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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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A framework for the extension of devs with sensor fusion capabilities

A framework for the extension of devs with sensor fusion cap...

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2020 Spring simulation Multiconference, SpringSim 2020

作者： Boi-Ukeme, Joseph Wainer, Gabriel Department of Systems and Computer Engineering Carleton University 1125 Colonel By Drive OttawaON Canada

ISBN: (纸本)9781713812883

Sensor fusion is a technique used to combine sensor data and improve the description of the physical property measured by these sensors. Sensors working alone could provide data that is erroneous, incomplete and uncertain. Several algorithms have been developed for sensor fusion, some of which are complex to understand and difficult to implement. The extensive list of algorithms often leaves designers confused about what choices to make as regards which algorithm is best and this discourages them from implementing sensor fusion. In this paper, we propose a generic sensor fusion framework to facilitate the implementation of sensor fusion algorithms using the Discrete-Event modeling of embedded systems (DEMES) which is a model-based development methodology for cyber-physical systems based on discrete-event systems specifications (DEVS). © 2020 Society for modeling & simulation international (SCS)

关键词： embedded systems

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Digital Holographic Based Food Supply Post Flood Assessment System

Digital Holographic Based Food Supply Post Flood Assessment ...

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international conference on Power, Energy, Control and Transmission systems (ICPECTS)

作者： C. Jeeva Giraja Shankar Chaurasia Marshal A Raghavendra R P Sabarikrishnan S Dharani Kumar P Department of Electrical and Electronics Sri Sairam Engineering College Chennai India Department of Electrical and Electronics SRM Institute of Science & Technology Ghaziabad U.P India Mphasis Chennai India Super auto forge pvt ltd Chennai India Cognizant Technologies Solution Corp. Chennai India Wipro technologies Chennai India

ISBN: (纸本)9781665462761

There are many possible applications for virtual reality, which is regarded as the apex of human-computer interactions. In order to improve the standardization and automation of disaster operation management, a novel emergency management strategy based on activity network technology is presented. First, the emergency plan is constructed utilizing technology called an activity network and emergency response activities. Straight lines connecting waypoints of interest can be used to depict a virtual journey, although this basic model does not adequately capture ordinary user activity. We put the model into a framework that may be used to reroute medical and food assistance in various real-world and virtual settings. It is helpful for evaluating redirected parameters in different circumstances. In our concept, a flood scenario is the emergency that is needed, and the virtual hologram aids the user in gathering data from each person who requires assistance utilizing a wireless sensor network. The electronic civilization has undergone significant transformation thanks to embedded technology, which has a sizable community. Microcontrollers can be used by embedded systems to collectdata, process it, and produce reliable results. Intelligent principal layout and precise analysis are provided by simulation software when designing a project.

关键词： Solid modeling Wireless sensor networks Virtual reality Standardization Emergency services Software Software reliability

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GPU Parallelization and Optimization of a Combustion simulation Application

GPU Parallelization and Optimization of a Combustion Simulat...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Zhixiang Liao Yongzhou Liu Yonggang Che State Key Laboratory of High Performance Computing Institute for Quantum Information College of Computer National University of Defense Technology Changsha China

Graphics processing units (GPUs) are widely used in the area of scientific computing. While GPUs provide much higher peak performance, efficient implementation of real applications on the GPU architectures is still a non-trivial task. It is crucial to realize efficient solution algorithms that can better utilize GPU architectures. This paper presents our efforts in parallelizing and optimizing LESAP, a CFD application for scramjet combustion simulation, on NVIDIA GPUs. The GPU parallelization is realized based on the CUDA programming model, with a data-parallel implicit time-marching method that is efficient on the GPU architecture. Furthermore, shared memory and redundant calculation are proposed to reduce memory access overhead during GPU computation, and data transfer between CPU and GPU is optimized by packing the data to be transferred. The experimental results show that the GPU version, when runs on four V100 GPUs, achieves a speedup of 11.26 times compared to the CPU version that runs on two 24-core Intel Skylake Gold 6240R CPUs. Excellent parallel scalability across multiple GPUs is also observed.

关键词： Gold Smart cities Computational modeling Graphics processing units computer architecture Combustion Central Processing Unit

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A co-simulation approach for the evaluation of multi-core embedded platforms in cyber-physical systems

A co-simulation approach for the evaluation of multi-core em...

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2020 Summer computer simulation conference, SCSC 2020, Held at the 2020 Summer simulation Multi-conference, SummerSim 2020

作者： Vanommeslaeghe, Yon van Acker, Bert Vanherpen, Ken de Meulenaere, Paul Flanders Make - AnSyMo/CoSys Core Lab Faculty of Applied Engineering University of Antwerp Antwerp Belgium

ISBN: (纸本)9781713819462

The increasing complexity of Cyber-Physical systems (CPS) causes a shift from traditional single-core embedded platforms to complex multi-core or even heterogeneous platforms to meet the performance requirements. However, the deployment of control or monitoring algorithms on such platforms is not straightforward as the temporal behaviour of the embedded platform can affect the functional behaviour of these algorithms. In this paper, we propose a co-simulation strategy for multi-core embedded platforms. This allows us to evaluate the impact of the deployment on the behaviour of the algorithm early on in the design process, reducing the risk of costly re-engineering and allowing for a more agile design process. Our approach is validated using an example case in different deployment scenarios, after which its applicability is demonstrated using a real-world use case. ©2020 Society for modeling & simulation international (SCS)

关键词： Cyber Physical System

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Incentivizing Smart Vehicles For Autonomous Driving HD Maps using predictive analytics

Incentivizing Smart Vehicles For Autonomous Driving HD Maps ...

