Alex Wiens

University of Paderborn

4Publications

2H-index

5Citations

Publications 4

Newest

#1Achim Losch (University of Paderborn)H-Index: 2

#2Alex Wiens (University of Paderborn)H-Index: 2

Last.Marco Platzner (University of Paderborn)H-Index: 25

view all 3 authors...

Profiling applications on a heterogeneous compute node is challenging since the way to retrieve data from the resources and interpret them varies between resource types and manufacturers. This holds especially true for measuring the energy consumption. In this paper we present Ampehre, a novel open source measurement framework that allows developers to gather comparable measurements from heterogeneous compute nodes, e.g., nodes comprising CPU, GPU, and FPGA. We explain the architecture of Ampehr...

Mar 1, 2017 in DATE (Design, Automation, and Test in Europe)

#1Alexander Boschmann (University of Paderborn)H-Index: 6

#2Georg Thombansen (University of Paderborn)H-Index: 1

Last.Marco Platzner (University of Paderborn)H-Index: 25

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The combination of high-density electromyographic (HD EMG) sensor technology and modern machine learning algorithms allows for intuitive and robust prosthesis control of multiple degrees of freedom. However, HD EMG real-time processing poses a challenge for common microprocessors in an embedded system. With the goal set on an autonomous prosthesis capable of performing training and classification of an amputee's HD EMG signals, the focus of this paper lies in the acceleration of the computationa...

#1Alex Wiens (University of Paderborn)H-Index: 2

#2Gitta Domik (University of Paderborn)H-Index: 12

This article describes a simple course exercise to deepen the understanding of real-time shadow volume algorithms. The exercise takes less than 10 minutes to perform during lecture time, leads to a profounder understanding of the topic, and serves as a basis for further discussions of improvements for the shadow mapping algorithm. Using this exercise, the authors noticed an increase in students implementing shadow algorithms for later real-time graphics projects.

#1Alex Wiens (University of Paderborn)H-Index: 2

#2Gitta Domik (University of Paderborn)H-Index: 12

This article describes a simple course exercise to deepen the understanding of real-time shadow mapping algorithms. The exercise takes less than 10 minutes to perform during lecture time, leads to a profounder understanding of the topic, and serves as a basis for further discussions of improvements for the shadow mapping algorithm. Using this exercise, the authors noticed an increase in implementing shadow algorithms for later real-time graphics projects.

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