A self-improving LLM agent with optimization memory raises average kernel throughput from 45-49% to 59-61% of peak on Trainium accelerators and matches proprietary models at 26x lower cost.
Users could also explicitly annotate the partition dimension with par_dim from nki.language
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AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization
A self-improving LLM agent with optimization memory raises average kernel throughput from 45-49% to 59-61% of peak on Trainium accelerators and matches proprietary models at 26x lower cost.