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检索条件"任意字段=Internation Conference on Embedded Systems and Applications/International Conference on VLSI"

共 881 条记录，以下是1-10 订阅

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ERS: Energy-efficient Real-time DAG Scheduling on Uniform Multiprocessor embedded systems 37

ERS: Energy-efficient Real-time DAG Scheduling on Uniform Mu...

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37th international conference on vlsi Design (vlsiD) / 23rd international conference on embedded systems (ES)

作者： Senapati, Debabrata Maurya, Dharmendra Sarkar, Arnab Karfa, Chandan SRM Univ AP Amaravati Andhra Pradesh India IIT Guwahati Gauhati India IIT Kharagpur Kharagpur W Bengal India

ISBN: (纸本)9798350384406

Nowadays, many embedded systems such as mobiles and laptops to satellites and robotic systems, are often driven by limited energy sources like batteries. Hence, these devices are not only judged by their real-time and functional performance but also by their efficiencies in terms of energy management. Energy minimization is one of the primary design requirements for distributed embedded systems. The growing importance of complex applications in the distributed system introduces significant challenges in reducing energy consumption. This work addresses the problem of scheduling a real-time application abstracted as a directed acyclic graph (DAG), on a Dynamic Voltage and Frequency Scaling (DVFS) enabled uniform multiprocessor system, by proposing an efficient heuristic strategy called Energy-efficient Real-time DAG Scheduler (ERS). ERS effectively selects the appropriate processing frequency for each task-to-processor pair in the system such that overall energy saving is maximized while satisfying constraints related to resource, task precedence and deadline. We have evaluated the performance of the proposed framework using real-world benchmark applications. Obtained results reveal that ERS is able to deliver better performance in terms of energy savings than state-of-the-art works such as GSPM, SSPM, and PSPM.

关键词： DAG Scheduling List Scheduling Energy-aware Real-time Uniform Multiprocessor systems

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Certifying Learning-Enabled Autonomous Cyber Physical systems - A Deployment Perspective 37

Certifying Learning-Enabled Autonomous Cyber Physical System...

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37th international conference on vlsi Design (vlsiD) / 23rd international conference on embedded systems (ES)

作者： Singh, Suraj Hazra, Somnath Dey, Sumanta Dey, Soumyajit Indian Inst Technol Kharagpur Dept Comp Sci & Engn Kharagpur W Bengal India

ISBN: (纸本)9798350384406

Deployment of Autonomous Cyber-Physical systems (CPS) has penetrated almost every realm of human existence, including public transportation, military applications, critical infrastructures, and healthcare. While learning-enabled control methodologies for such systems promise scalability for massively distributed (yet coordinated) implementations, certification of safety and robustness is still considered elusive in that context. This is primarily because current strategies mostly rely on certification methods that are not scalable and inefficient in handling non-linearity. Such systems' model-based control design and validation methods rarely account for the deployment platform uncertainties and adversarial aspects leading to attack exposed solutions. This work comprehensively summarises existing methodologies and critical issues related to real-world deployment of multi-agent learning-enabled CPS and also provides potentials solutions that explore innovative research roadmaps.

关键词： Control Theory Reinforcement Learning Certification Formal Verification

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An Efficient Neural Network Controller for Autonomous Lane-Keeping Assist System 37

An Efficient Neural Network Controller for Autonomous Lane-K...

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37th international conference on vlsi Design (vlsiD) / 23rd international conference on embedded systems (ES)

作者： Mallik, Debanjan Ghosh, Sumana Jadavpur Univ Kolkata India Indian Stat Inst Kolkata Kolkata India

ISBN: (纸本)9798350384406

With the advent of new technologies and hardware, the importance and demand for autonomous vehicles are also increasing nowadays. For the safe deployment of these autonomous vehicles, efficient and reliable control techniques are very crucial. Classical control techniques encounter difficulties in accommodating various intricate real-world driving situations, hence, fail to properly control them. Moreover, since a major part of the underlying feedback control computation includes heavy vision computation tasks, classical control techniques are falling short in controlling them properly due to the delay coming from this lengthy vision computation. To overcome this, data-driven approaches are being used in many applications. This research work particularly addresses the challenge of controlling an autonomous lane-keeping assist system leveraging the power of neural networks (NN). The aim of the proposed NN-based controller is to enhance the precision and robustness of the lane-keeping assist system. The NN-based controller demonstrates promising results with respect to some state-of-the-art methodologies, offering hope for safer and more effective autonomous driving in dynamic environments.

