AI Processor Architecture, Design Principles, and Performance

Understand how AI processors are built, optimized, and deployed across diverse computing environments.

  • 0.5 CEU/ 5 PDH credits
  • Launched 2026
  • 5 courses
  • 5 hours

Course Description

This course program, developed by IEEE Educational Activities with the support from the IEEE Computer Society, provides a comprehensive exploration of the architectures, design principles, and performance foundations that define modern AI processors. Positioned at the intersection of computational design, electrical engineering, and machine learning, the program equips participants with a structured understanding of how AI processors are built, optimized, and deployed across diverse computing environments.

Course Objectives

  • Seven key focus areas that define the architectural, design, and performance foundations of modern AI processors
  • Fundamental AI processor architectures
  • Design principles for AI hardware
  • Performance analysis and optimization
  • Advanced AI chip architectures
  • Neural processing unit foundations
  • Architectural evolution and technology trends
  • Deployment across computing environments

Authors and Instructors

Dr. Santhosh Sivasubramani

Working group chair of IEC/IEEE P62659™, the International Standard for Nanomanufacturing in Large Scale Manufacturing for Nanoelectronics

Dr. Santhosh Sivasubramani is the working group chair of IEC/IEEE P62659™, the International Standard for Nanomanufacturing in Large Scale Manufacturing for Nanoelectronics. Sivasubramani is a Senior Member of IEEE as well as a member of the IEEE Nanotechnology Council Technical Committee 12 on Nanomagnetics and the IEEE Task Force on Rebooting Computing. Sivasubramani won the IEEE Member Geographic Activities Young Professional Achievement Award in 2023. He is a contributor to the IEEE International Roadmap of Devices and Systems: Beyond CMOS Working Group Report, in addition to serving as the IEEE NTC Standards Committee Secretary. Dr. Sivasubramani gained post-Ph.D. academic and industrial experience in the Advanced Embedded Systems and IC Design Laboratory and the Nanomagnetics Research Lab, demonstrating a versatile blend of expertise. He also contributes as a Track/Session Chair for IEEE international conferences and Founder of RSL Quantum. Dr. Sivasubramani graduated with a Ph.D. in Rebooting Computing from the Indian Institute of Technology Hyderabad (IITH).

Explore the Full Library

Related Articles

AI Semiconductor Packaging

AI in Advanced Semiconductor Packaging: Why Engineers Need New Skills for Next‑Generation Chips

Article
GenAI Training

Engineering’s Next Competitive Edge: Smarter Communication With Generative AI

Article
AI for Power Engineers, AI for Energy, AI for electrical engineers

Powering the Future: Why AI Literacy is the New Standard for Energy Professionals

Article