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检索条件"任意字段=International Conference on Embedded Computer Systems -Architectures, Modeling and Simulation"

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international conference on modeling, simulation and Optimization, CoMSO 2022

International Conference on Modeling, Simulation and Optimiz...

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international conference on modeling, simulation and Optimization, CoMSO 2022

ISBN: (纸本)9789819968657

The proceedings contain 45 papers. The special focus in this conference is on modeling, simulation and Optimization. The topics include: Enhancement and Gray-Level Optimization of Low Light Images;Prediction of Liver Disease Using Machine Learning Approaches Based on KNN Model;Modelling of embedded Cracks by NURBS-Based Extended Isogeometric Analysis;a New Version of Artificial Rabbits Optimization for Solving Complex Bridge Network Optimization Problem;regression Analysis on Synthesis of Biodiesel from Rice Bran Oil;a Study on Vision-Based Human Activity Recognition Approaches;in-Store Monitoring of Harvested Tomatoes Using Internet of Things;A Compact Microstrip Hexagonal Patch Antenna with a Slotted Ground Plane for RF Energy Harvesting Applications;on P-refinement in Topology Optimization;hierarchical Aadhaar-Based Anonymous eSign Based on Group Signatures;swarm Intelligence for Estimating Model Parameters in Thermodynamic systems;development of a Protocol on Various IoT-Based Devices Available for Women Safety;a Review on Indian Language Identification Using Deep Learning;markov Process Based IoT Model for Road Traffic Prediction;optimization of Process Parameters in Biodiesel Production from Waste Cooking Oil Using Taguchi-Grey Relational Analysis;a Novel D-Latch Design for Low-Power and Improved Immunity;anonymous and Privacy Preserving Attribute-Based Decentralized DigiLocker Using Blockchain Technology;FIFO Memory Implementation with Reduced Metastability;Diabetic Retinopathy Detection Using Ensemble of CNN architectures;computational Analysis of Darrieus Vertical Axis Wind Turbines for Exhaust Air Energy Extraction;narrow Band 5G Antenna;rectangular and Cylindrical Slotted Microstrip Patch Antenna Design for Biomedical Application;An Implementation of Machine Learning-Based Healthcare Chabot for Disease Prediction (MIBOT);fabrication of Patient Specific Distal Femur with Additive Manufacturing.

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FAA+RTS: Designing Fault-Aware Adaptive Real-Time systems —From Specification to Execution— 24th

FAA+RTS: Designing Fault-Aware Adaptive Real-Time Systems —...

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24th international conference on embedded computer systems: architectures, modeling, and simulation, SAMOS 2024

作者： Miedema, Lukas Sapra, Dolly Novobilsky, Petr Altmeyer, Sebastian Grelck, Clemens Pimentel, Andy D. University of Amsterdam Amsterdam Netherlands Q-media s.r.o. Prague Czech Republic University of Augsburg Augsburg Germany Friedrich Schiller University Jena Jena Germany

ISBN: (纸本)9783031783760

Large-scale cyber-physical systems, such as those for subway transportation or air traffic control, are becoming increasingly complex and often need to operate without human intervention. At the same time, these systems are subject to high requirements on the timing behavior and fault-tolerance. Consequently, the detection and mitigation of both hard and soft errors is of high importance in the already complex systems design process. The main challenges towards fault-aware real-time systems is the overall system design, in which the sheer size of the state-space and the system’s complexity exceeds the capacity of today’s development tools. In this paper, we present a new holistic methodology called FAA+RTS, for designing fault-aware adaptive real-time systems. We cover the entire path from system specification using a coordination language, via design-space exploration and task scheduling to the adaptive fault-aware runtime environment. Mitigating both hard and soft errors addresses competing requirements. Improving soft error tolerance (through redundant execution) may accelerate the aging process of silicon, thus expediting hard error failures. FAA+RTS is a novel solution as it integrates previously-isolated methods for dealing with multiple constraints into a single framework, presenting a single overview of all possible trade-offs to the application designer. This integration ensures that all aspects of system design, from specification to execution, are cohesively addressed, resulting in a robust and reliable system. We exemplify FAA+RTS using industrial-sized autonomous subway transportation system as a use-case. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Air traffic control

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Study of DNN-Based Ragweed Detection from Drones 22nd

Study of DNN-Based Ragweed Detection from Drones

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22nd international conference on embedded computer systems - architectures, modeling, and simulation (SAMOS)

作者： Lechner, Martin Steindl, Lukas Jantsch, Axel TU Wien Christian Doppler Lab Embedded Machine Learning Inst Comp Technol A-1040 Vienna Austria

