--- _id: '22483' abstract: - lang: eng text: This bachelor thesis presents a C/C++ implementation of the XCS algorithm for an embedded system and profiling results concerning the execution time of the functions. These are then analyzed in relation to the input characteristics of the examined learning environments and compared with related work. Three main conclusions can be drawn from the measured results. First, the maximum size of the population of the classifiers influences the runtime of the genetic algorithm; second, the size of the input space has a direct effect on the execution time of the matching function; and last, a larger action space results in a longer runtime generating the prediction for the possible actions. The dependencies identified here can serve to optimize the computational efficiency and make XCS more suitable for embedded systems. author: - first_name: Mathis full_name: Brede, Mathis last_name: Brede citation: ama: 'Brede M. Implementation and Profiling of XCS in the Context of Embedded Systems. Paderborn: Paderborn University; 2021.' apa: 'Brede, M. (2021). Implementation and Profiling of XCS in the Context of Embedded Systems. Paderborn: Paderborn University.' bibtex: '@book{Brede_2021, place={Paderborn}, title={Implementation and Profiling of XCS in the Context of Embedded Systems}, publisher={Paderborn University}, author={Brede, Mathis}, year={2021} }' chicago: 'Brede, Mathis. Implementation and Profiling of XCS in the Context of Embedded Systems. Paderborn: Paderborn University, 2021.' ieee: 'M. Brede, Implementation and Profiling of XCS in the Context of Embedded Systems. Paderborn: Paderborn University, 2021.' mla: Brede, Mathis. Implementation and Profiling of XCS in the Context of Embedded Systems. Paderborn University, 2021. short: M. Brede, Implementation and Profiling of XCS in the Context of Embedded Systems, Paderborn University, Paderborn, 2021. date_created: 2021-06-21T09:35:03Z date_updated: 2022-01-06T06:55:33Z department: - _id: '78' extern: '1' language: - iso: eng place: Paderborn project: - _id: '14' name: SFB 901 - Subproject C2 - _id: '4' name: SFB 901 - Project Area C - _id: '1' name: SFB 901 publisher: Paderborn University status: public supervisor: - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner - first_name: Tim full_name: Hansmeier, Tim id: '49992' last_name: Hansmeier orcid: 0000-0003-1377-3339 title: Implementation and Profiling of XCS in the Context of Embedded Systems type: bachelorsthesis user_id: '477' year: '2021' ... --- _id: '29540' abstract: - lang: eng text: "Autonomous mobile robots are becoming increasingly more capable and widespread. Reliable Obstacle avoidance is an integral part of autonomous navigation. This involves real time interpretation and processing of a complex environment. Strict time and energy constraints of a mobile autonomous system make efficient computation extremely desirable. The benefits of employing Hardware/Software co-designed applications are obvious and significant. Hardware accelerators are used for efficient processing of the algorithms by exploiting parallelism. FPGAs are a class of hardware accelerators, which\r\ncan contain hundreds of small execution units, and can be used for Hardware/Software co-designed application. However, there is a reluctance when it comes to adoption of these devices in well established application domains, such as Robotics, due to a steep learning curve needed for FPGA application design. ReconROS has successfully bridged the gap between robotic and FPGA application development, by providing an intuitive, common development platform for robotic application development for FPGA. It does so by integrating Robotics Operating System(ROS) which is an industry and academia standard for robotics application development, with ReconOS, an operating system for re-configurable hardware. In this thesis an obstacle avoidance system is designed and implemented for an autonomous vehicle using ReconROS. The objectives of the thesis is to demonstrate and explore ReconROS integration within the ROS ecosystem and explore the design process within ReconROS framework, and to demonstrate the effectiveness of Hardware Acceleration in Robotics, by analysing the resulting architectures for Latency and Power Consumption." author: - first_name: Muhammad Aamir full_name: Sheikh, Muhammad Aamir last_name: Sheikh citation: ama: Sheikh MA. Design and Implementation of a ReconROS-Based Obstacle Avoidance System. Paderborn University; 2021. apa: Sheikh, M. A. (2021). Design and