Horoměřice, Czech Republic
Horoměřice, Czech Republic
Keynotes
Semiconductor Innovation Supporting Industrial Trends
Speaker: Roman Ludin, STMicroelectronics, Czech Rep.
In this presentation you will learn about importance of semiconductor components innovation to the Industry 4.0 evolution. Quick time line lookback followed by outlook into incoming new semiconductor components brining high level of innovation and integration allowing designers to implement more smart and more autonomous systems.
Roman has played several key roles inside STMicroelectronics since joining the company in 2003. He is focusing on ST microcontrollers and microprocessors, supporting leading customers across in Europe. Currently Roman is driving team of Field Application Engineers which mission is to enable developers and designers of embedded applications to release their creativity and bring essential innovation into final products.
Privacy Preserving Collaborative Learning
Speaker: Oana Stan, CEA, Systems Safety & Security laboratory, France
Machine learning is feasible for various use cases; however, the traditional approach requires all training data locally. This is an issue when multiple institutions are willing to collaborate but cannot share sensitive data. Promising recent technologies for collaborative use of machine learning are Federated Learning or Private Aggregation of Teacher Ensembles (PATE). This talk will briefly present an ongoing research project funded by Defense research (PADR) of the European Union that aims to apply these concepts to real-world use cases and improved them with privacy-preserving enhancements such as homomorphic encryption.
Dr. Oana Stan is a full-time researcher at CEA as a member of the Systems Safety & Security laboratory. Prior to her current position, she accomplished a Ph.D. in Computer Science on discrete optimization under uncertainty applied to the compilation of parallel programs for manycore architectures. Her main research activities from 2013 include the application of advanced cryptographic techniques for secure computation such as the homomorphic encryption, functional encryption or verifiable computing. She was involved in various R&D projects (national and European) related to the compilation for programs working on encrypted data as well as the deployment of secure computation methods in practical settings such as the analysis of energy data in smart cities and protection of data privacy for end-users in health-related applications.
Modular Arithmetic-based Circuits and Systems for Emerging Technologies and Applications: Deep Neural Networks and Cryptography
Speaker: Leonel Sousa, INESC Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Portugal
Energy efficiency and limited power consumption are key aspects for the next-generation of integrated circuits and systems. Thus, together with the increase of performance, they should drive the design of new architectures and arithmetic units. Unconventional number systems, namely Residue Number Systems (RNSs), may hold the answer to these emerging challenges. RNS relies on the use of modular arithmetic to perform additions, subtractions and multiplications in parallel without any dependency between the RNS-digits, thus improving the energy efficiency. Due to a few limitations, such as conversion overheads and division, only recently have RNSs experienced a significant number of advances in its application to new domains, such as Deep Convolutional Neural Networks (DCNN) and cryptography. In this talk, we present a state-of-the-art overview concerning the use of the RNS not only to improve the performance of public-key cryptographic algorithms but also to make them more resistant to attacks. RNS for emerging post-quantum algorithms, namely the ones supporting lattice-based cryptosystems (LBCs), and Fully Homomorphic Encryption (FHE) are also covered in this seminar. The potential of RNS for the high-performance implementation of deep convolutional neural networks (DCNNs) is unveiled. A novel hardware implementation of RNS-based matrix multiplication useful for implementing DCNNs is discussed in this seminar.
Leonel Sousa received his PhD in electrical and computer engineering from the Instituto Superior Técnico (IST), Universidade de Lisboa (UL), Lisbon, Portugal, in 1996. He is currently a Full Professor and Chair of the Electrical and Computer Engineering Department at the IST and a Senior Researcher with the Instituto de Engenharia de Sistemas e Computadores – Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal. He spent three months in Japan at the beginning of 2017 with a prestigious JSPS Invitation Fellowship for Research, and he has been a Visiting Professor at The Carnegie Mellon University (CM) in the fall semester of 2017/2018. He has given more than 30 keynote, invited talks and tutorials. He has authored or co-authored more than 250 papers, appearing in international journals and conferences, and edited five special issues of international journals. As professor, he has given several undergraduate and graduate courses, and supervised 15 PhD Theses.
His research interests include computer architectures, parallel computing, computer arithmetic, and multimedia systems. Prof. Sousa is a Senior Member of IEEE, Fellow of the IET, and a Distinguished Scientist of the ACM. He served as a member of the organization committee for several international conferences, and he is currently an Associate Editor and Editor-in-Chief of several renowned international journals, including two IEEE Transactions and the IEEE Access. He received several awards for the quality and impact of his scientific publications (DASIP, SAMOS, UL/Santander).
