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Acceleration and Energy Efficiency of a Geometric Algebra Computation using Reconfigurable Computers and GPUs

Holger Lange, Florian Stock, Andreas Koch, Dietmar Hildenbrand
LOEWE Research Center AdRIA, Technische Universitat Darmstadt
17th IEEE Symposium on Field Programmable Custom Computing Machines, 2009. FCCM ’09, p.255-258

@conference{lange2009acceleration,

   title={Acceleration and Energy Efficiency of a Geometric Algebra Computation using Reconfigurable Computers and GPUs},

   author={Lange, H. and Stock, F. and Koch, A. and Hildenbrand, D.},

   booktitle={Field Programmable Custom Computing Machines, 2009. FCCM’09. 17th IEEE Symposium on},

   pages={255–258},

   year={2009},

   organization={IEEE}

}

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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.
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