Multivariate Polynomial Multiplication on GPU

https://doi.org/10.1016/j.procs.2016.05.306Get rights and content
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Abstract

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).

Keywords

computer algebra
multivariate polynomial multiplication
GPU
CUDA
particle accelerator design

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Selection and peer-review under responsibility of the Scientific Programme Committee of ICCS 2016.