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Tensor Decompositions are a solved problem in terms of evaluating for a result. Performance, however, is not. There are several projects to parallelize tensor decompositions, using a variety of different methods. This work focuses on investigating other possible strategies for parallelization of rank-one tensor decompositions, measuring performance across a variety of tensor sizes, and reporting the best avenues to continue investigation
Advisor: | Marron, Christopher |
Commitee: | Banerjee, Nilanjan, Nicholas, Charles |
School: | University of Maryland, Baltimore County |
Department: | Computer Science |
School Location: | United States -- Maryland |
Source: | MAI 57/04M(E), Masters Abstracts International |
Source Type: | DISSERTATION |
Subjects: | Computer science |
Keywords: | |
Publication Number: | 10683240 |
ISBN: | 978-0-355-67415-6 |