ISBN: (纸本)9783031150746;9783031150739

Ambrosia artemisiifolia, also known as ragweed, is an invasive weed species that aggressively spreads across Europe. 4-5% of the population suffers from strong allergic reactions to its pollen. This work studies the use of aerial drones equipped with highly compressed deep neural networks (DNNs) to scan large areas of vegetation for ragweed with high speed and precision. Compared to the manual approaches with an estimated survey cost of roughly 860 EUR/km(2), the proposed technique can cut the cost of ragweed detection and monitoring by orders of magnitudes. Aerial drones are heavily limited by their battery capacity and thus require an efficient computation platform. As such, it is not possible to use standard DNN models due to memory and computational constraints. Offloading the workload into data centers introduces new issues as the drones may operate in rural areas with poor network connectivity. To overcome these challenges, we train state-of-the-art object detection and segmentation models on a ragweed dataset. The best performing segmentation models were compressed using shunt connections, fine-tuned with knowledge distillation, and further optimized with Nvidias TensorRT library for deployment on an Nvidia Jetson TX2. The highest accuracy models still achieve between 200 ms and 400 ms inference latency, enabling real-time ragweed survey and potentially allowing more advanced autonomous eradication use cases.

关键词： Machine learning DNN Autonomous machines Drones

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Cross-domain Modelling of Verification and Validation Workflows in the Large Scale European Research Project VALU3S Invited Paper 21st

Cross-domain Modelling of Verification and Validation Workfl...

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21st international conference on embedded computer systems - architectures, modeling, and simulation (SAMOS)

作者： Bauer, Thomas Agirre, Joseba A. Fuercho, David Herzner, Wolfgang Hruska, Bob Karaca, Mustafa Pereira, David Proenca, Jose Schlick, Rupert Sicher, Robert Smrcka, Ales Yayan, Ugur Sangchoolie, Behrooz Fraunhofer IESE Kaiserslautern Germany Mondragon Univ Arrasate Mondragon Spain NXP Semicond Hamburg Germany AIT Austrian Inst Technol Vienna Austria Lieber Lieber Vienna Austria Inovasyon Muhendislik Ltd Sti Eskisehir Turkey ISEP Porto Portugal Brno Univ Technol Brno Czech Republic RISE Res Inst Sweden Gothenburg Sweden

ISBN: (纸本)9783031045806;9783031045790

The complexity of systems continues to increase rapidly, especially due to the multi-level integration of subsystems from different domains into cyber-physical systems. This results in special challenges for the efficient verification and validation (V&V) of these systems with regard to their requirements and properties. In order to tackle the new challenges and improve the quality assurance processes, the V&V workflows have to be documented and analyzed. In this paper, a novel approach for the workflow modelling of V&V activities is presented. The generic approach is tailorable to different industrial domains and their specific constraints, V&V methods, and toolchains. The outcomes comprise a dedicated modelling notation (VVML) and tool-support using the modelling framework Enterprise Architect for the efficient documentation and implementation of workflows in the use cases. The solution enables the design of re-usable workflow assets such as V&V activities and artifacts that are exchanged between workflows. This work is part of the large scale European research project VALU3S that deals with the improvement and evaluation of V&V processes in different technical domains, focusing on safety, cybersecurity, and privacy properties.

关键词： Verification and validation Safety Cybersecurity Privacy Automated systems V&V workflows V&V tool chains

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37th international conference on Architecture of Computing systems, ARCS 2024

37th International Conference on Architecture of Computing S...

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37th international conference on Architecture of Computing systems, ARCS 2024

ISBN: (纸本)9783031661457

The proceedings contain 23 papers. The special focus in this conference is on Architecture of Computing systems. The topics include: The Power of Training: How Different Neural Network Setups Influence the Energy Demand;an Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing;Modifiable Artificial DNA - Change Your System’s ADNA at Any Time;From Structured to Unstructured: A Comparative Analysis of computer Vision and Graph Models in Solving Mesh-Based PDEs;enhancing Maritime Behaviour Analysis Through Novel Feature Engineering and Digital Shadow Modelling: A Case Study in the Kiel Fjord;Synthesizing Training Data for Intelligent Weed Control systems Using Generative AI;towards the Online Reconfiguration of a Dependable Distributed On-Board computer;An Organic Computing Approach for CARLA Simulator;Idle is the New Sleep: Configuration-Aware Alternative to Powering Off FPGA-Based DL Accelerators During Inactivity;On-the-Fly CT Image Pre-processing on MPSoC-FPGAs;AccProf: Increasing the Accuracy of embedded Application Profiling Using FPGAs;accelerating WebAssembly Interpreters in embedded systems Through Hardware-Assisted Dispatching;Exploring the ARM Coherent Mesh Network Topology;comparison of a Binary Signed-Digit Adder with Conventional Binary Adder Circuits on Layout Level;Case Studies on the Impact and Challenges of Heterogeneous NUMA architectures for HPC;a Hierarchical modeling Approach for Assessing the Reliability and Performability of Burst Buffers;Generative-Based Algorithm for Data Clustering on Hybrid Classical-Quantum NISQ Architecture;improving Memory Dependence Prediction with Static Analysis;Atalanta: Open-Source RISC-V Microcontroller for Rust-Based Hard Real-Time systems;software-Based Erasure-Tolerant Coding with Buffering and Compression;determination of Optimal H-Matrices for 2-Bit Error Correcting Codes.

