2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)最新文献_第8页

BAFFI: a bit-accurate fault injector for improved dependability assessment of FPGA prototypes 用于改进FPGA原型可靠性评估的位精确故障注入器

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137300

I. Tuzov, D. Andrés, Juan-Carlos Ruiz-Garcia, Carles Hernández

{"title":"BAFFI: a bit-accurate fault injector for improved dependability assessment of FPGA prototypes","authors":"I. Tuzov, D. Andrés, Juan-Carlos Ruiz-Garcia, Carles Hernández","doi":"10.23919/DATE56975.2023.10137300","DOIUrl":"https://doi.org/10.23919/DATE56975.2023.10137300","url":null,"abstract":"FPGA-based fault injection (FFI) is an indispensable technique for verification and dependability assessment of FPGA designs and prototypes. Existing FFI tools make use of Xilinx essential bits technology to locate the relevant fault targets in FPGA configuration memory (CM). Most FFI tools treat essential bits as black-box, while few of them are able to filter essential bits on the area basis in order to selectively target design components contained within the predefined Pblocks. This approach, however, remains insufficiently precise since the granularity of Pblocks in practice does not reach the smallest design components. This paper proposes an open-source FFI tool that enables much more fine-grained FFI experiments for Xilinx 7-series and Ultrascale+ FPGAs. By mapping the essential bits with the hierarchical netlist, it allows to precisely target any component in the design tree, up to an individual LUT or register, without the need for defining Pblocks (floorplanning). With minimal experimental effort it estimates the contribution of each DUT component into the resulting dependability features, and discovers weak points of the DUT. Through case studies we show how the proposed tool can be applied to different kinds of DUTs: from small-footprint microcontrollers, up to multicore RISC-V SoC. The correctness of FFI results is validated by means of RT-level and gate-level simulation-based fault injection.","PeriodicalId":340349,"journal":{"name":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127414154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

APUF Production Line Faults: Uniqueness and Testing APUF生产线故障:独特性和测试

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137226

Y. Wei, Wenjing Rao, N. Devroye

引用次数: 0

A Coupled Battery State-of-Charge and Voltage Model for Optimal Control Applications 用于最优控制的电池充电状态和电压耦合模型

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137028

Masoomeh Karami, Sajad Shahsavari, E. Immonen, M. Haghbayan, J. Plosila

引用次数: 1

Achieving Datacenter-scale Performance through Chiplet-based Manycore Architectures 通过基于芯片的多核架构实现数据中心规模的性能

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137125

Harsh Sharma, Sumit K. Mandal, J. Doppa, Ümit Y. Ogras, P. Pande

引用次数: 1

Optimizing Data Migration for Garbage Collection in ZNS SSDs ZNS ssd垃圾回收数据迁移优化

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137231

Z. Tan, Linbo Long, Renping Liu, Congming Gao, Yi Jiang, Yan Liu

引用次数: 0

SAFEXPLAIN: Safe and Explainable Critical Embedded Systems Based on AI SAFEXPLAIN:基于AI的安全且可解释的关键嵌入式系统

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137128

J. Abella, Jon Pérez, Cristofer Englund, Bahram Zonooz, Gabriele Giordana, Carlo Donzella, F. Cazorla, E. Mezzetti, Isabel Serra, Axel Brando, Irune Agirre, Fernando Eizaguirre, Thanh Hai Bui, E. Arani, F. Sarfraz, Ajay Balasubramaniam, Ahmed Badar, I. Bloise, L. Feruglio, Ilaria Cinelli, Davide Brighenti, Davide Cunial