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Machine Vision, Image Processing and Imaging Technology (MVIPIT), international conference on

作者： Muhammad Ilyas Khattak Yuan Hui Inam Ullah Ajmal Khan Ayaz Ahmad School of Control Science and Engineering Shandong University Jinan City Shandong province P.R. China Depart. of Computer Science Shandong Jianzhu University (SDJZU) Jinan City Shandong province P. R. China AI & Big data Depart. Woosong University Daejeon South Korea Depart. of Electrical and Computer Engineering COMSATS Institute of Information Technology (CIIT) Wah Cantt Pakistan

ISBN: (数字)9798350306545

ISBN: (纸本)9798350306552

Recent advancements in distributed data storage, colloborative processing capabilities, and their architectural design have a profound influence on our daily lives, simplifying the process of hosting computation-intensive software applications. A single software hosting device, for instance, an Onboard Computation Unit (OBCU) of an autonomous vehicle, on the other hand, can’t keep up with the growing need for diverse requirements of computing architectures and processing power of such applications. For example, the real-time handling and generation of HD maps is one such crucial and highly computation-intensive application for autonomous vehicles. For this purpose, an efficient solution is to rely on the computing power of adjacent resource-rich nodes. Hence, the use of a latency-aware predictive analytics-based computation task offloading method has a vital significance, especially with the advent of Vehicular Edge and Fog Computing (VEFC). VEFC models pool redundant computational resources in close proximity. It, however, faces several challenges. The stochastic nature of vehicular networks, intricate heterogeneity at several levels, and the uncertainty of time-sensitive applications for the timely completion of tasks impede the VEFC’s efficiency. We developed a computation offloading framework that timely alleviates the computing-resource-deficit devices by deploying vehicles as fog-nodes commensurate with the minimum latency requirements of advanced vehicular applications, especially computation-intensive HD map handling, and generation in real-time. Our technique is a greedy heuristic method that works in small, discrete steps instead of solving the entire optimization problem holistically. We used Monte Carlo simulation to show that our approach had an overall response time of under-300 milliseconds compared to other baseline methods.

关键词： Processor scheduling Computational modeling Scheduling Real-time systems Software Resource management Time factors

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Formal modeling and Verification of the Sequential Kernel of an embedded Operating System

Formal Modeling and Verification of the Sequential Kernel of...

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international conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Zhang Haitao Chen Lirong Luo Lei School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781665413657

A formal computational model is presented for the sequential kernel of an automotive embedded real-time operating system, which provides infrastructural mechanism to support the isolation between applications and the operating system, as well as the isolation between executive entities such as tasks and ISRs (Interrupt Service Routines) in applications. The target embedded system is modeled at the granularity of isolated memory regions and stacks. Tasks, nested ISRs and the preempt-able part of the operating system (i.e. system services) are concurrent entities executing on dedicated memory regions and stacks determined by the sequential kernel. States of these entities can be correctly saved and restored in isolated stacks and in the kernel data structures, such that the control flow changes among them can be correctly made. The implementation correctness theorem of the kernel is established along with the corresponding simulation relationship and implementation invariants. According to the features of the model and the related implementation languages, the kernel is formally verified with the theorem prover Isabelle/HOL.

关键词： embedded systems Computational modeling Memory management Information processing Media Data structures Real-time systems

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Execution time modeling for CNN inference on embedded GPUs 21

Execution time modeling for CNN inference on embedded GPUs

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2021 Worshop on Drone systems Engineering and Rapid simulation and Performance Evaluation: Methods and Tools, DroneSE and RAPIDO 2021

作者： Bouhali, Noureddine Ouarnoughi, Hamza Niar, Smail El Cadi, Abdessamad Ait Université Polytechnique Hauts-de-France Valenciennes France

ISBN: (纸本)9781450389525

Machine learning is one of the most cutting edge methods in computer vision. Convolutional Neural Networks (CNN) in particular are widely used in edge computing based applications such as autonomous driving for image recognition or object tracking. Different constraints exist in this application area such as real-time, energy consumption, memory resources, etc. Choosing the optimal CNN for each GPU at hand is really hard to do, while maintaining high levels of accuracy and performance. This makes prior knowledge about the execution time a necessary prerequisite information before the final deployment of the CNN on the edge GPU platform. In this paper, we compare 5 execution time prediction models on a large set of CNNs-based applications. The tested predictors use machine learning regression approach. The proposed methodology is based on the utilization of high level CNN features. At the opposite of state-of-the-art approaches, no implementation or profiling on the hardware is required. A Mean Absolute Percentage Error (MAPE) of 5% using Support Vector Regression and Artificial Neural Networks has been obtained in the experiments. Our comparison shows the efficiency of these models to rapidly explore a large space of CNN models or Hardware configurations. © 2021 ACM.