Component-Based Design by Solving Language Equations
Speaker: Tiziano Villa, Universita di Verona, Italy
An important step in the design of a complex system is its decomposition into a number of interacting components, of which some are given (known) and some need to be synthesized (unknown). Then a basic task in the design flow is to synthesize an unknown component that when combined with the known part of the system (the context) satisfies a given specification. This problem arises in several applications ranging from sequential synthesis to the design of discrete controllers. There are different formulations of the problem, depending on the formal models to specify the system and its components, the composition operators, and the conformance relations of the composed system vs. the specification. Various behavioral models have been studied in the literature, e.g., finite state machines and automata, omega-automata, Petri nets, process spaces process algebras; various forms of synchronous and asynchronous (interleaving/parallel) composition have been considered; the conformance relations include language containment and equality, and notions of simulation. In this talk we give an overview of the problem (a.k.a., the unknown component problem, or submodule construction, etc.), and we focus on its reduction to solving equations over languages, as a key technology for supporting synthesis of compositional systems. We survey the state-of-art and highlight open problems requiring further investigation.
Tiziano Villa completed a Ph.D. in EECS in 1995 at the University of California, Berkeley. In 1997 he joined as a Research Scientist the PARADES Labs, Rome, Italy. In 2002 he became an Associate Professor at Universita di Udine, Italy. Since 2006 he is a Professor with the Department of Computer Science (DI), Universita di Verona, Italy. His research interests are in formal methods for electronic design automation, including logic synthesis, formal verification, automata theory and models of computation, discrete-event dynamic systems, supervisory control, cyber-physical and embedded systems. He co-authored three books: Synthesis of Finite State Machines: Functional Optimization (Kluwer/Springer - 1997 and reprint 2010), Synthesis of Finite State Machines: Logic Optimization (Kluwer/Springer - 1997 and reprint 2012), The Unknown Component Problem: Theory and Applications (Springer - 2012), and co-edited the book "Coordination Control of Distributed Systems" (Springer, 2015).
Keynotes
Semiconductor Innovation Supporting Industrial Trends
Speaker: Roman Ludin, STMicroelectronics, Czech Rep.
In this presentation you will learn about importance of semiconductor components innovation to the Industry 4.0 evolution. Quick time line lookback followed by outlook into incoming new semiconductor components brining high level of innovation and integration allowing designers to implement more smart and more autonomous systems.
Roman has played several key roles inside STMicroelectronics since joining the company in 2003. He is focusing on ST microcontrollers and microprocessors, supporting leading customers across in Europe. Currently Roman is driving team of Field Application Engineers which mission is to enable developers and designers of embedded applications to release their creativity and bring essential innovation into final products.
Privacy Preserving Collaborative Learning
Speaker: Oana Stan, CEA, Systems Safety & Security laboratory, France
Machine learning is feasible for various use cases; however, the traditional approach requires all training data locally. This is an issue when multiple institutions are willing to collaborate but cannot share sensitive data. Promising recent technologies for collaborative use of machine learning are Federated Learning or Private Aggregation of Teacher Ensembles (PATE). This talk will briefly present an ongoing research project funded by Defense research (PADR) of the European Union that aims to apply these concepts to real-world use cases and improved them with privacy-preserving enhancements such as homomorphic encryption.
Dr. Oana Stan is a full-time researcher at CEA as a member of the Systems Safety & Security laboratory. Prior to her current position, she accomplished a Ph.D. in Computer Science on discrete optimization under uncertainty applied to the compilation of parallel programs for manycore architectures. Her main research activities from 2013 include the application of advanced cryptographic techniques for secure computation such as the homomorphic encryption, functional encryption or verifiable computing. She was involved in various R&D projects (national and European) related to the compilation for programs working on encrypted data as well as the deployment of secure computation methods in practical settings such as the analysis of energy data in smart cities and protection of data privacy for end-users in health-related applications.