{"title":"SAFEXPLAIN: Safe and Explainable Critical Embedded Systems Based on AI","authors":"J. Abella, Jon Pérez, Cristofer Englund, Bahram Zonooz, Gabriele Giordana, Carlo Donzella, F. Cazorla, E. Mezzetti, Isabel Serra, Axel Brando, Irune Agirre, Fernando Eizaguirre, Thanh Hai Bui, E. Arani, F. Sarfraz, Ajay Balasubramaniam, Ahmed Badar, I. Bloise, L. Feruglio, Ilaria Cinelli, Davide Brighenti, Davide Cunial","doi":"10.23919/DATE56975.2023.10137128","DOIUrl":"https://doi.org/10.23919/DATE56975.2023.10137128","url":null,"abstract":"Deep Learning (DL) techniques are at the heart of most future advanced software functions in Critical Autonomous AI-based Systems (CAIS), where they also represent a major competitive factor. Hence, the economic success of CAIS industries (e.g., automotive, space, railway) depends on their ability to design, implement, qualify, and certify DL-based software products under bounded effort/cost. However, there is a fundamental gap between Functional Safety (FUSA) requirements on CAIS and the nature of DL solutions. This gap stems from the development process of DL libraries and affects high-level safety concepts such as (1) explainability and traceability, (2) suitability for varying safety requirements, (3) FUSA-compliant implementations, and (4) real-time constraints. As a matter of fact, the data-dependent and stochastic nature of DL algorithms clashes with current FUSA practice, which instead builds on deterministic, verifiable, and pass/fail test-based software. The SAFEXPLAIN project tackles these challenges and targets by providing a flexible approach to allow the certification - hence adoption - of DL-based solutions in CAIS building on: (1) DL solutions that provide end-to-end traceability, with specific approaches to explain whether predictions can be trusted and strategies to reach (and prove) correct operation, in accordance to certification standards; (2) alternative and increasingly sophisticated design safety patterns for DL with varying criticality and fault tolerance requirements; (3) DL library implementations that adhere to safety requirements; and (4) computing platform configurations, to regain determinism, and probabilistic timing analyses, to handle the remaining non-determinism.","PeriodicalId":340349,"journal":{"name":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130475348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Efficient Fault Injection Algorithm for Identifying Unimportant FFs in Approximate Computing Circuits 一种有效的故障注入算法用于识别近似计算电路中不重要的ff

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137272

Jiaxuan Lu, Yutaka Masuda, T. Ishihara

引用次数: 0

Information Processing Factory 2.0 - Self-awareness for Autonomous Collaborative Systems 信息处理工厂2.0——自主协作系统的自我意识

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137006

Nora Sperling, Alex Bendrick, Dominik Stöhrmann, Rolf Ernst, Bryan Donyanavard, F. Maurer, Oliver Lenke, A. Surhonne, A. Herkersdorf, Walaa Amer, Caio Batista de Melo, Ping-Xiang Chen, Quang Anh Hoang, Rachid Karami, Biswadip Maity, Paul Nikolian, Mariam Rakka, Dongjoo Seo, Saehanseul Yi, Minjun Seo, N. Dutt, Fadi J. Kurdahi

引用次数: 0

Lightspeed Binary Neural Networks using Optical Phase-Change Materials 利用光学相变材料的光速二元神经网络

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137229

Taha Shahroodi, Raphael Cardoso, Mahdi Zahedi, Stephan Wong, A. Bosio, Ian O’Connor, S. Hamdioui

引用次数: 1

Towards Deep Learning-based Occupancy Detection Via WiFi Sensing in Unconstrained Environments 基于深度学习的无约束环境下WiFi感知占用检测

2023 Design, Automation & Test in Europe Conference & Exhibition (DATE) Pub Date : 2023-04-01 DOI: 10.23919/DATE56975.2023.10137260

Cristian Turetta, Geri Skenderi, Luigi Capogrosso, Florenc Demrozi, Philipp H. Kindt, Alejandro Masrur, F. Fummi, M. Cristani, G. Pravadelli

{"title":"Towards Deep Learning-based Occupancy Detection Via WiFi Sensing in Unconstrained Environments","authors":"Cristian Turetta, Geri Skenderi, Luigi Capogrosso, Florenc Demrozi, Philipp H. Kindt, Alejandro Masrur, F. Fummi, M. Cristani, G. Pravadelli","doi":"10.23919/DATE56975.2023.10137260","DOIUrl":"https://doi.org/10.23919/DATE56975.2023.10137260","url":null,"abstract":"In the context of smart buildings and smart cities, the design of low-cost and privacy-aware solutions for recognizing the presence of humans and their activities is becoming of great interest. Existing solutions exploiting wearables and video-based systems have several drawbacks, such as high cost, low usability, poor portability, and privacy-related issues. Consequently, more ubiquitous and accessible solutions, such as WiFi sensing, became the focus of attention. However, at the current state-of-the-art, WiFi sensing is subject to low accuracy and poor generalization, primarily affected by environmental factors, such as humidity and temperature variations, and furniture position changes. Such is-sues are partially solved at the cost of complex data preprocessing pipelines. In this paper, we present a highly accurate, resource-efficient deep learning-based occupancy detection solution, which is resilient to variations in humidity and temperature. The approach is tested on an extensive benchmark, where people are free to move and the furniture layout does change. In addition, based on a consolidated algorithm of explainable AI, we quantify the importance of the WiFi signal w.r.t. humidity and temperature for the proposed approach. Notably, humidity and temperature can indeed be predicted based on WiFi signals; this promotes the expressivity of the WiFi signal and at the same time the need for a non-linear model to properly deal with it.","PeriodicalId":340349,"journal":{"name":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122687565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0