关键词： Autonomous Vehicles Lane Keeping Assist systems Neural Network Controller Control Performance

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embedded Soft Computing applications Using Low Power vlsi Techniques

Embedded Soft Computing Applications Using Low Power VLSI Te...

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2024 IEEE international conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Suman, Jami Venkata Anitha Priyadarshini, G.M. Rao, P. Krishna Siri Chandana, Niddana Gmr Institute of Technology Department of Ece Andhra Pradesh Rajam India Anurag University Department of Ece Hyderabad India Aditya Institute of Technology and Management Department of Ece Andhra Pradesh Tekkali India

ISBN: (纸本)9798350390759

Energy deficit vlsi addresses are important for several purposes, especially in IC and microchip development. Energy-efficient, compact, and durable electronics require low-power vlsi addressing. Modern integrated circuit design must address power limits, temperature regulation, and environmental concerns. Soft computing is used in embedded systems. Soft computing is an AI discipline that develops intelligent systems that can handle uncertainty, imprecision, and imperfect truth. Soft computing uses approximation reasoning and probabilistic tactics to solve complex real-world problems instead of mathematical models. The work emphasizes low-power vlsi addressing for cost-effective and durable soft computing applications embedding. These low-power vlsi techniques in integrated soft computing applications can enhance battery life, energy utilization, and performance while maintaining precision and predictability. Low-power vlsi techniques in embedded soft computing systems enhance energy efficiency, battery life, cost, and dependability. These tactics encourage the development of cutting-edge, environmentally friendly embedded systems that can perform complex soft computing tasks within power constraints. © 2024 IEEE.

关键词： Energy utilization

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Dynamic Scheduling for Event-Driven embedded Industrial applications 31

Dynamic Scheduling for Event-Driven Embedded Industrial Appl...

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31st IFIP/IEEE international conference on Very Large Scale Integration (vlsi-SoC)

作者： Taji, Hossein Miranda, Jose Peon-Quiros, Miguel Balasi, Szabolcs Atienza, David Ecole Polytech Fed Lausanne Embedded Syst Lab ESL Lausanne Switzerland Ecole Polytech Fed Lausanne EcoCloud Lausanne Switzerland Nespresso Wallisellen Switzerland

ISBN: (纸本)9798350325997

This paper addresses the optimization of embedded platforms to meet the computing and real-time requirements of cyber-physical systems and IoT applications, including embedded intelligence. In this context, schedulers are vital in enhancing processor utilization in industrial contexts. Although existing research has focused primarily on the schedulability of periodic tasks, event-driven tasks better represent these new embedded intelligence scenarios in the real world. This work explores static and dynamic scheduling policies within a general scenario and a specific case study based on an actual industrial application. The proposed dynamic scheduler has been integrated into the FreeRTOS kernel and has been employed to conduct all of our experiments on industrial products within the smart home domain. Our results show that, while we can respect real-time requirements, our proposed dynamic scheduling can improve the performance of event-driven applications by reducing missed task deadlines by up to 60%. Moreover, we have also developed a lightweight version of our dynamic scheduler for industrial products that reduces average timing overhead for task selection and insertion by up to 34.7% and memory overhead for task creation and list scheduling by up to 74.7% compared to state-of-the-art static alternatives.

