Abstract
A major component of many advanced programming courses is an open-ended “end-of-term project” assignment. Delivering and evaluating open-ended parallel programming projects for hundreds or thousands of students brings a need for broad system reconfigurability coupled with challenges of testing and development uniformity, access to esoteric hardware and programming environments, scalability, and security.
We present RAI, a secure and extensible system for delivering open-ended programming assignments configured with access to different hardware and software requirements. We describe how the system was used to deliver a programming-competition-style final project in an introductory GPU programming course at the University of Illinois Urbana-Champaign.
Cheng Li
Member of Technical Staff
I specialize in building efficient AI training and inference systems using GPUs, with a focus on optimizing performance for Large Language Models (LLMs) and Large Vision Models (LVMs).