Implementation of a ReconROS-based Obstacle Avoidance System. Paderborn University. bibtex: '@book{Sheikh_2021, title={Design and Implementation of a ReconROS-based Obstacle Avoidance System}, publisher={Paderborn University}, author={Sheikh, Muhammad Aamir}, year={2021} }' chicago: Sheikh, Muhammad Aamir. Design and Implementation of a ReconROS-Based Obstacle Avoidance System. Paderborn University, 2021. ieee: M. A. Sheikh, Design and Implementation of a ReconROS-based Obstacle Avoidance System. Paderborn University, 2021. mla: Sheikh, Muhammad Aamir. Design and Implementation of a ReconROS-Based Obstacle Avoidance System. Paderborn University, 2021. short: M.A. Sheikh, Design and Implementation of a ReconROS-Based Obstacle Avoidance System, Paderborn University, 2021. date_created: 2022-01-26T08:50:52Z date_updated: 2022-01-28T08:30:46Z department: - _id: '78' language: - iso: eng publisher: Paderborn University status: public supervisor: - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner - first_name: Christian full_name: Lienen, Christian id: '60323' last_name: Lienen title: Design and Implementation of a ReconROS-based Obstacle Avoidance System type: mastersthesis user_id: '60323' year: '2021' ... --- _id: '21324' author: - first_name: Khushboo full_name: Chandrakar, Khushboo last_name: Chandrakar citation: ama: Chandrakar K. Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis.; 2020. apa: Chandrakar, K. (2020). Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis. bibtex: '@book{Chandrakar_2020, title={Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis}, author={Chandrakar, Khushboo}, year={2020} }' chicago: Chandrakar, Khushboo. Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis, 2020. ieee: K. Chandrakar, Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis. 2020. mla: Chandrakar, Khushboo. Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis. 2020. short: K. Chandrakar, Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis, 2020. date_created: 2021-03-01T09:19:29Z date_updated: 2022-01-06T06:54:54Z department: - _id: '78' - _id: '7' language: - iso: eng project: - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing status: public supervisor: - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner - first_name: Linus Matthias full_name: Witschen, Linus Matthias id: '49051' last_name: Witschen title: Comparison of Feature Selection Techniques to Improve Approximate Circuit Synthesis type: mastersthesis user_id: '49051' year: '2020' ... --- _id: '21432' abstract: - lang: eng text: "Robots are becoming increasingly autonomous and more capable. Because of a limited portable energy budget by e.g. batteries, and more demanding algorithms, an efficient computation is of interest. Field Programmable Gate Arrays (FPGAs) for example can provide fast and efficient processing and the Robot Operating System (ROS) is a popular\r\nmiddleware used for robotic applications. The novel ReconROS combines version 2 of the Robot Operating System with ReconOS, a framework for integrating reconfigurable hardware. It provides a unified interface between software and hardware. ReconROS is evaluated in this thesis by implementing a Sobel filter as the video processing application, running on a Zynq-7000 series System on Chip. Timing measurements were taken of execution and transfer times and were compared to theoretical values. Designing the hardware implementation is done by C code using High Level Synthesis and with the interface and functionality provided by ReconROS. An important aspect is the publish/subscribe mechanism of ROS. The Operating System interface functions for publishing and subscribing are reasonably fast at below 10 ms for a 1 MB color VGA image. The main memory interface performs well at higher data sizes, crossing 100 MB/s at 20 kB and increasing to a maximum of around 150 MB/s. Furthermore, the hardware implementation introduces consistency to the execution times and performs twice as fast as the software implementation." author: - first_name: Luca-Sebastian full_name: Henke, Luca-Sebastian last_name: Henke citation: ama: Henke L-S. Evaluation of a ReconOS-ROS Combination Based on a Video Processing Application.; 2020. apa: Henke, L.-S. (2020). Evaluation of a ReconOS-ROS Combination based on a Video Processing Application. bibtex: '@book{Henke_2020, title={Evaluation of a ReconOS-ROS Combination based on a Video Processing Application}, author={Henke, Luca-Sebastian}, year={2020} }' chicago: Henke, Luca-Sebastian. Evaluation of a ReconOS-ROS Combination Based on a Video Processing Application, 2020. ieee: L.