An LLM agent loop iteratively optimized a HIP GEMM kernel for AMD MI300 using only end-to-end timings, reaching about 450µs versus 850µs for the PyTorch reference.
How to optimize a CUDA matmul kernel for cuBLAS -like performance: a worklog, 12 2022
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GPU Kernel Scientist: An LLM-Driven Framework for Iterative Kernel Optimization
An LLM agent loop iteratively optimized a HIP GEMM kernel for AMD MI300 using only end-to-end timings, reaching about 450µs versus 850µs for the PyTorch reference.