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AgenticCANN

Source
arxiv.org
Author
Junhao Qiu, Zidong Wang, Yansong Sun, Zhitong Ma, Ping Guo, Qingfu Zhang
Date
Why it matters

Shows how to get code-gen agents working on a hardware stack the models barely saw in training: inject structured, staged domain knowledge instead of relying on CUDA-style priors, with measured feasibility and speedup gains.

Terms in this piece · Glossary
  • inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.
  • LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
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