Machine Learning Systems & Hardware

Catalog description

Course Description: Hardware architectures and systems for executing machine-learning workloads, with emphasis on dataflows, memory hierarchy, accelerator microarchitecture, hardware quantization, hardware with support for model sparsity, and hardware–software co-design.