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
Senior Researcher
My work focus on optimizing inference/training of Deep Learning models, particularly on Transformers (LLMs).