AI and Hardware. (1-0) 1 Credit Hour

Catalog description

Prerequisite: MAT 1073 . This course introduces students to the relationship between AI algorithms and modern computing hardware. Students will examine how hardware architectures, including CPUs, GPUs, TPUs, and specialized AI accelerators, influence the performance, efficiency, and scalability of AI systems. Topics include parallel computing, memory hierarchies, and data movement, as well as emerging paradigms such as edge AI and neuromorphic computing. Through modern case studies and practical exercises, students learn how to assess and optimize AI systems with respect to hardware constraints, energy efficiency, scalability, and system-level design considerations. Course Fees: DL01 $25; IUCA $15; LTAI $13.61.