1996
DOI: 10.1006/jsco.1996.0021
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Parallel Polynomial Operations on SMPs: an Overview

Abstract: SMP-based parallel algorithms and implementations for polynomial factoring and GCD are overviewed. Topics include polynomial factoring modulo small primes, univariate and multivariate p-adic lifting, and reformulation of lift basis. Sparse polynomial GCD is also covered.

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Cited by 16 publications
(11 citation statements)
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References 16 publications
(18 reference statements)
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“…Early implementations of parallel algorithms for polynomial multiplication include the work of Wang in [18] and Fitch and Norman [13]. For dense univariate polynomials f = a0 + a1x + ... + amx m and g = b0 + b1x + ... + bnx n Wang used the following formula to multiply f × g:…”
Section: Resultsmentioning
confidence: 99%
“…Early implementations of parallel algorithms for polynomial multiplication include the work of Wang in [18] and Fitch and Norman [13]. For dense univariate polynomials f = a0 + a1x + ... + amx m and g = b0 + b1x + ... + bnx n Wang used the following formula to multiply f × g:…”
Section: Resultsmentioning
confidence: 99%
“…As the d k could be computed independently [21], the outer loops of FMAsame (line 4) and FMAcst (line 2) could be easily parallelized. Only a synchronization barrier is required after the loop between the threads which process the body loop.…”
Section: Recursive Densementioning
confidence: 99%
“…We divide recursively to obtain a quotient term qi, then we subtract f := f − qig. The recursive coefficient operations could be performed in parallel as suggested by Wang in [15].…”
Section: Sparse Polynomial Divisionmentioning
confidence: 99%
“…Our algorithm is asynchronous and does not wait between the computation of qi and qi+1. In [15], Wang suggests parallelizing the subtraction of qi · g and synchronizing after each new term of the quotient. No data is provided to assess the effectiveness of this approach but we believe the waiting would be a problem.…”
Section: Introductionmentioning
confidence: 99%