Distributed Machine Learning for FPGAs in the Cloud
Machine Learning (ML) is a growing area in both research and applications. Trends
include larger and larger ML models and the interest in getting results from ML with low
latency and high throughput. To address these trends, researchers are increasingly
looking at accelerators (such as Graphics Processing Units (GPUs) and Field
Programmable Gate Arrays (FPGAs), especially those that are directly connected to the
network to achieve low latency access to data.
In this talk, I will introduce the Open Cloud Testbed (OCT): https://octestbed.org/
OCT is available to researchers who are interested in conducting cloud research with
accelerators. We provide GPUS, FPGAs, and AI engines from AMD. The FPGAs and
AI engines are directly connected to the network.
I will discuss experiments on using OCT for distributed ML using multiple network
connected FPGAs. Specifically I will present results for running Resnet50 inference on
the imagenet dataset.
No hardware knowledge is assumed for this webinar.
Speaker(s): Miriam
Virtual: https://events.vtools.ieee.org/m/473027
