FedLess: Secure and Scalable Serverless Federated Learning - Mohak Chadha
Channel: The Linux Foundation
Date: 2023-10-04

FedLess: Secure and Scalable Serverless Federated Learning - Mohak Chadha, Technical University of Munich

Federated learning (FL) is a machine learning paradigm that enables the collaborative training of a shared global model across distributed clients while keeping the training data local. However, conventional FL systems face several challenges such as limited scalability, complex infrastructure management, and wasted compute and incurred costs due to idling clients. These challenges of FL systems closely align with the several advantages that an emerging cloud paradigm called serverless computing has to offer. These include rapid scalability, no infrastructure management, automatic scaling to zero for idle clients, and a fine-grained pay-per-use billing model. This talk will describe FedLess, an open-source cloud-agnostic framework that enables scalable FL for training arbitrary DNN models using serverless platforms such as AWS Lambda, Google Cloud Functions, and Azure functions. This talk will then discuss the different built-in strategies in FedLess to address common challenges in scalable FL such as stragglers and resource heterogeneity among clients. Finally, a demo for using FedLess to set up a client federation for training will be presented. This talk will be beneficial for those who are interested in FL and want to learn more about serverless computing.