Evaluating Polynomials in Several Variables and Their Derivatives on a GPU Computing Processor

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Provided by: University of Illinois
Topic: Hardware
Format: PDF
In order to obtain more accurate solutions of polynomial systems with numerical continuation methods the users use multiprecision arithmetic. Their goal is to offset the overhead of double arithmetic accelerating the path trackers and in particular Newton's method with a general purpose graphics processing unit. In this paper, the authors describe algorithms for the massively parallel evaluation and differentiation of sparse polynomials in several variables. They report on their implementation of the algorithmic differentiation of products of variables on the NVIDIA Tesla C2050 Computing Processor using the NVIDIA CUDA compiler tools.
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