关键词： Event-Driven Tasks Scheduling RTOS embedded systems Industrial applications

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Delay-Aware Control for Autonomous systems 36

Delay-Aware Control for Autonomous Systems

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36th international conference on vlsi Design (vlsiD) / 22nd international conference on embedded systems (ES)

作者： Ihosh, Sumana Indian Stat Ins Kolkata India

ISBN: (纸本)9798350346787

The increasing demand for implementing multiple perception-based real-time applications (e.g., lateral control) onto autonomous systems is introducing new challenges into their control design paradigm, such as the delay-aware design of software controllers for such systems. This becomes more challenging when a variable delay occurs due to the variation of the workload of computation associated with the perception tasks, such as compute-intensive image processing tasks. For such systems, the traditional controller-design-followed-by-implementation paradigm fails to provide the desired control performance all the time. One such example is designing controllers by considering worst-case perception computation delay and thus providing sub-optimal control performance. The primary focus of this work is to address this issue by introducing a novel multirate control synthesis approach for autonomous systems. The idea is to apply multiple controllers and adaptively switch among them based on the current delay value without compromising the stability while improving the control performance. We report promising results w.r.t state-of-the-art approaches toward enhancing control performance and optimizing control cost.

关键词： Perception-based systems Autonomous systems Controller Synthesis Variable Delay Control Performance

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Next-Generation embedded systems with Synergies vlsi with Deep Learning: Design Methodologies, Optimization Techniques, and Real-World applications

Next-Generation Embedded Systems with Synergies VLSI with De...

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2025 IEEE international Students' conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Kalarani, G. Mohanapriya, M. Pattunnarajam, P. Sasikala, G. Sivakumar, J. Suresh, M. Jaya Engineering College Department of Electronics and Instrumentation Engineering Tamil Nadu Chennai India Srm Valliammai Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Sri Venkateswara College of Engineering Department of Ece Tamil Nadu Sriperumbudur India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Tamil Nadu Chennai India St. Joseph's College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India R.M.D. Engineering College Department of Mathematics Tamil Nadu Thiruvallur India

ISBN: (纸本)9798331529833

New generation of embedded systems with superior intelligence, energy efficiency, and performance have emerged as a result of the merging of deep learning with Very-Large-Scale Integration (vlsi) technology. Methodologies for design, optimisation strategies, and practical uses of next-generation embedded systems are the foci of this study, which investigates the ways in which vlsi and deep learning might work together. These systems have the potential to transform several industries, such as transportation, medicine, robotics, and the IoT, by harnessing the processing power of deep neural networks with the improvements in semiconductor fabrication. Prior to delving into the advantages of bespoke hardware design for deep learning inference and training, we trace the history of very large scale integration (vlsi) technology and its incorporation with deep learning algorithms. Investigated here are the design techniques that, when applied to very large scale integration (vlsi) architectures like FPGAs and ASICs, allow for the efficient mapping of deep learning models onto these devices. We show case studies that show how these methods work and talk about the trade-offs between performance, power consumption, and adaptability. The development of next-generation embedded systems relies heavily on optimisation approaches. Model compression, quantisation, and pruning are some of the optimisation strategies that we examine;they lessen the memory and computational demands of deep learning models without drastically altering their accuracy. For embedded devices with limited resources, these methods are crucial for implementing deep learning models. Additionally, we explore the practical uses of embedded systems augmented with vlsi and deep learning. By capitalising on the complementary strengths of vlsi and deep learning, applications like autonomous driving, medical imaging, and smart home automation are revolutionising entire industries. In this paper, we examine the design

关键词： Integrated circuit design

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Exploring the Intersection of vlsi and embedded systems: Technological Advancements and Future applications 2

Exploring the Intersection of VLSI and Embedded Systems: Tec...

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2nd international conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Pandi, V. Samuthira James, Aaron S. Jaishika, S. Shobana, D. Priya, Lakshmi J. Pattunnarajam, P. Centre for Advanced Wireless Integrated Technology Chennai Institute of Technology Tamil Nadu Chennai India Electrical and Electronics Section Department of Engineering & Technology University of Technology and Applied Sciences Ibri Oman Department of Information Technology Sri Sairam Institute of Technology Sai Leo Nagar West Tambaram Chennai India Department of Mechatronics Engineering Rajalakshmi Engineering College Chennai India Department of ECE Saveetha Engineering College Chennai India Department of ECE Sri Venkateswara College of Engineering Sriperumbudur India