关键词： Convolutional neural networks

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System-Level modeling and simulation of MPSoC Run-Time Management Using Execution Traces Analysis 19th

System-Level Modeling and Simulation of MPSoC Run-Time Manag...

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19th international conference on embedded computer systems: architectures, modeling, and simulation (SAMOS)

作者： Yang, S. Le Nours, S. Real, M. Mendez Pillement, S. Univ Nantes CNRS IETR UMR 6164 F-44000 Nantes France

ISBN: (纸本)9783030275624;9783030275617

Dynamic management of modern Multi-Processors System on Chip (MPSoC) become mandatory for optimization purpose. Evaluation of these managers is essential early in the design process to guarantee a reduced design cycle. However, most of the existing system-level simulation-based frameworks consider static application mapping and do not consider the run-time management effects. In this work, we present a modeling and simulation approach that allows integration of run-time management strategies in MPSoC system simulation. We have integrated the proposed approach in an industrial modeling and simulation framework. A case-study with seven applications running on a heterogeneous multicore platform is considered and different management strategies are evaluated according to latency and power consumption criteria.

关键词： System-level simulation Execution trace Run-time management strategies Heterogeneous multicore systems

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DL Based System for On-Board Image Classification in Real Time, Applied to Disaster Mitigation

DL Based System for On-Board Image Classification in Real Ti...

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international conference on Parallel Distributed and Grid Computing (PDGC)

作者： Amogh Shukla Shubh Almal Ankur Gupta Rinisha Jain Rishabh Mishra Dharmesh Dhabliya School of CSE Vellore Institute of Technology Vellore TL India Department of CSE Vaish College of Engineering Rohtak Haryana India Vishwakarma Institute of Information Technology Pune Maharashtra India

ISBN: (纸本)9781665454025

Natural phenomena such as earthquakes that cause the destruction of bridges and can cause tsunamis, among other phenomena and disasters, are on the rise as a result of climate change, which is affecting our planet. This is because of the rise in average global temperature and the development of extreme rains, which causes rivers to overflow. The use of satellites for terrestrial observation has made it possible to keep tabs on events throughout the world in recent years. However, these satellite systems aren't without their drawbacks; one is that cloud cover may make it difficult to accurately record photographs. It is done based on the clouds present, and another drawback is the visiting time that the satellites have, which means that the area that you want to record the image is not always available, so you have to wait for the day and the time in which the satellite orbit can pass through the area of interest that the image is to be recorded. Drones, which fly at low altitudes and do not have cloud problems, are one such alternative, solving a problem of satellites, on cloud cover. In light of this, in the present work, a methodology based on low-cost systems is proposed for on-board processing in drones of such data in the event of an emergency, such as after the effects of rain or an earthquake. Methodology involves processing the image in an embedded device, which is coupled to the drone and connected to the camera, in such a way that the information that is sent to the ground station, concentrates on the affected area; this allows for faster decision-making and lessens the impact of the natural disaster. Therefore, it is shown by testing of the embedded computer based on a Raspberry pi 3 for detecting changes in land cover and transmitting this information to an earth station.

关键词： Training Satellites Rain Clouds Computational modeling simulation Earthquakes

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EmuNoC: Hybrid Emulation for Fast and Flexible Network-on-Chip Prototyping on FPGAs

EmuNoC: Hybrid Emulation for Fast and Flexible Network-on-Ch...

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international conference on Field Programmable Logic and Applications

作者： Yee Yang Tan Felix Staudigl Lukas Jünger Anna Drewes Rainer Leupers Jan Moritz Joseph Institute for Communication Technologies and Embedded Systems RWTH Aachen University Germany Institute for Information and Communication Technologies Otto-von-Guericke Universität Magdeburg Germany

Networks-on-Chips (NoCs) recently became widely used, from multi-core CPUs to edge-AI accelerators. Emulation on FPGAs promises to accelerate their RTL modeling compared to slow simulations. However, realistic test stimuli are challenging to generate in hardware for diverse applications. In other words, both a fast and flexible design framework is required. The most promising solution is hybrid emulation, in which parts of the design are simulated in software, and the other parts are emulated in hardware. This paper proposes a novel hybrid emulation framework called EmuNoC. We introduce a clock-synchronization method and software-only packet generation that improves the emulation speed by 36.3 × to 79.3 × over state-of-the-art frameworks while retaining the flexibility of a pure-software interface for stimuli simulation. We also increased the area efficiency to model up to an NoC with 169 routers on a single FPGA, while previous frameworks only achieved 64 routers.

关键词： Emulation Network-on-chip computer architecture Benchmark testing Software Hardware Field programmable gate arrays

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