Acceleration and Energy Efficiency of Geometric Algebra Computations Using Reconfigurable Computers and Gpus

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 robotics can be accelerated using reconfigurable FPGAbased computing and on a graphics processing unit (GPU). The practical evaluation covers not only the sheer compute performance, but also the energy efficiency of the various solutions.