Keynote speakers – CPSIoT2021
Benoît Dupont de Dinechin
Title: “Engineering a Manycore Processor for Edge Computing”
Abstract: Edge computing applications such as autonomous driving systems (ADS) and 5G radio access network (RAN) require significant computing capabilities and predictable response times, while being constrained by size, weight and power (SWaP). Such applications significantly benefit from computing platforms based on manycore processors. We first expose the differences between multi-core architectures and many-core architectures, currently mainly represented by GPGPU processors. Then, by using the MPPA3 processor from Kalray as an illustration, we present some of the challenges and the choices involved by engineering an edge processing computing platform based on a manycore architecture. On the local architecture, energy efficiency and time predictability can be leveraged from a Fisher-style VLIW architecture. Accelerating deep learning inference is achieved by tightly coupling a tensor coprocessor. On the global architecture, the cache coherence domains are preferably localized to the compute units. These compute units are connected by a network-on-chip capable of multi-casting, where deadlock-free routing requires some care. The computing platform is completed by providing standard and open programming environments. Among these, OpenCL, OpenVX and OpenMP appear as the most relevant for compute-intensive edge applications, once these environments are enabled to efficiently exploit the compute unit local memories of the manycore architecture.
Benoît Dupont de Dinechin is the Chief Technology Officer of Kalray. He is the main architect of the Kalray VLIW core including its deep learning coprocessor, and the co-architect of the Kalray Multi-Purpose Processing Array (MPPA) family of processors. Benoît also defined the Kalray software roadmap and still contributes to its production compilers. Before joining Kalray, Benoît was managing Research and Development of the STMicroelectronics Software, Tools, Services division, and was promoted to STMicroelectronics Fellow in 2008. Prior to STMicroelectronics, Benoît worked at the Cray Research park (Minnesota, USA), where he designed and developed the software pipeliner of the Cray T3E production compilers.
Benoît earned an engineering degree in Radar and Telecommunications from the Ecole Nationale Supérieure de l’Aéronautique et de l’Espace (Toulouse, France), and a doctoral degree in computer systems from the University Pierre et Marie Curie (Paris) under the direction of Prof. P. Feautrier. He completed his post-doctoral studies at the McGill University (Montreal, Canada) at the ACAPS laboratory led by Prof. G.R. Gao. Benoît authored 16 patents in the area of computer architecture, and published over 60 conference papers, journal articles and book chapters in the areas of parallel computing, compiler design and operations research
Prof. Ioannis Pitas
Title: Privacy Protection, Ethics, Robustness and Regulatory Issues in Autonomous Systems
Abstract: One of the most important challenges of the present decade in Autonomous Systems and CPS is the accommodation of ethics, trustworthiness, reliability and robustness issues related to embedded intelligence. This lecture is divided in 3 sections. First, we will overview the typical regulatory, data security and privacy protection issues and restrictions that should be considered when designing modern CPS, e.g., autonomous cars or drones. Second, we will describe private data de-identification algorithms (e.g., face de-identification), discussing the differences between traditional, GAN-based and adversarial-attack-based privacy protection methodologies. Finally, the presentation will focus on Autonomous Systems and CPS AI robustness. Slight imperceptible changes to sensorial data (e.g., images captured by a CPS camera) that may be crafted by adversaries or even be produced by environmental noise, lead to a dramatic decrease of performance, especially in deep learning-based trained classification models. We will present modern AI neural network training schemes that alleviate this threat, by focusing on enhancing the robustness of CPS classification systems against adversarial treats.
Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received the Diploma and PhD degree in Electrical Engineering, both from the Aristotle University of Thessaloniki (AUTH), Greece. Since 1994, he has been a Professor at the Department of Informatics of AUTH and Director of the Artificial Intelligence and Information Analysis (AIIA) lab. He served as a Visiting Professor at several Universities.
His current interests are in the areas of computer vision, machine learning, autonomous systems, intelligent digital media, image/video processing, human-centred computing, affective computing, 3D imaging and biomedical imaging. He has published over 1000 papers, contributed in 47 books in his areas of interest and edited or (co-)authored another 11 books. He has also been member of the program committee of many scientific conferences and workshops. In the past he served as Associate Editor or co-Editor of 9 international journals and General or Technical Chair of 4 international conferences. He participated in 71 R&D projects, primarily funded by the European Union and is/was principal investigator in 42 such projects. Prof. Pitas lead the big European H2020 R&D project MULTIDRONE: He is AUTH principal investigator in H2020 R&D projects Aerial Core and AI4Media. He is chair of the Autonomous Systems Initiative He is head of the EC funded AI doctoral school of Horizon2020 EU funded R&D project AI4Media (1 of the 4 in Europe). He has 32200+ citations to his work and h-index 85+ (Google Scholar).