ISBN: (纸本)9798331541217

In this study, we look at the present and future of embedded systems as well as vlsi (Very Large Scale Integration) technology to see how the two work together. In particular, very large scale integration (vlsi) technology has altered the landscape of consumer electronics and medical diagnostics by enabling the integration of millions of transistors onto a single chip. Whereas bigger systems rely on embedded systems for their operation, the latter perform tasks that are unique to their settings. One area that has benefited greatly from vlsi technology's incorporation into embedded systems is the automotive industry, which uses it to power cutting-edge electronic systems like navigation and voice recognition. Communication device development, 5G evolution, and beyond have all relied heavily on this integration, demonstrating vlsi's significance in the field of future communication technologies. Trends in very large scale integration (vlsi) technology that are yet to come include developments in semiconductor manufacturing, AI, and new fields like neuromorphic engineering and quantum computing. embedded systems stand to benefit from these developments, which should increase their efficiency, power, and adaptability to new uses. In particular, this research looks at how very large scale integration (vlsi) and embedded systems can change sectors including consumer electronics, healthcare, and the automobile industry in the future. For a full picture of how these technologies will influence the future of technology, it also discusses the pros and cons of integrating them. © 2024 IEEE.

关键词： Automotive industry

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An Energy-Efficient and Robust 10T SRAM based In-Memory Computing Architecture 36

An Energy-Efficient and Robust 10T SRAM based In-Memory Comp...

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36th international conference on vlsi Design (vlsiD) / 22nd international conference on embedded systems (ES)

作者： Srivastava, Noopur Rajput, Anil Kumar Pattanaik, Manisha Kaushal, Gaurav ABV IIITM VLSI Design Lab Gwalior India

ISBN: (纸本)9798350346787

In-Memory Computing (IMC) is emerging as a new paradigm to address the von Neumann bottleneck (VNB) in data-intensive applications. This research proposes a 10T SRAM-based IMC architecture that is both robustand energy-efficient. The write margin and read margin of the proposed 10T SRAM are both increased by 40% and 2.5%, respectively, over the 9T SRAM cell. The proposed 10T SRAM has write energy and leakage power reduction of 89% and 96.6%, respectively while maintaining a similar read enery as compared to 9T SRAM. Additionally, a 4 Kb SRAM array based on 10T SRAM is implemented in 180nm SCL technology to analyze the suggested IMC architecture. At 1.8 V, 60 MHz, the suggested IMC architecture achieves energy efficiency of 0.43 TOPS/W for 1-bit logic and 0.41TOPS/W for 1-bit addition. The area efficiency of 65.2% for a 136 32 array is achieved.

关键词： SRAM Von-Neumann architecture (VNA) In-Memory Computing (IMC) energy-efficiency

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Compute-In-Place Serial FeRAM: Enhancing Performance, Efficiency and Adaptability in Critical embedded systems 31

Compute-In-Place Serial FeRAM: Enhancing Performance, Effici...

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31st IFIP/IEEE international conference on Very Large Scale Integration (vlsi-SoC)

作者： Noel, J. -P. Valea, E. Grenouillet, L. Chapuis, B. Fisher, C. Recoquillay, A. Giraud, B. Univ Grenoble Alpes CEA LIST F-38000 Grenoble France Univ Paris Saclay CEA List F-91120 Palaiseau France

ISBN: (纸本)9798350325997

In an era where embedded systems play an increasingly vital role in critical domains like electric mobility, healthcare, industry, or infrastructure monitoring, the demand for real-time data processing is paramount. This paper addresses the challenges posed by high sensor data rates and limited processing power of microcontrollers (MCUs) in these applications. It introduces a novel computational method leveraging the Serial Ferroelectric RAM (FeRAM) architecture, along with the Computational SRAM concept, and will be called Compute-In-Place (CIP). This exploration of CIP Serial FeRAM reveals its potential for improving predictability, energy efficiency and security in high-throughput processing of large volumes of sensor data. Unlike conventional computing architectures, CIP Serial FeRAM lightens the MCU's computational load, reduces latency and improves energy efficiency by enabling computational tasks within memory. This paper emphasizes the flexibility of CIP Serial FeRAM for diverse real-time tasks, paving the way for more performance, efficient and adaptable critical embedded systems.

关键词： Energy efficiency

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