✨CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning
📝 Summary:
CUDA-L2 uses LLMs and reinforcement learning to optimize Half-precision General Matrix Multiply CUDA kernels. It significantly outperforms major baselines like cuBLAS and torch.matmul, achieving up to 28.7% speedup in server mode. This demonstrates AI can enhance even highly optimized kernels.
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02551
• PDF: https://arxiv.org/pdf/2512.02551
• Github: https://github.com/deepreinforce-ai/CUDA-L2
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For more data science resources:
✓ https://t.iss.one/DataScienceT
#CUDA #ReinforcementLearning #LLM #MatrixMultiplication #AI
📝 Summary:
CUDA-L2 uses LLMs and reinforcement learning to optimize Half-precision General Matrix Multiply CUDA kernels. It significantly outperforms major baselines like cuBLAS and torch.matmul, achieving up to 28.7% speedup in server mode. This demonstrates AI can enhance even highly optimized kernels.
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02551
• PDF: https://arxiv.org/pdf/2512.02551
• Github: https://github.com/deepreinforce-ai/CUDA-L2
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#CUDA #ReinforcementLearning #LLM #MatrixMultiplication #AI
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