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Event Details

MP Associates, Inc.
SUNDAY September 30, 9:00am - 1:00pm | Einaudi
Embedded Machine Learning Today and Tomorrow

Luca Benini - ETH Zurich & Univ. of Bologna
Lukas Cavigelli - ETH Zurich & Univ. of Bologna
Timoleon Moraitis - IBM Research
Manuel Le Gallo - IBM Research
Luca Benini - ETH Zurich & Univ. of Bologna
The tutorial will start with an overview of architectures and systems for machine learning available today, with a focus on advanced techniques to boost energy efficiency for ML accelerators, such as
exploiting temporal redundancy, sparsity and reduced precision in inference and training. We will then cover some of the recent progress and challenges in implementing machine learning algorithms using
analog resistive memory devices. Finally, we will discuss spiking neural networks and the properties and advantages that are unique to them, including new algorithms applied on spatiotemporal data. The emulation of these bio-inspired mechanisms, through the physics of nanodevices, particularly memristors, will be covered.

Luca Benini holds the chair of digital Circuits and systems at ETHZ and is Full Professor at the Universita di Bologna. He received ad PhD degree from Stanford University in 1997. Dr. Benini's research interests are in energy-efficient system design, from embedded to high-performance computing. He is also active in the design ultra-low power VLSI circuits for machine learning. He is a Fellow of the IEEE, of the ACM and a member of the Academia Europaea. He is the recipient of the 2016 IEEE CAS Mac Van Valkenburg award.

Lukas Cavigelli received the M.Sc. degree in electrical engineering and information technology from ETH Zürich, Zürich, Switzerland, in 2014. Since then he has been with the Integrated Systems Laboratory, ETH Zürich, where he is pursuing a PhD degree. His current research interests include deep learning, computer vision, embedded systems, and low-power integrated circuit design. He has received the best paper award at the VLSI-SoC and the ICDSC conferences in 2013 and 2017 and the best student paper award at the Security+Defense conference in 2016.

Manuel Le Gallo is a Post-Doctoral researcher at IBM Research - Zurich, where he is currently employed in the Memory and Cognitive Technologies group. His main research interest is in using phase-change memory devices for non-von Neumann computing. Manuel holds a doctoral degree in Electrical Engineering (DrSc) from ETH Zurich (2017), a Master's degree in Electrical Engineering and Information Technology (MSc) from ETH Zurich (2014), an undergraduate degree of Cycle Ingénieur Polytechnicien from Ecole Polytechnique (l'X), Palaiseau, France (2014), as well as a Bachelor's degree in Engineering Physics (BEng) from Ecole Polytechnique de Montréal, Canada (2011).

Timoleon Moraitis is a researcher at IBM Research – Zurich, Switzerland, currently working on biologically-inspired machine learning algorithms such as spiking neural networks and their physical
implementation through hardware emulation. His research explores which neurosynaptic mechanisms can enable the next generation of cognitive machines. Previously he transitioned from the experimental and computational neuroscience of the rat’s and human’s sensory-motor system to neuromorphic engineering, during his PhD at the Institute of Neuroinformatics (INI) in Zurich. He received his diploma in applied mathematics and physics from the National Technical University of Athens, Greece.