Affiliation:
1. Simon Fraser University, Burnaby B.C., Canada
Abstract
We demonstrate new routines for sparse multivariate polynomial multiplication and division over the integers that we have integrated into Maple 14 through the expand and divide commands. These routines are currently the fastest available, and the multiplication routine is parallelized with superlinear speedup. The performance of Maple is significantly improved. We describe our polynomial data structure and compare it with Maple's. Then we present benchmarks comparing Maple 14 with Maple 13, Magma, Mathematica, Singular, Pari, and Trip.
Publisher
Association for Computing Machinery (ACM)
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Algorithms and Data Structures for Sparse Polynomial Arithmetic;Mathematics;2019-05-17
2. Rings: An efficient Java/Scala library for polynomial rings;Computer Physics Communications;2019-02
3. What Can (and Can't) we Do with Sparse Polynomials?;Proceedings of the 2018 ACM International Symposium on Symbolic and Algebraic Computation;2018-07-11
4. Multivariate Polynomial Multiplication on GPU;Procedia Computer Science;2016
5. POLY;ACM Communications in Computer Algebra;2013-01-15