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2023 International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2023

作者： Van Den Brink, Arvid B. Meteer, Oǧuz Bekooij, Marco J.G. University of Twente Department of Computer Architectures for Embedded Systems Enschede Netherlands Nxp Semiconductors Department of Embedded Software and Signal Processing Eindhoven Netherlands

ISBN: (纸本)9798350322972

The belief propagation algorithm is one of the preferred algorithms for a polar code based decoder that can potentially achieve the lowest latency. Although belief propagation polar code algorithms have the ability for a highly parallelized implementation, they require more iterations to achieve a comparable frame error rate and bit error rate compared to the successive cancellation polar code algorithm. The iterative nature of the belief propagation algorithms also results in a higher computational complexity, i.e. O(N(2log2N-1)) compared to the computational complexity O(Nlog2N) of the successive cancellation decoder algorithm. In this paper we propose several software implementations of belief propagation polar code decoders using the computational complexity reduced belief propagation algorithm and the enhanced loop-weakened belief propagation algorithm, to increase the number of decoded codes per second. Compared to a baseline belief propagation implementation, our proposed radix-2 and radix-4 implementations increase the throughput by approximately 15.4% and 22.04% respectively. This gain is the result of a reduction of arithmetic operations, i.e., additions, compares, and multiplications, which is obtained without a loss in error-correcting performance. © 2023 IEEE.

关键词： Belief propagation

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Association of Camera and Radar Detections Using Neural Networks

Association of Camera and Radar Detections Using Neural Netw...

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IEEE National Conference on Radar

作者： Konstantinos Fatseas Marco J.G. Bekooij Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands Embedded Software and Signal Processing NXP Semiconductors Eindhoven The Netherlands

Automotive radar and camera fusion relies on linear point transformations from one sensor's coordinate system to the other. However, these transformations cannot handle non-linear dynamics and are susceptible to sensor noise. Furthermore, they operate on a point-to-point basis, so it is impossible to capture all the characteristics of an object. This paper introduces a method that performs detection-to-detection association by projecting heterogeneous object features from the two sensors into a common high-dimensional space. We associate 2D bounding boxes and radar detections based on the Euclidean distance between their projections. Our method utilizes deep neural networks to transform feature vectors instead of single points. Therefore, we can leverage real-world data to learn non-linear dynamics and utilize several features to provide a better description for each object. We evaluate our association method against a traditional rule-based method, showing that it improves the accuracy of the association algorithm and it is more robust in complex scenarios with multiple objects.

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Weakly Supervised Semantic Segmentation for Range-Doppler Maps 18

Weakly Supervised Semantic Segmentation for Range-Doppler Ma...

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18th European Radar Conference, EuRAD 2021

作者： Fatseas, Konstantinos Bekooij, Marco J.G. University of Twente Department of Computer Architectures for Embedded Systems Netherlands NXP Semiconductors Department of Embedded Software and Signal Processing Netherlands

ISBN: (纸本)9782874870651

Deep convolutional neural networks (DCNNs) have been successfully applied for object detection and semantic segmentation of radar range-Doppler (RD) maps. However, training a DCNN requires many annotated examples that are costly and difficult to create. In this work we present a method that reduces significantly the manual effort involved in the annotation of RD maps to train a DCNN for segmentation. A 40 times reduction in manual labelling effort is achieved because the annotation of each RD map includes only the class of the objects instead of drawing a polygon around the corresponding cells. The localization of the objects is performed by tracing back from the output to the input of a classification neural network. Experimental results show that our approach achieves robust localization performance in complex real-world urban scenarios as observed with a low-cost automotive radar. Furthermore, we show that our approach performs similarly to DCNNs that are trained with a publicly available dataset in which localization information is provided. © 2022 European Microwave Association (EuMA).

关键词： Convolutional neural networks

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Software Implementation and Performance of a Computational Complexity Reduced Belief Propagation Polar Code Decoder

Software Implementation and Performance of a Computational C...

