用于人工智能应用的热力学计算系统
Denis Melanson1, Mohammad Abu Khater1, Maxwell Aifer1
1Normal Computing Corporation, New York, NY, USA.
Nature communications
|April 22, 2025
概括
研究人员开发了一个新的随机处理单元,一个小规模的热力学计算机,以加速人工智能 (AI) 任务. 这种基于物理的硬件展示了人工智能快速,低功耗计算的潜力,特别是对于概率和生成模型.
科学领域:
- 基于物理的计算计算.
- 人工智能 硬件加速 硬件加速
- 热力学计算系统 热力学计算系统
背景情况:
- 人工智能算法的进步需要新的计算硬件.
- 现有的硬件限制了人工智能的全部潜力,特别是在复杂的任务中.
- 基于物理的方法为高效的AI计算提供了潜力.
研究的目的:
- 介绍一款新的小规模热力学计算机,即随机处理单元.
- 为了证明硬件对人工智能原始的能力,如采样和线性代数.
- 探索基于物理的硬件,以加速人工智能应用.
主要方法:
- 使用RLC电路作为单元细胞构建一个随机处理单元.
- 通过打印电路板上的开关容量,8个单元电池的全对全合.
- 使用热力学计算机进行高斯取样和矩阵反转的实验演示.
主要成果:
- 一个小规模的热力学计算设备的成功实施.
- 证明高斯取样,一个关键的概率AI原始.
- 执行矩阵反转,展示热力学线性代数的能力.
结论:
- 随机处理单元显示出加速AI原始体的承诺.
- 热力学计算为快速,低功耗的人工智能硬件提供了可行的途径.
- 这种硬件的扩展版本可能会对概率AI应用产生重大影响.
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