Lange, Holger ; Stock, Florian ; Koch, Andreas ; Hildenbrand, Dietmar (2009)
Acceleration and Energy Efficiency of a Geometric Algebra Computation Using Reconfigurable Computers and GPUs.
Proceedings of the 2009 17th IEEE Symposium on Field Programmable Custom Computing Machines.
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Geometric algebra (GA) is a mathematical framework that allows the compact description of geometric relationships and algorithms in many fields of science and engineering. The execution of these algorithms, however, requires significant computational power that made the use of GA impractical for many real-world applications. We describe how a GA-based formulation of the inverse kinematics problem from computer animation and robotics can be accelerated using reconfigurable FPGA-based computing and using a graphics processing unit (GPU). The practical evaluation covers not only the sheer compute performance, but also the energy efficiency.
Typ des Eintrags: | Konferenzveröffentlichung |
---|---|
Erschienen: | 2009 |
Autor(en): | Lange, Holger ; Stock, Florian ; Koch, Andreas ; Hildenbrand, Dietmar |
Art des Eintrags: | Bibliographie |
Titel: | Acceleration and Energy Efficiency of a Geometric Algebra Computation Using Reconfigurable Computers and GPUs |
Sprache: | Englisch |
Publikationsjahr: | 2009 |
Verlag: | IEEE Computer Society Conference Publishing Services (CPS), Los Alamitos, Calif. |
Veranstaltungstitel: | Proceedings of the 2009 17th IEEE Symposium on Field Programmable Custom Computing Machines |
Kurzbeschreibung (Abstract): | Geometric algebra (GA) is a mathematical framework that allows the compact description of geometric relationships and algorithms in many fields of science and engineering. The execution of these algorithms, however, requires significant computational power that made the use of GA impractical for many real-world applications. We describe how a GA-based formulation of the inverse kinematics problem from computer animation and robotics can be accelerated using reconfigurable FPGA-based computing and using a graphics processing unit (GPU). The practical evaluation covers not only the sheer compute performance, but also the energy efficiency. |
Freie Schlagworte: | Forschungsgruppe Geometric Algebra Computing (GACO), Graphics Processing Unit (GPU), Geometric algebra (GA), Inverse kinematics, Field-programmable gate array (FPGA) |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
Hinterlegungsdatum: | 12 Nov 2018 11:16 |
Letzte Änderung: | 12 Nov 2018 11:16 |
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