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), International Conference on

作者： Arvid B. Van Den Brink Oğuz Meteer Marco J.G. Bekooij Department of Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands Department of Embedded Software and Signal Processing NXP Semiconductors Eindhoven The Netherlands

The belief propagation algorithm is one of the preferred algorithms for a polar code based decoder that can potentially achieve the lowest latency. Although belief propagation polar code algorithms have the ability for a highly parallelized implementation, they require more iterations to achieve a comparable frame error rate and bit error rate compared to the successive cancellation polar code algorithm. The iterative nature of the belief propagation algorithms also results in a higher computational complexity, i.e. O(N(2log 2 N-1)) compared to the computational complexity O(Nlog 2 N) of the successive cancellation decoder algorithm. In this paper we propose several software implementations of belief propagation polar code decoders using the computational complexity reduced belief propagation algorithm and the enhanced loop-weakened belief propagation algorithm, to increase the number of decoded codes per second. Compared to a baseline belief propagation implementation, our proposed radix-2 and radix-4 implementations increase the throughput by approximately 15.4% and 22.04% respectively. This gain is the result of a reduction of arithmetic operations, i.e., additions, compares, and multiplications, which is obtained without a loss in error-correcting performance.

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Energy-Efficient Radix-4 Belief Propagation Polar Code Decoding Using an Efficient Sign-Magnitude Adder and Clock Gating

Energy-Efficient Radix-4 Belief Propagation Polar Code Decod...

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Euromicro Symposium on Digital System Design

作者： Oğuz Meteer Arvid Van Den Brink Marco J.G. Bekooij Department of Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands Department of Embedded Software and Signal Processing NXP Semiconductors Eindhoven The Netherlands

ISBN: (数字)9781665474047

ISBN: (纸本)9781665474054

Polar encoding is the first information coding method that has been proven to achieve channel capacity for binary-input discrete memoryless channels. Since its introduction, much research has been done on improving decoding performance, execution time and energy efficiency. Classic belief propagation uses radix-2 decoding, but a recent study proposed radix-4 decoding which reduces memory usage by 50%. However a drawback is its higher computational complexity, negatively impacting energy usage and throughput. In this paper we present an energy-efficient radix-4 belief propagation polar decoder architecture that uses a new sign-magnitude adder that does not require conversion to two's complement and back. On top of that we also propose using clock gating of input values by checking if all $R$ inputs of the decoder are zero. These two key contributions lead to a more energy -efficient design that is smaller and has higher maximum clock speed and throughput. Post-layout simulation results show that compared to the previously proposed 1024-bit radix-4 belief propagation polar code decoder, our decoder uses between 30.22 % and 32.80 % less power and is 5.2 % smaller at the same clock speed. Also, our design can achieve a 15.7% higher clock speed at which it is still up to 10.76% more power efficient and 4.8% smaller.

关键词： Simulation Switches Energy efficiency Encoding Decoding Polar codes Adders

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High-Level Synthesis of Digital Circuits from Template Haskell and SDF-AP

arXiv

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arXiv 2025年

作者： Folmer, Hendrik H. de Groote, Robert Bekooij, Marco J.G. University of Twente CAES: Computer Architectures for Embedded Systems Enschede Netherlands Saxion Hogeschool Enschede Netherlands

Functional languages as input specifications for HLS-tools allow to specify data dependencies but do not contain a notion of time nor execution order. In this paper, we propose a method to add this notion to the functional description using the dataflow model SDF-AP. SDF-AP consists of patterns that express consumption and production that we can use to enforce resource usage. We created an HLS-tool that can synthesize parallel hardware, both data and control path, based on the repetition, expressed in Higher-Order Functions, combined with specified SDF-AP patterns. Our HLS-tool, based on Template Haskell, generates an Abstract Syntax Tree based on the given patterns and the functional description uses the Clash-compiler to generate VHDL/Verilog. Case studies show consistent resource consumption and temporal behavior for our High-Level Synthesis (HLS). A comparison with a commercially available HLS-tool shows that our HLS tool outperforms in terms of latency and sometimes in resource consumption. The method and tool presented in this paper offer more transparency to the developer and allow to specify more accurately the synthesized hardware compared to what is possible with pragmas of the Vitis HLS-tool. Copyright © 2025, The Authors. All rights reserved.

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Reachability Analysis of Hybrid Automata with Clocked Linear Dynamics 19

Reachability Analysis of Hybrid Automata with Clocked Linear...

