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Team Show image information

Team

Linus Witschen

Contact
 Linus  Witschen

Computer Engineering

Research Associate

Phone:
+49 5251 60-1729
Office:
O3.119
Visitor:
Pohlweg 51
33098 Paderborn

Approximate Computing

You can find the repository of our Approximate Circuit Synthesis framework here:
CIRCA: A Modular and Extensible Framework for Approximate Circuit Generation

Publications


Open list in Research Information System

Conferences

Timing Optimization for Virtual FPGA Configurations

L.M. Witschen, T. Wiersema, M. Raeisi Nafchi, A. Bockhorn, M. Platzner, in: Proceedings of International Symposium on Applied Reconfigurable Computing (ARC'21), Springer Lecture Notes in Computer Science, 2021

@inproceedings{Witschen_Wiersema_Raeisi Nafchi_Bockhorn_Platzner, series={Reconfigurable Computing: Architectures, Tools, and Applications}, title={Timing Optimization for Virtual FPGA Configurations}, booktitle={Proceedings of International Symposium on Applied Reconfigurable Computing (ARC’21)}, publisher={Springer Lecture Notes in Computer Science}, author={Witschen, Linus Matthias and Wiersema, Tobias and Raeisi Nafchi, Masood and Bockhorn, Arne and Platzner, Marco}, editor={Hannig, Frank and Derrien, Steven and Diniz, Pedro and Chillet, DanielEditors}, collection={Reconfigurable Computing: Architectures, Tools, and Applications} }


    Jump Search: A Fast Technique for the Synthesis of Approximate Circuits

    L.M. Witschen, H. Ghasemzadeh Mohammadi, M. Artmann, M. Platzner, in: Proceedings of the 2019 on Great Lakes Symposium on VLSI - GLSVLSI '19, ACM, 2019

    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 (JS) method which seeks to reduce the runtime of an approximation process by reducing the number of expensive synthesis and verification steps. To reduce the runtime, JS computes impact factors for each approximation candidate in the circuit to create a selection of approximate circuits without invoking synthesis or verification processes. We denote the selection as path from which JS determines the final solution. In our experimental results, JS achieved speed-ups of up to 57x while area savings remain comparable to the reference search method, Simulated Annealing.

    @inproceedings{Witschen_Ghasemzadeh Mohammadi_Artmann_Platzner_2019, place={New York, NY, USA}, title={Jump Search: A Fast Technique for the Synthesis of Approximate Circuits}, DOI={10.1145/3299874.3317998}, booktitle={Proceedings of the 2019 on Great Lakes Symposium on VLSI  - GLSVLSI ’19}, publisher={ACM}, author={Witschen, Linus Matthias and Ghasemzadeh Mohammadi, Hassan and Artmann, Matthias and Platzner, Marco}, year={2019} }


      A Zynq-based dynamically reconfigurable high density myoelectric prosthesis controller

      A. Boschmann, G. Thombansen, L.M. Witschen, A. Wiens, M. Platzner, in: Design, Automation and Test in Europe (DATE), 2017

      @inproceedings{Boschmann_Thombansen_Witschen_Wiens_Platzner_2017, title={A Zynq-based dynamically reconfigurable high density myoelectric prosthesis controller}, DOI={10.23919/DATE.2017.7927137}, booktitle={Design, Automation and Test in Europe (DATE)}, author={Boschmann, Alexander and Thombansen, Georg and Witschen, Linus Matthias and Wiens, Alex and Platzner, Marco}, year={2017} }


        FPGA-based acceleration of high density myoelectric signal processing

        A. Boschmann, A. Agne, L.M. Witschen, G. Thombansen, F. Kraus, M. Platzner, in: 2015 International Conference on ReConFigurable Computing and FPGAs (ReConFig), IEEE, 2016

