For the Distinguished Lecture in April, MAKI and emergenCITY could win Professor Torsten Hoefler from ETH Zurich. We are looking forward to his talk on “Designing network support for High-Performance Deep Learning Systems” on April 20, 2023 at 16:15 and cordially invite all interested to attend the Zoom talk:

  • Date: 20.04.2023 at 4:15 p.m.
  • Speaker: Professor Torsten Hoefler, ETH Zürich, Switzerland
  • Title: *Designing Network Support for High-Performance Deep Learning Systems *
  • Join Zoom
In the talk, David F. Bacon will explain the principles for training large-scale AI models efficiently

The talk will cover principles for training large-scale AI models efficiently and how to design AI systems for this purpose. It will focus on discussing networking support for distributed large-scale AI training based on the fast that much of the progress in modern artificial intelligence is made by scaling to larger and larger deep learning models trained with more data. One such example is the GPT-3 model with 175 billion parameters that forms the basis for many services like Microsoft’s Copilot and ChatGPT. The talk will also explain how networking support can help with distributed training of these models. We will discuss communication patterns in AI and derive a design for a specialized network topology that improves cost per bandwidth by nearly 15 times.

Speaker Bio

Torsten Hoefler is a Professor of Computer Science at ETH Zurich, a member of Academia Europaea, and a Fellow of the ACM and IEEE. His research interests revolve around the central topic of “Performance-centric System Design” and include scalable networks, parallel programming techniques, and performance modeling. Torsten won best paper awards at the ACM/IEEE Supercomputing Conference SC10, SC13, SC14, SC19, SC22, EuroMPI’13, HPDC’15, HPDC’16, IPDPS’15, and other conferences. He published numerous peer-reviewed scientific conference and journal articles and authored chapters of the MPI-2.2 and MPI-3.0 standards. He received the IEEE CS Sidney Fernbach Award, the ACM Gordon Bell Prize, the Latsis prize of ETH Zurich, as well as both ERC starting and consolidator grants. Additional information about Torsten can be found on his homepage.