Modular Arithmetic-based Circuits and Systems for Emerging Technologies and Applications: Deep Neural Networks and Cryptography
Speaker: Leonel Sousa, INESC Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Portugal
Energy efficiency and limited power consumption are key aspects for the next-generation of integrated circuits and systems. Thus, together with the increase of performance, they should drive the design of new architectures and arithmetic units. Unconventional number systems, namely Residue Number Systems (RNSs), may hold the answer to these emerging challenges. RNS relies on the use of modular arithmetic to perform additions, subtractions and multiplications in parallel without any dependency between the RNS-digits, thus improving the energy efficiency. Due to a few limitations, such as conversion overheads and division, only recently have RNSs experienced a significant number of advances in its application to new domains, such as Deep Convolutional Neural Networks (DCNN) and cryptography. In this talk, we present a state-of-the-art overview concerning the use of the RNS not only to improve the performance of public-key cryptographic algorithms but also to make them more resistant to attacks. RNS for emerging post-quantum algorithms, namely the ones supporting lattice-based cryptosystems (LBCs), and Fully Homomorphic Encryption (FHE) are also covered in this seminar. The potential of RNS for the high-performance implementation of deep convolutional neural networks (DCNNs) is unveiled. A novel hardware implementation of RNS-based matrix multiplication useful for implementing DCNNs is discussed in this seminar.
Leonel Sousa received his PhD in electrical and computer engineering from the Instituto Superior Técnico (IST), Universidade de Lisboa (UL), Lisbon, Portugal, in 1996. He is currently a Full Professor and Chair of the Electrical and Computer Engineering Department at the IST and a Senior Researcher with the Instituto de Engenharia de Sistemas e Computadores – Investigação e Desenvolvimento (INESC-ID), Lisbon, Portugal. He spent three months in Japan at the beginning of 2017 with a prestigious JSPS Invitation Fellowship for Research, and he has been a Visiting Professor at The Carnegie Mellon University (CM) in the fall semester of 2017/2018. He has given more than 30 keynote, invited talks and tutorials. He has authored or co-authored more than 250 papers, appearing in international journals and conferences, and edited five special issues of international journals. As professor, he has given several undergraduate and graduate courses, and supervised 15 PhD Theses.
His research interests include computer architectures, parallel computing, computer arithmetic, and multimedia systems. Prof. Sousa is a Senior Member of IEEE, Fellow of the IET, and a Distinguished Scientist of the ACM. He served as a member of the organization committee for several international conferences, and he is currently an Associate Editor and Editor-in-Chief of several renowned international journals, including two IEEE Transactions and the IEEE Access. He received several awards for the quality and impact of his scientific publications (DASIP, SAMOS, UL/Santander).
Component-Based Design by Solving Language Equations
Speaker: Tiziano Villa, Universita di Verona, Italy
An important step in the design of a complex system is its decomposition into a number of interacting components, of which some are given (known) and some need to be synthesized (unknown). Then a basic task in the design flow is to synthesize an unknown component that when combined with the known part of the system (the context) satisfies a given specification. This problem arises in several applications ranging from sequential synthesis to the design of discrete controllers. There are different formulations of the problem, depending on the formal models to specify the system and its components, the composition operators, and the conformance relations of the composed system vs. the specification. Various behavioral models have been studied in the literature, e.g., finite state machines and automata, omega-automata, Petri nets, process spaces process algebras; various forms of synchronous and asynchronous (interleaving/parallel) composition have been considered; the conformance relations include language containment and equality, and notions of simulation. In this talk we give an overview of the problem (a.k.a., the unknown component problem, or submodule construction, etc.), and we focus on its reduction to solving equations over languages, as a key technology for supporting synthesis of compositional systems. We survey the state-of-art and highlight open problems requiring further investigation.
Tiziano Villa completed a Ph.D. in EECS in 1995 at the University of California, Berkeley. In 1997 he joined as a Research Scientist the PARADES Labs, Rome, Italy. In 2002 he became an Associate Professor at Universita di Udine, Italy. Since 2006 he is a Professor with the Department of Computer Science (DI), Universita di Verona, Italy. His research interests are in formal methods for electronic design automation, including logic synthesis, formal verification, automata theory and models of computation, discrete-event dynamic systems, supervisory control, cyber-physical and embedded systems. He co-authored three books: Synthesis of Finite State Machines: Functional Optimization (Kluwer/Springer - 1997 and reprint 2010), Synthesis of Finite State Machines: Logic Optimization (Kluwer/Springer - 1997 and reprint 2012), The Unknown Component Problem: Theory and Applications (Springer - 2012), and co-edited the book "Coordination Control of Distributed Systems" (Springer, 2015).