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AI system CUDA-L2 surpasses NVIDIA's cuBLAS for matrix multiplication

By PulseAugur Editorial · [1 sources] ·

Researchers have developed CUDA-L2, a system that leverages large language models and reinforcement learning to automatically optimize matrix multiplication CUDA kernels. This system significantly outperforms existing baselines, including NVIDIA's cuBLAS and cuBLASLt libraries, by exploring a vast configuration space that is impractical for human optimization. CUDA-L2 achieves substantial speedups in both offline and simulated real-time inference scenarios, demonstrating the potential of AI-driven automation for performance-critical computational tasks. AI

IMPACT Demonstrates AI's capability to significantly enhance performance in highly optimized computational kernels, potentially impacting scientific computing and AI infrastructure.

RANK_REASON The cluster describes a new research paper detailing a novel system for optimizing computational kernels using AI techniques. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI system CUDA-L2 surpasses NVIDIA's cuBLAS for matrix multiplication

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The cluster describes a new research paper detailing a novel system for optimizing computational kernels using AI techniques. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Songqiao Su, Xiaoya Li, Albert Wang, Guoyin Wang, Jiwei Li, Chris Shum ·

    CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

    arXiv:2512.02551v3 Announce Type: replace-cross Abstract: In this paper, we propose CUDA-L2, a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimize Half-precision General Matrix Multiply (HGEMM) CUDA kernels. Using CUDA execu…

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