Efficient Evaluation of Large Polynomials

Minimizing the evaluation cost of a polynomial expression is a fundamental problem in computer science. We propose tools that, for a polynomial P given as the sum of its terms, compute a representation that permits a more efficient evaluation. Our algorithm runs in d(nt) [superscript O(1)] bit opera...

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Main Authors: Leiserson, Charles E., Li, Liyun, Maza, Marc Moreno, Xie, Yuzhen
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: Springer-Verlag 2014
Online Access:http://hdl.handle.net/1721.1/90262
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author Leiserson, Charles E.
Li, Liyun
Maza, Marc Moreno
Xie, Yuzhen
author2 Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
author_facet Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Leiserson, Charles E.
Li, Liyun
Maza, Marc Moreno
Xie, Yuzhen
author_sort Leiserson, Charles E.
collection MIT
description Minimizing the evaluation cost of a polynomial expression is a fundamental problem in computer science. We propose tools that, for a polynomial P given as the sum of its terms, compute a representation that permits a more efficient evaluation. Our algorithm runs in d(nt) [superscript O(1)] bit operations plus dt [superscript O(1)] operations in the base field where d, n and t are the total degree, number of variables and number of terms of P. Our experimental results show that our approach can handle much larger polynomials than other available software solutions. Moreover, our computed representation reduce the evaluation cost of P substantially.
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spelling mit-1721.1/902622022-10-01T05:39:55Z Efficient Evaluation of Large Polynomials Leiserson, Charles E. Li, Liyun Maza, Marc Moreno Xie, Yuzhen Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Leiserson, Charles E. Minimizing the evaluation cost of a polynomial expression is a fundamental problem in computer science. We propose tools that, for a polynomial P given as the sum of its terms, compute a representation that permits a more efficient evaluation. Our algorithm runs in d(nt) [superscript O(1)] bit operations plus dt [superscript O(1)] operations in the base field where d, n and t are the total degree, number of variables and number of terms of P. Our experimental results show that our approach can handle much larger polynomials than other available software solutions. Moreover, our computed representation reduce the evaluation cost of P substantially. 2014-09-22T17:14:55Z 2014-09-22T17:14:55Z 2010-09 Article http://purl.org/eprint/type/JournalArticle 978-3-642-15581-9 978-3-642-15582-6 0302-9743 1611-3349 http://hdl.handle.net/1721.1/90262 Leiserson, Charles E., Liyun Li, Marc Moreno Maza, and Yuzhen Xie. "Efficient Evaluation of Large Polynomials." K. Fukuda et al. (Eds.): Mathematical Software – ICMS 2010, Lecture Notes in Computer Science, Volume 6327, 2010, pp. 342-353. en_US http://dx.doi.org/10.1007/978-3-642-15582-6_55 Mathematical Software – ICMS 2010 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Springer-Verlag Other univ. web domain
spellingShingle Leiserson, Charles E.
Li, Liyun
Maza, Marc Moreno
Xie, Yuzhen
Efficient Evaluation of Large Polynomials
title Efficient Evaluation of Large Polynomials
title_full Efficient Evaluation of Large Polynomials
title_fullStr Efficient Evaluation of Large Polynomials
title_full_unstemmed Efficient Evaluation of Large Polynomials
title_short Efficient Evaluation of Large Polynomials
title_sort efficient evaluation of large polynomials
url http://hdl.handle.net/1721.1/90262
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