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IAS-Seminar "Towards scalable AI: Opportunities & challenges of distributed Deep Learning"

Anfang
26.01.2021 10:00 Uhr
Ende
26.01.2021 11:00 Uhr
Veranstaltungsort
online via Zoom

Referent:

Dr. Peter Labus, Large Scale Deep Learning Team Lead, Fraunhofer Institute for Industrial Mathematics ITWM, Kaiserslautern, Germany

Abstract:

Much of the recent progress in Deep Learning has been achieved through datasets and Deep Neural Networks (DNNs) growing in size, thereby reaching the limits of the available hardware and software capabilities.

In this talk, I will give an overview of the opportunities High Performance Computing can provide to scale and improve Deep Learning methods. I will particularly focus on our recent work using Neural Architecture Search to minimize the energy consumption for DNN inference on FPGAs, as well as our Deep Learning framework Tarantella for distributed DNN training on CPUs and GPUs.

Zeit:

Dienstag, 26. Januar 2021, 10.00-11.00 Uhr

Ort:

Online via Zoom

https://uni-wuppertal.zoom.us/j/99606167252?pwd=UTlIaThRNUtsZmkxUVEybXpRKzFiQT09

Meeting ID: 996 0616 7252
Passcode: 2NJVdi1k