Multivariate Polynomial Multiplication on GPU | Zendy

Diana Andreea Popescu | Zendy; Rogelio Tomás | Zendy

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Multivariate Polynomial Multiplication on GPU

Author(s) -

Diana Andreea Popescu,

Rogelio Tomás

Publication year - 2016

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2016.05.306

Subject(s) - cuda , computer science , multiplication (music) , parallel computing , polynomial , multivariate statistics , computational science , double precision floating point format , floating point , algorithm , mathematics , mathematical analysis , combinatorics , machine learning

Multivariate polynomial multiplication is a fundamental operation which is used in many scientific domains, for example in the optics code for particle accelerator design at CERN. We present a novel and efficient multivariate polynomial multiplication algorithm for GPUs using floating-point double precision coefficients implemented using the CUDA parallel programming platform. We obtain very good speedups over another multivariate polynomial multiplication library for GPUs (up to 548x), and over the implementation of our algorithm for multi-core machines using OpenMP (up to 7.46x)

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