{"title":"Determining MPSoC layout from thermal camera images: work-in-progress","authors":"M. Sojka, Ondřej Benedikt, Z. Hanzálek","doi":"10.1145/3477244.3477619","DOIUrl":"https://doi.org/10.1145/3477244.3477619","url":null,"abstract":"In many safety-critical applications, Multi-Processor Systems-on-Chip (MPSoC) must operate within a given thermal envelope under harsh environmental conditions. Meeting the thermal requirements often requires using advanced task allocation and scheduling techniques that are guided by detailed power models. This paper introduces a method that has the potential to simplify the creation of such models. It constructs so-called heat maps from thermal camera images. By comparing the heat maps of different workloads, we identify the locations of on-chip components and the amount of heat produced by them. We demonstrate our method on the i.MX8QuadMax chip from NXP, where we identify the locations of CPU clusters, bigger CPU cores, GPUs, and DRAM controllers.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124688712","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}
{"title":"Performance analysis and optimization of decision tree classifiers on embedded devices: work-in-progress","authors":"A. Krishnakumar, Ümit Y. Ogras","doi":"10.1145/3477244.3477618","DOIUrl":"https://doi.org/10.1145/3477244.3477618","url":null,"abstract":"Decision trees (DTs) offer a popular implementation choice for machine learning classifiers since they are highly interpretable and easy to use. Resource management decision overheads must be minimal in embedded systems to meet latency targets and deadline constraints. While the literature has preferred hardware architectures for DTs to meet latency targets, they are not suitable for ultra-low latency applications due to their data movement overheads despite the parallelism they offer. Therefore, we propose software optimization techniques for decision trees. The proposed DTs achieve lower than 50 ns latencies for depth 12, making them highly suitable for classification in embedded resource management.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116176065","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}
{"title":"OHTLoc: an online heterogeneous transfer method on wifi-based indoor localization system: work-in-progress","authors":"Lufei Han, Chen Bian","doi":"10.1145/3477244.3477612","DOIUrl":"https://doi.org/10.1145/3477244.3477612","url":null,"abstract":"With the development of wireless network technology, the WiFi-based indoor localization methods incorporating machine learning have attracted wide attention due to its easy deployment and low cost characteristics. However, the existing learning methods are limited to locating homogeneous and tagged target data. Such strict conditions do not exist in the actual indoor positioning environment, and therefore cannot meet people's locational needs. In this article, we design an Online Heterogeneous Transfer method in Indoor Localization(OHTLoc), a novel transfer learning approach that can realize online location prediction based on the RSS(Received Signal Strength) fingerprint and CSI(Channel State Information) data using WLANs. In particular, OHTLoc does not require any tags on the target data. This is the first time this type of algorithm has been proposed in the field of indoor localization. The prediction results of the target demonstrate showed in the experiment part demonstrate the effectiveness of the proposed technique.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125409104","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}
{"title":"WCET-aware reachability for verified simplex design: work-in-progress","authors":"Ole Lübke, S. Schupp","doi":"10.1145/3477244.3477613","DOIUrl":"https://doi.org/10.1145/3477244.3477613","url":null,"abstract":"Previous online reachability algorithms for hybrid automata reduced conservatism in verified Simplex controller architectures, but were restricted to the imprecise real-time paradigm, i.e., their precision increases over time. Yet, many safety-critical cyber-physical systems are hard real-time systems, requiring an upper bound on the worst-case execution time (WCET) of each task to be known. We show that the iteration bound of the reachability loop can be parameterized by a single factor which determines the precision. Consequently, an algorithm could select a fixed precision depending on the time left until its deadline. In this paper we present such a WCET-aware reachability algorithm, based on an existing algorithm for imprecise real-time. Its smallest WCET bound on an Infineon XMC4500 microprocessor is 32.861 milliseconds.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127643796","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}
Xiangyu Wen, Wei Jiang, Jinyu Zhan, Chen Bian, Ziwei Song
{"title":"Generative strategy based backdoor attacks to 3D point clouds: work-in-progress","authors":"Xiangyu Wen, Wei Jiang, Jinyu Zhan, Chen Bian, Ziwei Song","doi":"10.1145/3477244.3477611","DOIUrl":"https://doi.org/10.1145/3477244.3477611","url":null,"abstract":"3D deep learning has been applied in safety-critical scenarios, e.g., autonomous driving. Several works have raised the security problems of 3D deep learnings mainly from the perspective of adversarial attacks. In this paper, we propose a novel backdoor attack method to threaten 3D deep learning without the original training data. Several neurons are selected and made sensitive to backdoor triggers. The backdoor triggers are generated by reversing neural network, and the shape of which is constrained to map the objects in the physical world. Sufficient training data can be also generated by reverse engineering. Finally, retraining with the generated 3D trigger and training data is applied to inject backdoors, which is in no need of accessing the original training process and data.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"9 36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130473374","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}
