RAI

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 built RAI, a secure and extensible system for delivering open-ended programming assignments configured with access to different hardware and software requirements. More details in the paper and docs are at RAI Docs

Cheng Li
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).

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