Prerequisites

• COMS W3157 Advanced Programming or CSEE W3827 Fundamentals of Computer Systems or Prior Experience with C(++) Programming (e.g., pointers, arrays, and memory management)
• COMS W3251 Computational Linear Algebra (or equivalents)
• MATH UN1201 Calculus III (or equivalents)
• Please contact the instructor if you have relevant prior experience but do not have prerequisites

Course Overview

Many stages of state-of-the-art robotics pipelines rely on the solutions of underlying optimization algorithms. Unfortunately, many of these approaches rely on simplifications and conservative approximations in order to reduce their computational complexity and support online operation. At the same time, parallelism has been used to significantly increase the throughput of computationally expensive algorithms across the field of computer science. And, with the widespread adoption of parallel computing platforms such as GPUs, it is natural to consider whether these architectures can benefit robotics researchers interested in solving computationally constrained problems online. This course will provide students with an introduction to both parallel programming on GPUs as well as numerical optimization. It will then dive into the intersection of those fields through case studies of recent state-of-the-art research and culminate in a team-based final project.

Learning Outcomes

By the end of the semester, you will be able to:

• Understand the opportunities and limitations of parallel programming on GPUs
• Understand the opportunities and challenges of numerical optimization algorithms
• Engage critically with recent research on parallel optimization algorithms for robotics
• Collaborate with a team to develop and present an open-ended final project

Waiting List

This class is capped at 75 students. This semester, I am handling the waitlist as an instructor-controlled waiting list. Students will be admitted based on a combination of seniority, interests in the class, and contributions to a diverse set of viewpoints and experiences in the class. Half of the available slots will be reserved for Barnard students (assuming sufficient demand). To be considered for the class, please join the waiting list AND fill out the form at https://bit.ly/COMS3159-SP24-WL, which asks a few questions about your background and your interests in the class.

Office Hours

The most up-to-date schedule of office hours can be found here. I will also try to respond to requests emailed to bplancher+courses@barnard.edu within 36 hours during the weekdays and within 48 hours over the weekend. Faster response time will be achieved via the course Slack.