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Horizontal Federated Learning with Intel® Trust Domain Extensions (Intel® TDX) on VMware® ESXi

June 6, 3:45 PM - 4:05 PM
Imperial Room A

Intel® Trust Domain Extensions (Intel® TDX) is designed to isolate Trust Domain (TD) VMs from the hypervisor and other non-TD software on the host platform to enhance confidential computing from broad range of software attacks. Federated Learning is a machine learning algorithm that allows a model to be trained across multiple decentralized nodes without explicitly exchanging local data samples.

In this session, we describe the use case of running Federated Learning to train a global machine learning model collaboratively across a network of Trust Domains running on VMware® ESXi while keeping the sensitive data localized.

About the speakers

Kuo-Lang Tseng

Software Engineer, Intel Corporation

Software development and technical lead.

Sanrio Alvares

Software Engineer, Intel Corporation

Sanrio is a Software Engineer with experience in system software engineering, particularly focused on Kernel/BIOS software. His role covers all aspects of software development, spanning the addition of new features, debugging problems, and fine-tuning code for better performance. His interests outside of work are varied and include but are not limited to playing music, soccer, and keeping my BMI in check.