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Conference Papers Year : 2017

A hybrid approach for computing products of high-dimensional geometric algebras

Abstract

Geometric Algebra is considered as a very intuitive tool to deal with geometric problems and it appears to be increasingly efficient and useful to deal with computer graphics solutions. For example, the Conformal Geometric Algebra includes circles, spheres, planes and lines as algebraic objects, and intersections between these objects are also algebraic objects. More complex objects such as conics, quadric surfaces can also be expressed and be manipulated using an extension of the conformal Geometric Algebra. However due to high dimension of their representations in Geometric Algebra, implementations of Geometric Algebra that are currently available do not allow efficient realizations of these objects. This paper presents a Geometric Algebra implementation dedicated for both low and high dimensions. The proposed method is a hybrid solution for precomputed code with fast execution and runtime computations with low memory requirement. More specifically, the proposed method combines a precomputed table approach with a recursive method using binary trees. Some rules are defined to select the most appropriate choice, according to the dimension of the algebra and the type of multivectors involved in the product. The resulting implementation is well suited for high dimensional spaces (e.g. algebra of dimension 15) as well as for lower dimensional space. This paper details the integration of this hybrid method as a plug-in into Gaalop, which is a very advanced optimizing code generator. This paper also presents some benchmarks to show the performances of our method, especially in high dimensional spaces.

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Other [cs.OH]
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Dates and versions

hal-01552462 , version 1 (03-07-2017)

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Stéphane Breuils, Vincent Nozick, Laurent Fuchs, Dietmar Hildenbrand, Werner Benger, et al.. A hybrid approach for computing products of high-dimensional geometric algebras. CGI / ENGAGE 2017, Jun 2017, Hiyoshi, Japan. pp.1 - 6, ⟨10.1145/3095140.3097284⟩. ⟨hal-01552462⟩
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