6.5930/1 Hardware Architecture for Deep Learning - Spring 2026

Top Course Info Staff Announcements Syllabus Reading List Recitations Collaboration Policy

Overview Introduction to the design and implementation of hardware architectures for efficient processing of deep learning algorithms and tensor algebra in AI systems. Topics include basics of deep learning, optimization principles for programmable platforms, design principles of accelerator architectures, co-optimization of algorithms and hardware (including sparsity) and use of advanced technologies (including memristors and optical computing). Includes labs involving modeling and analysis of hardware architectures, architecting deep learning inference systems, and an open-ended design project. Students taking graduate version complete additional assignments. Course Information Warning: All information on this website is subject to change. Though we send messages to the class in case of a change, please do check the course web site in case of doubt. Lectures: Lectures will be from 1:00PM to 2:30 PM every Monday and Wednesday. Recitations: A 1-hour recitation session will be held each week on Friday at 11 AM. Office Hours: See the staff page and piazza for details. Laboratory Exercises: There will be four Laboratory Exercises. Lab 0: Infrastructure Setup Lab 1: Analyze and Evaluate DNN Workloads Lab 2: Hardware Design & Mapping Lab 3: Advanced Mapping: Parallelism and Fusion Lab 4: Sparsity Lab 5: Compute in Memory (CiM) Final Design Project: You will be able to apply concepts and tools learnt from the class to the final project. You could either choose from a list of suggested projects or propose own project (requires formal proposal and approval by course staff). It is recommended to use the tools from the labs (e.g. PyTorch, AccelForge). Grades: Five Labs: 50% Lab 0: 1 pt Lab 1: 12 pts Lab 2: 25 pts Lab 3: 25 pts Lab 4: 25 pts Lab 5: 25 pts Final Design Project: 50% Milestone 1: 15 pts Milestone 2: 10 pts Milestone 3: 5 pts Project Proposal: 5 pts Final project: 115 pts Late Policy for Labs: You should always submit your labs on time. Nonetheless, since unexpected situations, like illnesses, might occur, you have a budget of 5 late days to spend on the labs. We will not grant any additional extensions, so please use these days carefully. The budget is spent in increments of 1 day, and you may not use more than 2 days per lab. If you submit your lab later than two days after the deadline, or if you are late and have no budget left, your submission will not count towards your grade. However, you must complete all the labs to pass the course. You do not need to inform us about your use of your budget. The course staff will keep track of the days you have spent. No late days for project due to tight timeline Course Reading Material: See the reading list page for details. Communication: Please check for announcements, clarifications to assignments, and answers to common questions on Piazza: https://piazza.com/class/mk1k5bkzf8c69a. You can also contact all the course staff via Piazza, and contact the TAs only via email.