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English(EN) Autonomous Optimization of Numerical Algorithms by an AI Agent: Application to Atomistic Simulation

AI代理自主优化原子模拟数值算法

研究人员开发了AIOA,一个AI代理框架,旨在自主优化原子模拟的数值算法。该代理在一个改进循环中运行,重写代码以加快执行速度,并重新设计方法以改进收敛性。当应用于ASE库时,AIOA显著加速了六个内核,使用Python配合NumPy和SciPy平均速度提高了22-24倍。此外,与L-BFGS等现有方法相比,优化后的算法在结构弛豫和反应路径计算方面所需的力评估次数大大减少。 AI

影响 这项研究展示了一种通过AI驱动的算法优化来加速科学计算的新方法,可能影响依赖复杂模拟的领域。

排序理由 该集群包含一篇详细介绍用于算法优化的新AI框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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AI代理自主优化原子模拟数值算法

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该集群包含一篇详细介绍用于算法优化的新AI框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jeheon Woo ·

    AI Agent自主优化数值算法:应用于原子模拟

    arXiv:2611.13143v1 Announce Type: cross Abstract: Coding agents built on large language models, run in automated improvement loops, can discover more efficient algorithms. We present AIOA, a framework that brings this approach to the numerical algorithms of atomistic simulation: …