
Resource Type
Date Available
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
Publisher
Peer Reviewed
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome, 256 Grayscale) using Capture Perfect 3.0.82 on a Canon DR-9080C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces

Relationships

Parents:

This work has no parents.

In Collection:

Items

Thumbnail Title Date Uploaded Visibility Actions
file details BakkalogluBertan1996.pdf 2017-08-15 Public Download