        @inproceedings{Boschmann_Agne_Witschen_Thombansen_Kraus_Platzner_2016, title={FPGA-based acceleration of high density myoelectric signal processing}, DOI={10.1109/reconfig.2015.7393312}, booktitle={2015 International Conference on ReConFigurable Computing and FPGAs (ReConFig)}, publisher={IEEE}, author={Boschmann, Alexander and Agne, Andreas and Witschen, Linus Matthias and Thombansen, Georg and Kraus, Florian and Platzner, Marco}, year={2016} }


          Journal Articles

          Proof-carrying Approximate Circuits

          L.M. Witschen, T. Wiersema, M. Platzner, IEEE Transactions On Very Large Scale Integration Systems (2020), 28(9), pp. 2084 - 2088

          Approximate circuits trade-off computational accuracy against improvements in hardware area, delay, or energy consumption. IP core vendors who wish to create such circuits need to convince consumers of the resulting approximation quality. As a solution we propose proof-carrying approximate circuits: The vendor creates an approximate IP core together with a certificate that proves the approximation quality. The proof certificate is bundled with the approximate IP core and sent off to the consumer. The consumer can formally verify the approximation quality of the IP core at a fraction of the typical computational cost for formal verification. In this paper, we first make the case for proof-carrying approximate circuits and then demonstrate the feasibility of the approach by a set of synthesis experiments using an exemplary approximation framework.

          @article{Witschen_Wiersema_Platzner_2020, title={Proof-carrying Approximate Circuits}, volume={28}, DOI={10.1109/TVLSI.2020.3008061}, number={9}, journal={IEEE Transactions On Very Large Scale Integration Systems}, publisher={IEEE}, author={Witschen, Linus Matthias and Wiersema, Tobias and Platzner, Marco}, year={2020}, pages={2084–2088} }


            Zynq-based acceleration of robust high density myoelectric signal processing

            A. Boschmann, A. Agne, G. Thombansen, L.M. Witschen, F. Kraus, M. Platzner, Journal of Parallel and Distributed Computing (2019), 123, pp. 77-89

            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 accelerating two inherently different high density EMG-based control algorithms. The first hardware accelerated design achieves speed-ups of up to 4.8 over the software-only solution, allowing for a processing delay lower than the sample period of 1 ms. The second system achieved a speed-up of 5.5 over the software-only version and operates at a still satisfactory low processing delay of up to 15 ms while providing a higher reliability and robustness against electrode shift and noisy channels.

            @article{Boschmann_Agne_Thombansen_Witschen_Kraus_Platzner_2019, title={Zynq-based acceleration of robust high density myoelectric signal processing}, volume={123}, DOI={10.1016/j.jpdc.2018.07.004}, journal={Journal of Parallel and Distributed Computing}, publisher={Elsevier}, author={Boschmann, Alexander and Agne, Andreas and Thombansen, Georg and Witschen, Linus Matthias and Kraus, Florian and Platzner, Marco}, year={2019}, pages={77–89} }


              CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation

              L.M. Witschen, T. Wiersema, H. Ghasemzadeh Mohammadi, M. Awais, M. Platzner, Microelectronics Reliability (2019), 99, pp. 277-290

              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 for search-based approximate circuit generation. CIRCA is developed with a focus on modularity and extensibility. We present the architecture of CIRCA with its clear separation into stages and functional blocks, report on the current prototype, and show initial experiments.

              @article{Witschen_Wiersema_Ghasemzadeh Mohammadi_Awais_Platzner_2019, title={CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation}, volume={99}, DOI={10.1016/j.microrel.2019.04.003}, journal={Microelectronics Reliability}, publisher={Elsevier}, author={Witschen, Linus Matthias and Wiersema, Tobias and Ghasemzadeh Mohammadi, Hassan and Awais, Muhammad and Platzner, Marco}, year={2019}, pages={277–290} }


                Master's Theses

                A Framework for the Synthesis of Approximate Circuits

                L.M. Witschen, Master's thesis, Universität Paderborn, 2017

                @book{Witschen_2017, title={A Framework for the Synthesis of Approximate Circuits}, publisher={Universität Paderborn}, author={Witschen, Linus Matthias}, year={2017} }


