6 papers
Propius: A Platform for Collaborative Machine Learning across the Edge and the Cloud
Eric Ding
Collaborative Machine Learning is a paradigm in the field of distributed machine learning, designed to address the challenges of data privacy, communication overhead, and model het…
Morphlux: Transforming Torus Fabrics for Efficient Multi-tenant ML
Abhishek Vijaya Kumar, Eric Ding, Arjun Devraj +2
We develop Morphlux, a server-scale programmable photonic fabric to interconnect accelerators within servers. We show that augmenting state-of-the-art torus-based ML data-centers w…
Photonic Rails in ML Datacenters
Eric Ding, Chuhan Ouyang, Rachee Singh
Rail-optimized network fabrics have become the de facto datacenter scale-out fabric for large-scale ML training. However, the use of high-radix electrical switches to provide all-t…
Efficient AllReduce with Stragglers
Arjun Devraj, Eric Ding, Abhishek Vijaya Kumar +2
Distributed machine learning workloads use data and tensor parallelism for training and inference, both of which rely on the AllReduce collective to synchronize gradients or activa…
LUMION: Fast Fault Recovery for ML Jobs Using Programmable Optical Fabrics
Abhishek Vijaya Kumar, Eric Ding, Arjun Devraj +2
When accelerators fail in modern ML datacenters, operators migrate the affected ML training or inference jobs to entirely new racks. This approach, while preserving network perform…
PipSwitch: A Circuit Switch Using Programmable Integrated Photonics
Eric Ding, Rachee Singh
We present an optical circuit switch design for programmable integrated photonics (PIPs). Our solution finds the correct and optimal set of matchings that provides all-to-all netwo…