Florian Stock

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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(More)
The usage of Conformal Geometric Algebra leads to algorithms that can be formulated in a very clear and easy to grasp way. But it can also increase the performance of an implementation because of its capabilities to be computed in parallel. In this paper we show how a grasping algorithm for a robotic arm is accelerated using a Conformal Geometric Algebra(More)
Image reconstruction, a very compute-intense process in general, can often be reduced to large linear equation systems represented as sparse under-determined matrices. Solvers for these equation systems (not restricted to image reconstruction) spend most of their time in sparse matrix-vector multiplications (SpMV). In this paper we will present a(More)
The aim of this study was to assess cardiac deformation patterns in myocarditis applying feature tracking imaging (FTI) to cardiovascular magnetic resonance (CMR) images. Thirty-six patients (31 males) with acute myocarditis and 36 age- and gender-matched healthy volunteers were studied. CMR examinations were performed in a 1.5 T MR-scanner including late(More)
This paper presents a very efficient approach for algorithms developed based on conformal geometric algebra using reconfigurable hardware. We use the inverse kinematics of the arm of a virtual human as an example, but we are convinced that this approach can be used in a wide field of computer animation applications. We describe the original algorithm on a(More)
Control-memory-data flow graphs (CMDFGs) are a unified intermediate representation for compiling high-level languages onto reconfigurable adaptive computing systems. We present both their initial construction as well as transformations for parallel memory accesses. The impact on a number of applications is examined, also considering the effect of caches on(More)
Geometric Algebra (GA), a generalization of quaternions, is a very powerful form for intuitively expressing and manipulating complex geometric relationships common to engineering problems. The actual evaluation of GA expressions, though, is extremely compute intensive due to the high-dimensionality of data being processed. On standard desktop CPUs, GA(More)
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(More)
In recent years, Geometric Algebra (GA) has become more and more popular in fields of science and engineering due to its potential for compact algorithms. However, the execution of GA algorithms and the related need for high computational power is still the limiting factor for these algorithms to be used in practice. Therefore, it would be desirable to(More)