POLY: A new polynomial data structure for Maple 17.

Michael Monagan, CECM, Simon Fraser University

June 20th, 2012 at 3:30pm in K9509.

In this talk we present our parallel algorithm for polynomial multiplication
and a benchmark that shows that we get good parallel speedup for multiplication.
However conversion and other overhead limits parallel speedup and we find little
parallel speedup in polynomial factorization.  

We then demonstrate how a new polynomial data structure for sparse distributed
polynomials in the Maple kernel significantly accelerates a large subset of Maple
library routines and leads to real parallel speedup in polynomial factorization.
The POLY data structure and its associated kernel operations including
    degree, coeff, subs, has, diff, eval, taylor, indets, etc.,
are programmed for high scalability, allowing polynomials to have hundreds of 
millions of terms, with very low overhead, increasing parallel speedup in existing 
routines and improving the performance of high level Maple library routines.

This is joint work with Roman Pearce.