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Mitigating the Effects of RRAM Process Variation on the Accuracy of Artificial Neural Networks 21st

Mitigating the Effects of RRAM Process Variation on the Accu...

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21st international conference on embedded computer systems - architectures, modeling, and simulation (SAMOS)

作者： Fritscher, Markus Knoedtel, Johannes Mallah, Maen Pechmann, Stefan Quesada, Emilio Perez-Bosch Rizzi, Tommaso Wenger, Christian Reichenbach, Marc Friedrich Alexander Univ FAU Chair Comp Architecture Nurnberg Germany Fraunhofer IIS Erlangen Germany Univ Bayreuth Chair Commun Elect Bayreuth Germany IHP Leibniz Inst Innovat Mikroelekt Frankfurt Ode Frankfurt Germany BTU Cottbus Senftenberg Cottbus Germany

ISBN: (纸本)9783031045806;9783031045790

Weight storage is a key challenge in the efficient implementation of artificial neural networks. Novel memory technologies such as RRAM are able to greatly improve density and introduce non-volatility and multibit capabilities to this component of ANN accelerators. The usage of RRAM in this domain comes with downsides, mainly caused by cycle-to-cycle and device-to-device variability leading to erroneous readouts, greatly affecting digital systems. ANNs have the ability to compensate for this by their inherent redundancy and usually exhibit a gradual deterioration in the accuracy of the task at hand. This means, that slight error rates can be acceptable for weight storage in an ANN accelerator. In this work we link device-to-device variability to the accuracy of an ANN for such an accelerator. From this study, we can estimate how strongly a certain net is affected by a certain device parameter variability. This methodology is then used to present three mitigation strategies and to evaluate how they affect the reaction of the network to variability: a) Dropout Layers b) Fault-Aware Training c) Redundancy. These mitigations are then evaluated by their ability to improve accuracy and to lower hardware overhead by providing data for a real-word example. We improved this network's resilience in such a way that it could tolerate double the variation in one of the device parameters (standard deviation of the oxide thickness can be 0.4 nm instead of 0.2 nm while maintaining sufficient accuracy.)

关键词： Memristors RRAM Device variation Mixed analog digital integrated circuits simulation Neural networks

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Modelling and simulation-Based Evaluation of Twinning architectures and Their Deployment 14

Modelling and Simulation-Based Evaluation of Twinning Archit...

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19th international conference on Software Technologies, ICSOFT 2024

作者： Paredis, Randy Vangheluwe, Hans University of Antwerp Department of Computer Science Middelheimlaan 1 Antwerp Belgium

ISBN: (纸本)9789897587061

The Twinning paradigm –subsuming Digital Models, Digital Shadows and Digital Twins– is a powerful enabler for analyzing, verifying, deploying and maintaining complex Cyber-Physical systems (CPSs). Throughout the (currently quite ad-hoc) creation of such systems, a plethora of choices impacts the functionality and performance of the realized Twinning system comprised of the actual system under study and its twin. The choices that are made have a high impact on the required investment when creating the twin, most notably on the development time and deployment cost. This is especially true when multiple iterations are needed to find the most appropriate level(s) of abstraction and detail, architecture, technologies and tools. As a core contribution, this work follows a Model-Based systems Engineering methodology: before realizing a Twinning architecture, Discrete EVent system Specification (DEVS) models for deployed architecture alternatives are constructed and simulated, to evaluate their suitability. A simple use-case of a ship moving in one dimension is used as a running example. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Investments

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Efficient Operator Sharing Modulo Scheduling for Sum-Product Network Inference on FPGAs 21st

Efficient Operator Sharing Modulo Scheduling for Sum-Product...

