Parallel Multivariate Polynomial Multiplication and Division

In this internship, the team proposes to develop high performance sequential and parallel algorithms for multiplication and division of multivariate polynomials. They propose to use a recursive data structure. One of the possible advantages of a recursive data structure is that we can also see how to parallelize polynomial division. Potentially high level algorithms such as computing polynomial GCDs and polynomial factorization will benefit from this speedup. If successful, the final code could be integrated into Maple's existing recursive dense facility (called RECDEN) which currently supports polynomial arithmetic over number fields.

Intern: 
Simon Lo
Faculty Supervisor: 
Dr. Michael Monagan
Province: 
British Columbia
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