Teaching and Course Material

Courses

Spring 2024: Hardware Software Co-Design for Machine Learning

Course Objectives

This course aims to present recent advancements that strive to achieve efficient processing of DNNs. Specifically, it will offer an overview of DNNs, delve into techniques to distribute the workload, dive into various architectures and systems that support DNNs, and highlight key trends in recent techniques for efficient processing. These techniques aim to reduce the computational and communication costs associated with DNNs, either through hardware and system optimizations. The course will also provide a summary of various development resources to help researchers and practitioners initiate DNN deployments swiftly. Additionally, it will emphasize crucial benchmarking metrics and design considerations for evaluating the rapidly expanding array of DNN hardware designs, system optimizations, proposed in both academia and industry.