---
_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'
...