Comparing the speed of programs for sparse polynomial multiplication

Author:

Fateman Richard1

Affiliation:

1. University of California, Berkeley, CA

Abstract

How should one design and implement a program for the multiplication of sparse polynomials? This is a simple question, necessarily addressed by the builders of any computer algebra system (CAS). To examine a few options we start with a single easily-stated computation which we believe represents a useful benchmark of "medium difficulty" for CAS designs. We describe a number of design options and their effects on performance. We also examine the performance of a variety of commercial and freely-distributed systems. Important considerations include the cost of high-precision (exact) integer arithmetic and the effective use of cache memory.

Publisher

Association for Computing Machinery (ACM)

Reference5 articles.

1. The Altran system for rational function manipulation — a survey

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3. R. Fateman. "Memory Cache and Lisp: Faster list processing via automatically rearranging memory " Draft May 2002. R. Fateman. "Memory Cache and Lisp: Faster list processing via automatically rearranging memory " Draft May 2002.

4. Yozo Hida. "Data Structures and Cache Behavior of Sparse Polynomial Multiplication " Class project CS282 UC Berkeley May 2002. Yozo Hida. "Data Structures and Cache Behavior of Sparse Polynomial Multiplication " Class project CS282 UC Berkeley May 2002.

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