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The author developed a Lean4-to-TileLang tensor program superoptimizer that automatically generates optimized accelerator kernels and derives hyperparameter scaling laws, achieving a 1.8x speedup on A100 GPUs.
Researchers from Carnegie Mellon, University of Washington, and Arm propose AdaExplore, an LLM agent framework for GPU kernel code generation that achieves 3.12× and 1.72× speedups on KernelBench Level-2 and Level-3 benchmarks through failure-driven adaptation and diversity-preserving search, without additional fine-tuning.