CUDA-L2: AI-Optimized Matrix Multiplication Outperforms NVIDIA cuBLAS
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dzign
Hand-rolled, kettle-boiled, baked to perfection. Worth every minute at the bakery.
Summary
CUDA-L2 is a system that uses large language models and reinforcement learning to automatically optimize half-precision matrix multiplication CUDA kernels. The system systematically outperforms major matrix multiplication baselines including torch.matmul and NVIDIA's closed-source libraries (cuBLAS, cuBLASLt-heuristic, cuBLASLt-AutoTuning) across various GPU configurations including RTX 3090, A100, and H100. The research demonstrates significant speedups over existing solutions through AI-driven optimization of HGEMM kernels.
Key quotes
· 3 pulledCUDA-L2 is a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimize Half-precision General Matrix Multiply (HGEMM) CUDA kernels.
CUDA-L2 systematically outperforms major matmul baselines to date, from the widely-used torch.matmul to state-of-the-art NVIDIA closed-source libraries (cuBLAS, cuBLASLt-heuristic, cuBLASLt-AutoTuning).
Summary of CUDA-L2 speedup over baselines across all GPU configurations (RTX 3090-F32F16F16F32, A100-F16F16F16F16, A100-F32F16F16F32, H100-F32F16F16F32) in Offline and S
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