Today ISC 2017 announced a day-long Deep Learning track on June 21 as part of its technical program. The full conference takes place June 18-21 in Frankfurt, Germany.
The overwhelming success of deep learning has triggered a race to build larger artificial neural networks, using growing amounts of training data in order to allow computers to take on more complex tasks. Such work will challenge the computational feasibility of deep learning of this magnitude, requiring massive data throughput and compute power. Hence, implementing deep learning at scale has become an emerging topic for the high performance computing community.
The program is designed and chaired by deep learning experts, Dr. -Ing Janis Keuper, senior scientist at The Fraunhofer Institute for Industrial Mathematics ITWM, and Dr. Damian Borth, director of the deep learning competence center at the German Research Center for Artificial Intelligence (DFKI).
The Deep Learning Day will offer two keynotes, along with a series of talks, to give attendees up-to-date insights on the rapid development in deep learning and also demonstrate how this technology can be enabled with HPC. Also discussed will be how the computational demands of deep learning will affect current and future HPC infrastructure.
The principal topic areas include:
- How deep learning is changing the HPC landscape
- HPC and big data for autonomous driving and connected vehicles
- Future challenges for deep learning and HPC
- Zeynep Akata, Amsterdam Machine Learning Lab, University of Amsterdam (Keynoter)
- Brian van Essen, LLNL
- Costas Bekas, IBM Research Zurich
- René Wies, BMW Group
- Kai Demtröder, BMW Group
- Marco Pennachiotti, BMW Group
- Mario Tokarz, BMW Group
- Naveen Rao, Intel Data Center Group
- Achim Noller, Bosch
- Gunter Röth, NVIDIA
- Mayank Daga, Advanced Micro Devices
- Stephan Wolf, Google
Early Bird Registration is now open for ISC 2017.