This webinar is focused on the Horovod distributed deep learning framework and the reference architecture and service(s) built for supporting it. The aim of the presented works is to enable the efficient utilization of cloud resources in the heavily resource intensive task of distributed deep learning. The concept of reference architectures is also briefly presented, along with the experiences gained from their continous development.
30′ talk + 15′ demo + 15′ Q&A
e-Infrastructure platform and technology providers and those researching or applying (distributed) deep learning at any level.