-S. Henke, Evaluation of a ReconOS-ROS Combination based on a Video Processing Application. 2020. mla: Henke, Luca-Sebastian. Evaluation of a ReconOS-ROS Combination Based on a Video Processing Application. 2020. short: L.-S. Henke, Evaluation of a ReconOS-ROS Combination Based on a Video Processing Application, 2020. date_created: 2021-03-10T07:07:01Z date_updated: 2022-01-06T06:54:59Z department: - _id: '78' language: - iso: eng status: public supervisor: - first_name: Christian full_name: Lienen, Christian id: '60323' last_name: Lienen - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner title: Evaluation of a ReconOS-ROS Combination based on a Video Processing Application type: bachelorsthesis user_id: '60323' year: '2020' ... --- _id: '20820' author: - first_name: Simon full_name: Thiele, Simon last_name: Thiele citation: ama: Thiele S. Implementing Machine Learning Functions as PYNQ FPGA Overlays.; 2020. apa: Thiele, S. (2020). Implementing Machine Learning Functions as PYNQ FPGA Overlays. bibtex: '@book{Thiele_2020, title={Implementing Machine Learning Functions as PYNQ FPGA Overlays}, author={Thiele, Simon}, year={2020} }' chicago: Thiele, Simon. Implementing Machine Learning Functions as PYNQ FPGA Overlays, 2020. ieee: S. Thiele, Implementing Machine Learning Functions as PYNQ FPGA Overlays. 2020. mla: Thiele, Simon. Implementing Machine Learning Functions as PYNQ FPGA Overlays. 2020. short: S. Thiele, Implementing Machine Learning Functions as PYNQ FPGA Overlays, 2020. date_created: 2020-12-21T13:59:55Z date_updated: 2022-01-06T06:54:40Z department: - _id: '78' language: - iso: eng project: - _id: '1' name: SFB 901 - _id: '82' name: SFB 901 - Project Area T - _id: '83' name: SFB 901 -Subproject T1 status: public supervisor: - first_name: Lennart full_name: Clausing, Lennart id: '74287' last_name: Clausing orcid: 0000-0003-3789-6034 - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner - first_name: Christian full_name: Plessl, Christian id: '16153' last_name: Plessl orcid: 0000-0001-5728-9982 title: Implementing Machine Learning Functions as PYNQ FPGA Overlays type: bachelorsthesis user_id: '74287' year: '2020' ... --- _id: '20821' author: - first_name: Vivek full_name: Jaganath, Vivek last_name: Jaganath citation: ama: Jaganath V. Extension and Evaluation of Python-Based High-Level Synthesis Tool Flows.; 2020. apa: Jaganath, V. (2020). Extension and Evaluation of Python-based High-Level Synthesis Tool Flows. bibtex: '@book{Jaganath_2020, title={Extension and Evaluation of Python-based High-Level Synthesis Tool Flows}, author={Jaganath, Vivek}, year={2020} }' chicago: Jaganath, Vivek. Extension and Evaluation of Python-Based High-Level Synthesis Tool Flows, 2020. ieee: V. Jaganath, Extension and Evaluation of Python-based High-Level Synthesis Tool Flows. 2020. mla: Jaganath, Vivek. Extension and Evaluation of Python-Based High-Level Synthesis Tool Flows. 2020. short: V. Jaganath, Extension and Evaluation of Python-Based High-Level Synthesis Tool Flows, 2020. date_created: 2020-12-21T14:02:42Z date_updated: 2022-01-06T06:54:40Z department: - _id: '78' language: - iso: eng project: - _id: '1' name: SFB 901 - _id: '82' name: SFB 901 - Project Area T - _id: '83' name: SFB 901 -Subproject T1 status: public supervisor: - first_name: Lennart full_name: Clausing, Lennart id: '74287' last_name: Clausing orcid: 0000-0003-3789-6034 - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner - first_name: Christian full_name: Plessl, Christian id: '16153' last_name: Plessl orcid: 0000-0001-5728-9982 title: Extension and Evaluation of Python-based High-Level Synthesis Tool Flows type: mastersthesis user_id: '74287' year: '2020' ... --- _id: '21433' abstract: - lang: eng text: "Modern machine learning (ML) techniques continue to move into the embedded system space because traditional centralized compute resources do not suit certain application domains, for example in mobile or real-time environments. Google’s TensorFlow Lite (TFLite) framework supports this shift from cloud to edge computing and makes ML inference accessible on resource-constrained devices. While it offers the possibility to partially delegate computation to hardware accelerators, there is no such “delegate” available to utilize the promising characteristics of reconfigurable hardware.