{"title":"Improving fault tolerance of DNNs through weight remapping based on gaussian distribution: work-in-progress","authors":"Ruoxu Sun, Jinyu Zhan, Wei Jiang, Yucheng Jiang","doi":"10.1145/3477244.3478521","DOIUrl":"https://doi.org/10.1145/3477244.3478521","url":null,"abstract":"In this paper, we approach to improve the fault tolerance of Deep Neural Networks (DNNs) for safety-critical artificial intelligent applications. We propose to remap the range of 32-bit float to weights to reduce the influence of invalid weights caused by bit-flip faults. From preliminary experiments, we observe that weakening bit-flip faults which make positive weights larger can help to improve the reliability of DNNs. Then, we propose a gaussian distribution based mapping method to prevent weights from being influenced by bit-flip faults, in which a novel function is formulated to remap the relation between 32-bit float and the values of weights. Extensive experiments demonstrate that our approach can improve the accuracy of VGG16 from 13.5% to 80.5%, which is better than the other six tolerance approaches of DNNs.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121513047","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}
{"title":"Detecting deepfake videos by visual-audio synchronism: work-in-progress","authors":"Zhufeng Fan, Jinyu Zhan, Wei Jiang","doi":"10.1145/3477244.3477615","DOIUrl":"https://doi.org/10.1145/3477244.3477615","url":null,"abstract":"Different to traditional works on frame-level features and temporal characteristics, we propose a deepfake video detection method based on visual-audio synchronism, which compares the audio stream and the visual stream by an improved siamese neural network. We combine the audio stream and visual stream as a 2-channel input and design a 2-branches network to achieve the visual-audio synchronism detection. Preliminary experiments demonstrate the efficiency of the proposed method, which can achieve the highest accuracy compared with other existing methods.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123720350","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}
{"title":"An energy-aware optimization model for real-time systems analysis and design: work-in-progress","authors":"Suzanne Elashri, Akramul Azim","doi":"10.1145/3477244.3477622","DOIUrl":"https://doi.org/10.1145/3477244.3477622","url":null,"abstract":"Energy efficiency considerations are required for resource reservations in real-time systems. However, current systems lack considerations of energy efficiency when calculating the optimum processor speed to ensure that the supply of resources is no less than the workload demand during any time intervals. Therefore, we propose an energy-aware optimization model using supply and demand bound functions to reduce over-provisioning resources while still guaranteeing task deadlines. Our initial experiment shows the advantages of using the proposed technique in terms of energy efficiency.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125084253","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}
Bo Pang, Ashank Verma, Jingchao Zhou, Inigo Incer, A. Sangiovanni-Vincentelli
{"title":"The cyber-physical immune system: work-in-progress","authors":"Bo Pang, Ashank Verma, Jingchao Zhou, Inigo Incer, A. Sangiovanni-Vincentelli","doi":"10.1145/3477244.3477621","DOIUrl":"https://doi.org/10.1145/3477244.3477621","url":null,"abstract":"Cyber-Physical Systems (CPS) are important components of critical infrastructure and must operate with high levels of reliability and security. We propose a conceptual approach to securing CPSs: the Cyber-Physical Immune System (CPIS), a collection of hardware and software elements deployed on top of a conventional CPS. Inspired by its biological counterpart, the CPIS comprises an independent network of distributed computing units that collects data from the conventional CPS, utilizes data-driven techniques to identify threats, adapts to the changing environment, alerts the user of any threats or anomalies, and deploys threat-mitigation strategies.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129577962","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}
{"title":"Large-scale timer hardware analysis for a flexible low-level timer-API design: work-in-progress","authors":"Niels Gandraß, Michel Rottleuthner, T. Schmidt","doi":"10.1145/3477244.3477617","DOIUrl":"https://doi.org/10.1145/3477244.3477617","url":null,"abstract":"We report on our ongoing development of an optimized low-level timer-API for the RIOT operating system. Starting with a survey of hardware timer peripherals from 43 MCU-families and 8 manufacturers, we identify common properties and differences of all available timer types. Based on this hardware analysis, we propose a lightweight yet powerful low-level timer-API design. It streamlines existing timer interfaces and relieves application developers from the error-prone task of repeatedly writing additional peripheral driver code.","PeriodicalId":354206,"journal":{"name":"Proceedings of the 2021 International Conference on Embedded Software","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129971420","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}