Geometric Algebra (GA), a generalization of quaternions and complex numbers, is a very powerful framework for intuitively expressing and manipulating the complex geometric relationships common to engineering problems. However, actual processing of GA expressions is very compute intensive, and acceleration is generally required for practical use. GPUs and FPGAs offer such acceleration, while requiring only low-power per operation. In this paper, we present key components of a proof-of-concept compile flow combining symbolic and hardware optimization techniques to automatically generate hardware accelerators from the abstract GA descriptions that are suitable for high-performance embedded computing.
@InProceedings{huthmann_et_al:DagSemProc.10281.6, author = {Huthmann, Jens and M\"{u}ller, Peter and Stock, Florian and Hildenbrand, Dietmar and Koch, Andreas}, title = {{Compiling Geometric Algebra Computations into Reconfigurable Hardware Accelerators}}, booktitle = {Dynamically Reconfigurable Architectures}, pages = {1--15}, series = {Dagstuhl Seminar Proceedings (DagSemProc)}, ISSN = {1862-4405}, year = {2010}, volume = {10281}, editor = {Peter M. Athanas and J\"{u}rgen Becker and J\"{u}rgen Teich and Ingrid Verbauwhede}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.10281.6}, URN = {urn:nbn:de:0030-drops-28389}, doi = {10.4230/DagSemProc.10281.6}, annote = {Keywords: Geometric Algebra FPGA High-Level-Compiler Gaalop} }
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