Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
484081 | Procedia Computer Science | 2016 | 12 Pages |
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
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Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Diana Andreea Popescu, Rogelio Tomas Garcia,