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Survey details LLM-driven automation for GPU kernel generation

By PulseAugur Editorial · [1 sources] ·

A new survey paper explores the use of large language models (LLMs) and agentic systems for automating the generation and optimization of GPU kernels. These kernels are crucial for the performance of AI systems, but their manual creation is a time-consuming and non-scalable process. The paper aims to provide a structured overview of current LLM-driven approaches, datasets, and benchmarks, while also outlining future research directions in this rapidly evolving field. AI

IMPACT Automating GPU kernel generation with LLMs could significantly accelerate AI system development and performance.

RANK_REASON This is a survey paper on a research topic. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

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

Survey details LLM-driven automation for GPU kernel generation

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This is a survey paper on a research topic. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Yang Yu, Peiyu Zang, Chi Hsu Tsai, Haiming Wu, Yixin Shen, Jialing Zhang, Haoyu Wang, Zhiyou Xiao, Jingze Shi, Yuyu Luo, Wentao Zhang, Chunlei Men, Guang Liu, Yonghua Lin ·

    Towards Automated Kernel Generation in the Era of LLMs

    arXiv:2601.15727v3 Announce Type: replace Abstract: The performance of modern AI systems is fundamentally constrained by the quality of their underlying GPU kernels, which translate high-level algorithmic semantics into low-level hardware operations. Achieving near-optimal kernel…

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