\r\nThis thesis incorporates modern platform FPGAs into TFLite by implementing a modular delegate framework, which allows accelerators within the programmable logic to take over the execution of neural network layers. To facilitate the necessary hardware/software codesign, the FPGA delegate is based on the operating system for reconfigurable\r\ncomputing (ReconOS), whose partial reconfiguration support enables the instantiation of model-tailored accelerator architectures. In the hardware back-end, a streaming-based prototype accelerator for the MobileNet model family showcases the working order of the platform, but falls short of the desired performance. Thus, it indicates the need for further exploration of alternative accelerator designs, which the delegate could automatically synthesize to meet a model’s demands." author: - first_name: Felix P. full_name: Jentzsch, Felix P. last_name: Jentzsch citation: ama: Jentzsch FP. Design and Implementation of a ReconOS-Based TensorFlow Lite Delegate Architecture.; 2020. apa: Jentzsch, F. P. (2020). Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture. bibtex: '@book{Jentzsch_2020, title={Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture}, author={Jentzsch, Felix P.}, year={2020} }' chicago: Jentzsch, Felix P. Design and Implementation of a ReconOS-Based TensorFlow Lite Delegate Architecture, 2020. ieee: F. P. Jentzsch, Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture. 2020. mla: Jentzsch, Felix P. Design and Implementation of a ReconOS-Based TensorFlow Lite Delegate Architecture. 2020. short: F.P. Jentzsch, Design and Implementation of a ReconOS-Based TensorFlow Lite Delegate Architecture, 2020. date_created: 2021-03-10T07:09:14Z date_updated: 2023-07-09T17:12:52Z department: - _id: '78' language: - iso: eng project: - _id: '1' grant_number: '160364472' name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ' - _id: '82' name: 'SFB 901 - T: SFB 901 - Project Area T' - _id: '83' name: 'SFB 901 - T1: SFB 901 -Subproject T1' status: public supervisor: - first_name: Christian full_name: Lienen, Christian id: '60323' last_name: Lienen - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner - first_name: Christian full_name: Plessl, Christian id: '16153' last_name: Plessl orcid: 0000-0001-5728-9982 title: Design and Implementation of a ReconOS-based TensorFlow Lite Delegate Architecture type: mastersthesis user_id: '398' year: '2020' ... --- _id: '15920' abstract: - lang: eng text: "Secure hardware design is the most important aspect to be considered in addition to functional correctness. Achieving hardware security in today’s globalized Integrated Cir- cuit(IC) supply chain is a challenging task. One solution that is widely considered to help achieve secure hardware designs is Information Flow Tracking(IFT). It provides an ap- proach to verify that the systems adhere to security properties either by static verification during design phase or dynamic checking during runtime.\r\nProof-Carrying Hardware(PCH) is an approach to verify a functional design prior to using it in hardware. It is a two-party verification approach, where the target party, the consumer requests new functionalities with pre-defined properties to the producer. In response, the producer designs the IP (Intellectual Property) cores with the requested functionalities that adhere to the consumer-defined properties. The producer provides the IP cores and a proof certificate combined into a proof-carrying bitstream to the consumer to verify it. If the verification is successful, the consumer can use the IP cores in his hardware. In essence, the consumer can only run verified IP cores. Correctly applied, PCH techniques can help consumers to defend against many unintentional modifications and malicious alterations of the modules they receive. There are numerous published examples of how to use PCH to detect any change in the functionality of a circuit, i.e., pairing a PCH approach with functional equivalence checking for combinational or sequential circuits. For non-functional properties, since opening new covert channels to leak secret information from secure circuits is a viable attack vector for hardware trojans, i.e., intentionally added malicious circuitry, IFT technique is employed to make sure that secret/untrusted information never reaches any unclassified/trusted outputs.