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21st international conference on embedded computer systems - architectures, modeling, and simulation (SAMOS)

作者： Kruppe, Hanna Sommer, Lukas Weber, Lukas Oppermann, Julian Axenie, Cristian Koch, Andreas Tech Univ Darmstadt Embedded Syst & Applicat Grp Darmstadt Germany Huawei Munich Res Ctr Intelligent Cloud Technol Lab Munich Germany

ISBN: (纸本)9783031045806;9783031045790

Probabilistic models are receiving increasing attention as a complementary alternative to more widespread machine learning approaches such as neural networks. One particularly interesting class of models, so-called Sum-Product Networks (SPNs), combine the expressiveness of probabilistic models with tractable inference, making them an interesting candidate for use in real-world applications. Previously, inference in SPNs has successfully been accelerated by fully pipelined FPGA-based hardware. However, with these approaches, the maximum size of the SPN for FPGA acceleration has effectively been limited by the fully spatial mapping of arithmetic operations into hardware and the number of available resources in the FPGA. In this work, we present an extended and specialized modulo scheduling algorithm based on Integer Linear Programming (ILP) for time-multiplexed sharing of hardware arithmetic operators in the SPN inference accelerator. In addition and in order to scale the scheduling to large SPN graphs, we combine the scheduling algorithm with a graph-partitioning heuristic, exploiting the graph structure of SPNs. The combination of heuristic graph partitioning and ILP-based scheduling allows generating pipe-lined accelerators with the best possible initiation interval, while limiting the resource utilization to pre-set bounds. The evaluation discusses the effect different parameters have on convergence time and solution quality. A performance comparison shows that the FPGA improves the inference throughput over a comparable CPU- and GPU platform by a factor (geo.-mean) of 4.4x and 1.7x, respectively.

关键词： FPGA Machine learning Probabilistic model Sum-product network Modulo scheduling Graph partitioning

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Energy-Efficient BLAS L1 Routines for FPGA-Supported HPC Applications 23rd

Energy-Efficient BLAS L1 Routines for FPGA-Supported HPC App...

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23rd international conference on embedded computer systems: architectures, modeling, and simulation, SAMOS 2023

作者： Theodoropoulos, Dimitris Pekridis, Giorgos Miliadis, Panagiotis Pnevmatikatos, Dionisios Institute of Communication and Computation Systems National Technical University of Athens Athens Greece

ISBN: (纸本)9783031460760

Vector-based calculations dominate computations in scientific and industrial HPC software. However, up to now there are limited options for mapping them quickly and efficiently on FPGA-supported systems. This work presents a first set of FPGA kernels for mapping a large set of the BLAS L1 routine set on HPC FPGAs. All kernels retain exactly the same interface with respect to their software counterpart routine, whereas they can be configured in terms of internal computing engines. Results show that our kernels can achieve a speed up and performance-per-Watt ratio of up to 7× and 45× respectively, compared to Intel’s MKL routines when executed on server-class machines. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Field programmable gate arrays (FPGA)

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modeling Hydrodynamic Diffusion Processes using Spatio-Temporal Deep Neural Networks with Environmental Physical-Coupled Constraints

Modeling Hydrodynamic Diffusion Processes using Spatio-Tempo...

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2024 IEEE international conference on systems, Man, and Cybernetics, SMC 2024

作者： Jia, Lei Yen, Neil Pei, Yan Graduate School of Computer Science and Engineering University of Aizu Fukushima Aizuwakamatsu965-8580 Japan

ISBN: (纸本)9781665410205

The simulation and analysis of complex spatiotemporal systems are crucial for expressing and solving chaotic dynamical systems such as those in Earth and environmental sciences. Understanding and computing physical processes, re-actions, or substance transport typically relies on control equations. This paper aims to explore a novel research paradigm by enhancing the physical network coupling structure to construct predictive models for fluid dynamics systems, simulating spatiotemporal dynamical processes of substance transformation in the domain of environmental physics. In particular, when addressing problems involving the non-homogeneous 2D fluid dynamics equations, the characteristic parameters of the phys-ical processes were redefined. This was achieved by encoding hard boundary conditions and designing appropriate neural network architectures to mitigate over-fitting issues during the prediction of parameterized dynamical systems. Comparative experiments involving five benchmark physics-informed neural network methods emphasize the significant improvement in capturing time-varying features and prediction accuracy brought by the proposed approach. Through various water cycle scenarios, the model's estimation ability for diffusion fields is validated, focusing on analyzing the influence of data errors and sample size on the computational results of this deep neural network. Notably, the proposed method exhibits higher robustness to outlier observations under extreme conditions. © 2024 IEEE.

关键词： Temporal logic

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