AI RESEARCH
AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization
arXiv CS.LG
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ArXi:2511.15915v2 Announce Type: replace We present AccelOpt, a self-improving large language model (LLM) agentic system that autonomously optimizes kernels for emerging AI acclerators, eliminating the need for expert-provided hardware-specific optimization knowledge. AccelOpt explores the kernel optimization space through iterative generation, informed by an optimization memory that curates experiences and insights from previously encountered slow-fast kernel pairs.