Keynote

"Machine-Learning & Hardware Machine-Learning: A Lot Already, And Yet, Just The Beginning"
by Olivier Temam, Google

In this talk, I will reflect on ~5 years of research and engineering in hardware machine-learning, the journey we are on, the difficulties for the academic & industrial community to find the right paths, the remarkable progress we have collectively achieved, the challenges and choices ahead of us, and just how fascinating this journey is.


Olivier Temam was an academic till 2014, working on the design of hardware accelerators for machine-learning. He led teams at Inria, France, and a joint Inria-ICT (China) lab, on ML accelerators, where he designed the DianNao series of HW ML accelerators. He was also professor in computer architecture at Ecole Polytechnique, France. In June 2014, he joined Google to work on TPUs, and he now leads one of the TPU teams.

Invited Talk

"From the R&D lab to mass-production, a case study in tenacity"
by David Moloney, Intel Corporation

David Moloney is Director of Machine Vision Technology, NTG at Intel Corporation and formerly the Chief Technology Officer of Movidius. David has a BEng in Electronic Engineering Dublin City University 1985 and PhD from Trinity College Dublin in 2010 in the area of FPGA-based HPC for Computational Fluid Dynamics. David has worked in the semiconductor industry internationally for the past 28 years with Infineon in Germany, ST Microelectronics Italy, Parthus-Ceva (Ceva-DSP) and FrontierSilicon in Ireland, before founding Movidius in 2005 with Sean Mitchell. David has 31 granted patents and numerous publications. He acts as a reviewer for IEEE communications magazine and for the EU Commission on programs such as ARTEMIS. David is a member of the EU FP7 HiPEAC NoE and collaborates on the FP7 PHEPPER and EXCESS projects as well as the Eyes of Things (EoT) Horizon 2020 project. His interests Include Processor architecture, Computer Vision Algorithms and HW acceleration and systems, hardware and multiprocessor design for DSP communications, HPC and multimedia applications.

Lecturers

The topics of this year's Summer School will be presented by the following world-class experts:

The structure of the Summer School is such that the participants will have the opportunity to intensely interact with the lecturers during the full duration of the summer school (during meals, breaks, evening activities). All lecturers will stay on campus during the full week.


Courses

The summer school consists of 12 courses spread over two morning slots and two afternoon slots. Per slot there are three parallel courses of which you can take only one. When applying for admission, you will be asked to indicate your preference.

The courses have been allocated to slots in such a way that it is in any case possible to create a summer school program that matches your research interests.