Machine Learning Day at ISC 2018

Within the last few years, machine learning has become a vital topic within the HPC community. This is true of both vendors, who see the development as an opportunity to expand their high-performance solutions into a new and fast-growing market, and traditional HPC users, who are increasingly incorporating these techniques into their workflows to speed processing and extract greater insights.

As a result, ISC High Performance will provide a special focus on this subject matter with a one-day track on Wednesday, June 27. It is being led by Program Co-Chairs Janis Keuper, of the Fraunhofer Institute for Industrial Mathematics (ITWM) and Brian van Essen, from Lawrence Livermore National Laboratory (LLNL).

Attendance will require a Conference Pass.

Principal topic areas include:

  • How machine learning applications are changing HPC architectures
  • Challenges towards scalable machine learning on HPC systems
  • Software for machine learning on HPC
  • How the technology is being applied, by both commercial users and researchers 


Chairs - Dr.-Ing. Janis Keuper & Dr. Brian Van Essen

  • “Janis
  • Brian Van Essen

Keynotes and Speakers Confirmed to Date

Two keynotes, along with a series of talks, will give attendees up-to-date insights on the rapid development in machine learning and also demonstrate how this technology can be enabled with HPC. For this, we have lined up a range of speakers from industry, academia, and the vendor community to share their expertise in this area.

Our two keynote presenters are Jack Wells (ORNL), who will deliver a talk about the Summit architecture for machine learning, and Frank Hutter (University of Freiburg), who will speak about automatic machine learning.

Our current list of speakers for invited talks includes:

For the full Machine Learning Day program click here.


The Student Cluster Competition and Machine Learning

On the same day, student teams participating in the student cluster competition (SCC), will compete on an image-recognition task using TensorFlow, a popular open source library used for machine learning. The specific details of the task can be found here.

Attendees are encouraged to visit the SCC during session breaks to witness the graduate, undergraduate and even some high-school students grapple with real world machine learning problems.

The SCC is organized by ISC High Performance and the HPC Advisory Council.