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Marco Platzner
University of Paderborn
206Publications
24H-index
2,283Citations
Publications 206
Newest
#1Carlos Paiz Gatica (Detmold)H-Index: 2
#2Marco Platzner (University of Paderborn)H-Index: 24
Machine learning algorithms play a significant role for the realization of industrial analytics functions, such as predictive maintenance. This paper first outlines the workflow and topology variants for industrial analytics, and then focuses on the efficient realization of machine learning algorithms on edge devices using reconfigurable System-on-Chip architectures, showing the benefits of an optimized application-specific realization.
#1Linus Witschen (University of Paderborn)H-Index: 1
#2Muhammad Awais (University of Paderborn)H-Index: 1
Last.Marco Platzner (University of Paderborn)H-Index: 24
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Abstract Existing approaches and tools for the generation of approximate circuits often lack generality and are restricted to certain circuit types, approximation techniques, and quality assurance methods. Moreover, only few tools are publicly available. This hinders the development and evaluation of new techniques for approximating circuits and their comparison to previous approaches. In this paper, we first analyze and classify related approaches and then present CIRCA, our flexible framework ...
#1Linus Witschen (University of Paderborn)H-Index: 1
#2Hassan Ghasemzadeh Mohammadi (University of Paderborn)H-Index: 2
Last.Marco Platzner (University of Paderborn)H-Index: 24
view all 4 authors...
State-of-the-art frameworks for generating approximate circuits automatically explore the search space in an iterative process - often greedily. Synthesis and verification processes are invoked in each iteration to evaluate the found solutions and to guide the search algorithm. As a result, a large number of approximate circuits is subjected to analysis - leading to long runtimes - but only a few approximate circuits might form an acceptable solution. In this paper, we present our Jump Search (J...
2019 in IPDPS (International Parallel and Distributed Processing Symposium)
#1Zakarya Guettatfi (University of Paderborn)
#2Marco Platzner (University of Paderborn)H-Index: 24
Last.Abdelhakim KhouasH-Index: 1
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#1Qazi Arbab Ahmed (University of Paderborn)
#2Tobias Wiersema (University of Paderborn)H-Index: 3
Last.Marco Platzner (University of Paderborn)H-Index: 24
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Reconfigurable hardware has received considerable attention as a platform that enables dynamic hardware updates and thus is able to adapt new configurations at runtime. However, due to their dynamic nature, e.g., field-programmable gate arrays (FPGA) are subject to a constant possibility of attacks, since each new configuration might be compromised. Trojans for reconfigurable hardware that evade state-of-the-art detection techniques and even formal verification, are thus a large threat to these ...
#1Tim Hansmeier (University of Paderborn)
#2Marco Platzner (University of Paderborn)H-Index: 24
Last.David L. Andrews (UA: University of Arkansas)H-Index: 12
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Modern Boolean satisfiability solvers can emit proofs of unsatisfiability. There is substantial interest in being able to verify such proofs and also in using them for further computations. In this paper, we present an FPGA accelerator for checking resolution proofs, a popular proof format. Our accelerator exploits parallelism at the low level by implementing the basic resolution step in hardware, and at the high level by instantiating a number of parallel modules for proof checking. Since proof...
#1Alexander Boschmann (University of Paderborn)H-Index: 4
#2Andreas Agne (University of Paderborn)H-Index: 8
Last.Marco Platzner (University of Paderborn)H-Index: 24
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Abstract Advances in electromyographic (EMG) sensor technology and machine learning algorithms have led to an increased research effort into high density EMG-based pattern recognition methods for prosthesis control. With the goal set on an autonomous multi-movement prosthesis capable of performing training and classification of an amputee’s EMG signals, the focus of this paper lies in the acceleration of the embedded signal processing chain. We present two Xilinx Zynq-based architectures for acc...
#1Muhammad Awais (University of Paderborn)H-Index: 1
#2Hassan Ghasemzadeh Mohammadi (University of Paderborn)H-Index: 2
Last.Marco Platzner (University of Paderborn)H-Index: 24
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Approximate computing has become a very popular design strategy that exploits error resilient computations to achieve higher performance and energy efficiency. Automated synthesis of approximate circuits is performed via functional approximation, in which various parts of the target circuit are extensively examined with a library of approximate components/transformations to trade off the functional accuracy and computational budget (i.e., power). However, as the number of possible approximate tr...
#1Achim Lösch (University of Paderborn)H-Index: 2
#2Marco Platzner (University of Paderborn)H-Index: 24
Heterogeneous computing with CPUs, GPUs, and FPGAs has strongly gained interest in the last years. While scheduling and optimization problems for runtime have been widely studied, optimizing for energy-related metrics has become an emerging topic only recently due to rising electricity costs and the difficulties of thermal management. Energy-optimizing schedulers need to predict the effect of single task-resource assignment decisions on the consumed energy as well as the energy consumptions for ...
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