Abstract
We present a highly scalable algorithm for multiplying sparse multivariate polynomials represented in a distributed format. This algorithm targets not only the shared memory multicore computers, but also computers clusters or specialized hardware attached to a host computer, such as graphics processing units or many-core coprocessors. The scalability on the large number of cores is ensured by the lacks of synchronizations, locks and false-sharing during the main parallel step.
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Gastineau, M., Laskar, J. (2013). Highly Scalable Multiplication for Distributed Sparse Multivariate Polynomials on Many-Core Systems. In: Gerdt, V.P., Koepf, W., Mayr, E.W., Vorozhtsov, E.V. (eds) Computer Algebra in Scientific Computing. CASC 2013. Lecture Notes in Computer Science, vol 8136. Springer, Cham. https://doi.org/10.1007/978-3-319-02297-0_8
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DOI: https://doi.org/10.1007/978-3-319-02297-0_8
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02296-3
Online ISBN: 978-3-319-02297-0
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