                  Preprint

                  Search Space Characterization for AxC Synthesis

                  L.M. Witschen, T. Wiersema, M. Platzner, in: Fifth Workshop on Approximate Computing (AxC 2020), 2020

                  On the circuit level, the design paradigm Approximate Computing seeks to trade off computational accuracy against a target metric, e.g., energy consumption. This trade-off is possible for many applications due to their inherent resiliency against inaccuracies. In the past, several automated approximation frameworks have been presented, which either utilize designated approximation techniques or libraries to replace approximable circuit parts with inaccurate versions. The frameworks invoke a search algorithm to iteratively explore the search space of performance degraded circuits, and validate their quality individually. In this paper, we propose to reverse this procedure. Rather than exploring the search space, we delineate the approximate parts of the search space which are guaranteed to lead to valid approximate circuits. Our methodology is supported by formal verification and independent of approximation techniques. Eventually, the user is provided with quality bounds of the individual approximable circuit parts. Consequently, our approach guarantees that any approximate circuit which implements these parts within the determined quality constraints satisfies the global quality constraints, superseding a subsequent quality verification. In our experimental results, we present the runtimes of our approach.

                  @article{Witschen_Wiersema_Platzner, title={Search Space Characterization for AxC Synthesis}, journal={Fifth Workshop on Approximate Computing (AxC 2020)}, author={Witschen, Linus Matthias and Wiersema, Tobias and Platzner, Marco} }


                    Jump Search: A Fast Technique for the Synthesis of Approximate Circuits

                    L.M. Witschen, H. Ghasemzadeh Mohammadi, M. Artmann, M. Platzner, in: Fourth Workshop on Approximate Computing (AxC 2019), 2019

                    State-of-the-art frameworks for generating approximate circuits usually rely on information gained through circuit synthesis and/or verification to explore the search space and to find an optimal solution. Throughout the process, a large number of circuits may be subject to processing, leading to considerable runtimes. In this work, we propose a search which takes error bounds and pre-computed impact factors into account to reduce the number of invoked synthesis and verification processes. In our experimental results, we achieved speed-ups of up to 76x while area savings remain comparable to the reference search method, simulated annealing.

                    @article{Witschen_Ghasemzadeh Mohammadi_Artmann_Platzner, title={Jump Search: A Fast Technique for the Synthesis of Approximate Circuits}, journal={Fourth Workshop on Approximate Computing (AxC 2019)}, author={Witschen, Linus Matthias and Ghasemzadeh Mohammadi, Hassan and Artmann, Matthias and Platzner, Marco} }


                      CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation

                      L.M. Witschen, T. Wiersema, H. Ghasemzadeh Mohammadi, M. Awais, M. Platzner, in: Third Workshop on Approximate Computing (AxC 2018), 2018

                      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 for search-based approximate circuit generation. CIRCA is developed with a focus on modularity and extensibility. We present the architecture of CIRCA with its clear separation into stages and functional blocks, report on the current prototype, and show initial experiments.

                      @article{Witschen_Wiersema_Ghasemzadeh Mohammadi_Awais_Platzner, title={CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation}, journal={Third Workshop on Approximate Computing (AxC 2018)}, author={Witschen, Linus Matthias and Wiersema, Tobias and Ghasemzadeh Mohammadi, Hassan and Awais, Muhammad and Platzner, Marco} }


                        Making the Case for Proof-carrying Approximate Circuits

                        L.M. Witschen, T. Wiersema, M. Platzner, in: 4th Workshop On Approximate Computing (WAPCO 2018), 2018

                        @article{Witschen_Wiersema_Platzner_2018, title={Making the Case for Proof-carrying Approximate Circuits}, journal={4th Workshop On Approximate Computing (WAPCO 2018)}, author={Witschen, Linus Matthias and Wiersema, Tobias and Platzner, Marco}, year={2018} }


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