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22nd International Workshop on Software and Compilers for embedded systems, SCOPES 2019

作者： El Hakim, Viktorio S. Bekooij, Marco J. G. Computer Architectures for Embedded Systems University of Twente Enschede Netherlands Algorithms and Software Innovation NXP Semiconductors Eindhoven Netherlands

ISBN: (纸本)9781450367622

Disributed control systems often exhibit aperiodic sampling behavior due to varying communication delays and execution times. In such cases traditional analysis methods fall short because the functional and temporal behaviors need to be analyzed simultaneously. Therefore such systems are often modeled by Hybrid Automata (HA) with clock and non-clock variables, and verified using reachability analysis. However, modern reachability tools introduce a large overapproximation error because non-clock variables, as well as clock variables, are equally treated by the algorithm. In this paper we present a reachability algorithm which exploits the explicit separation of clock and non-clock variables in the Hybrid Automata with Clocked Linear Dynamics (HA-CLD) subclass, as well as restricting that guard and invariant constraints can only be specified in the HA-CLD model for clock variables. These properties of HA-CLD allow independent computation of tight reachable set over-approximations, in the form of flow-pipes, of clock and non-clock variables. A computationaly efficient and tight intersection operation is obtained by relating segments of the clock flow-pipe with segments of the non-clock flow-pipe. We demonstrate the effectiveness of our approach using two benchmarks, in the context of verifying stability. From the results it can be concluded that our reachability approach obtains significantly tighter results with an up-to 65 times smaller run-time compared to the start-of-the-art model checker SpaceEx. © 2019 ACM.

关键词： Clocks

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Neural Network Based Multiple Object Tracking for Automotive FMCW Radar

Neural Network Based Multiple Object Tracking for Automotive...

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IEEE International Conference on Radar

作者： Konstantinos Fatseas Marco J.G. Bekooij Department of Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands

ISBN: (数字)9781728126609

ISBN: (纸本)9781728137858

Tracking multiple objects from radar data poses several difficulties. In recent work, it has been shown that an algorithm consisting of a thresholding, clustering and multiple object tracking step using the Kalman filter can track multiple objects. Afterwards, features can be extracted from the range-Doppler map to classify the tracked objects. However, this method needs many heuristics on each stage and in the process, information which could be useful in subsequent steps is *** overcome these issues, in this paper we introduce a neural network based multiple object tracker. This removes the need for a separate thresholding, clustering, feature extraction and classification step because it combines those into one step which uses a neural network based on the You Only Look Once (YOLO) object detection system to classify and localize objects. The output of the neural network is fed into a Kalman filter based tracker to manage the *** show that a convolutional neural network trained as an object detector can be successfully applied in the radar domain and we show the advantages of our neural network based multiple object tracker over the clustering based method for specific scenarios. These scenarios include tracking objects that cross each other and tracking objects while the radar is non-stationary.

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Stability Verification of Self-Timed Control systems Using Model-Checking

Stability Verification of Self-Timed Control Systems Using M...

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Euromicro Symposium on Digital System Design

作者： Viktorio Semir el Hakim Marco Jan Gerrit Bekooij Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands

ISBN: (纸本)9781538673782

Cyber-physical control systems are typically time-triggered because the Analog to Digital (A/D) and Digital to Analog (D/A) converters are triggered by a periodic clock. This enables analytical stability analysis of closed-loop models in case the plant and controller are linear. However ensuring periodic sampling requires that a sampling period is selected larger than the Worst-Case Execution Times (WCETs) of the digital control tasks. Unfortunately, low sampling rates must be selected as a result of loose WCET bounds especially if multi-processor hardware is applied with shared data caches and SDRAM memory. In this paper we propose a model-checking based stability analysis approach for control systems that sample aperiodically. Our approach is targetting self-timed systems, where the A/D and D/A converters are driven by internal events, such as the completion of a task, which also trigger subsequent task executions. During self-timed execution the average sampling period tends to be significantly smaller than possible in time-triggered mode, and as a result the control performance is improved significantly. Self-timed systems also allow the use of a running average workload characterization of the tasks which is tighter than a WCET characterization, and which can greatly improve the accuracy of the stability analysis results. We show using two self-timed control systems that control performance in terms of stability and settling time improves for self-timed systems when the running average workload characterization is applied. Furthermore, we point at an essential feature that is needed for asymptotic stability analysis which is missing in well known model checkers such as SpaceEx.

关键词： Stability analysis Task analysis Asymptotic stability Control systems Analog-digital conversion Digital-analog conversion Analytical models

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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