\r\nThis master thesis aims to explore the possibility of adapting Information Flow Tracking into a Proof-Carrying Hardware scenario. It aims to create a method that combines Infor- mation Flow Tracking(IFT) with a PCH approach at bitstream level enabling consumers to validate the trustworthiness of a module’s information flow without the computational costs of a complete flow analysis." author: - first_name: Monica full_name: Keerthipati, Monica last_name: Keerthipati citation: ama: Keerthipati M. A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking. Universität Paderborn; 2019. apa: Keerthipati, M. (2019). A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking. Universität Paderborn. bibtex: '@book{Keerthipati_2019, title={A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking}, publisher={Universität Paderborn}, author={Keerthipati, Monica}, year={2019} }' chicago: Keerthipati, Monica. A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking. Universität Paderborn, 2019. ieee: M. Keerthipati, A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking. Universität Paderborn, 2019. mla: Keerthipati, Monica. A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking. Universität Paderborn, 2019. short: M. Keerthipati, A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking, Universität Paderborn, 2019. date_created: 2020-02-17T12:03:40Z date_updated: 2022-01-06T06:52:41Z department: - _id: '78' language: - iso: eng project: - _id: '12' name: SFB 901 - Subproject B4 - _id: '3' name: SFB 901 - Project Area B - _id: '1' name: SFB 901 publisher: Universität Paderborn status: public supervisor: - first_name: Tobias full_name: Wiersema, Tobias id: '3118' last_name: Wiersema - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner - first_name: Sybille full_name: Hellebrand, Sybille id: '209' last_name: Hellebrand orcid: 0000-0002-3717-3939 title: A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking type: mastersthesis user_id: '477' year: '2019' ... --- _id: '14831' author: - first_name: Nithin S. full_name: Sabu, Nithin S. last_name: Sabu citation: ama: Sabu NS. FPGA Acceleration of String Search Techniques in Huge Data Sets. Paderborn University; 2019. apa: Sabu, N. S. (2019). FPGA Acceleration of String Search Techniques in Huge Data Sets. Paderborn University. bibtex: '@book{Sabu_2019, title={FPGA Acceleration of String Search Techniques in Huge Data Sets}, publisher={Paderborn University}, author={Sabu, Nithin S.}, year={2019} }' chicago: Sabu, Nithin S. FPGA Acceleration of String Search Techniques in Huge Data Sets. Paderborn University, 2019. ieee: N. S. Sabu, FPGA Acceleration of String Search Techniques in Huge Data Sets. Paderborn University, 2019. mla: Sabu, Nithin S. FPGA Acceleration of String Search Techniques in Huge Data Sets. Paderborn University, 2019. short: N.S. Sabu, FPGA Acceleration of String Search Techniques in Huge Data Sets, Paderborn University, 2019. date_created: 2019-11-06T12:06:09Z date_updated: 2022-01-06T06:52:07Z department: - _id: '78' language: - iso: eng publisher: Paderborn University status: public supervisor: - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner - first_name: Stefan full_name: Böttcher, Stefan last_name: Böttcher - first_name: Tobias full_name: Wiersema, Tobias id: '3118' last_name: Wiersema title: FPGA Acceleration of String Search Techniques in Huge Data Sets type: mastersthesis user_id: '3118' year: '2019' ... --- _id: '14546' author: - first_name: Tim full_name: Hansmeier, Tim id: '49992' last_name: Hansmeier orcid: 0000-0003-1377-3339 citation: ama: Hansmeier T. Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers. Universität Paderborn; 2019. apa: Hansmeier, T. (2019). Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers. Universität Paderborn. bibtex: '@book{Hansmeier_2019, title={Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers}, publisher={Universität Paderborn}, author={Hansmeier, Tim}, year={2019} }' chicago: Hansmeier, Tim. Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers. Universität Paderborn, 2019. ieee: T. Hansmeier, Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers. Universität Paderborn, 2019. mla: Hansmeier, Tim. Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers. Universität Paderborn, 2019. short: T. Hansmeier, Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers, Universität Paderborn, 2019. date_created: 2019-11-05T14:32:46Z date_updated: 2022-01-06T06:52:02Z department: - _id: '78' - _id: '34' - _id: '7' language: - iso: eng project: - _id: '14' name: SFB 901 - Subproject C2 - _id: '4' name: SFB 901 - Project Area C - _id: '1' name: SFB 901 publisher: Universität Paderborn status: public supervisor: - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner title: Autonomous Operation of High-Performance Compute Nodes through Self-Awareness and Learning Classifiers type: mastersthesis user_id: '477' year: '2019' ...