Recent breakthroughs in artificial intelligence (AI) algorithms have
highlighted the need for novel computing hardware in order to truly unlock the
potential for AI. Physics-based hardware, such as thermodynamic computing, has
the potential to provide a fast, low-power means to accelerate AI primitives,
especially generative AI and probabilistic AI. In this work, we present the
first continuous-variable thermodynamic computer, which we call the stochastic
processing unit (SPU). Our SPU is composed of RLC circuits, as unit cells, on a
printed circuit board, with 8 unit cells that are all-to-all coupled via
switched capacitances. It can be used for either sampling or linear algebra
primitives, and we demonstrate Gaussian sampling and matrix inversion on our
hardware. The latter represents the first thermodynamic linear algebra
experiment. We also illustrate the applicability of the SPU to uncertainty
quantification for neural network classification. We envision that this
hardware, when scaled up in size, will have significant impact on accelerating
various probabilistic AI applications.

近期人工智能算法的突破强调了真正释放人工智能潜力所需的新型计算硬件的需求。本文介绍了第一个连续变量热力学计算机，称为随机处理单元 (SPU)，它由 RLC 电路组成，在一个印刷电路板上，有 8 个单元，通过开关电容进行全对全耦合。我们展示了 SPU 在高斯采样、矩阵求逆等方面的应用，以及在神经网络分类的不确定性量化中的适用性，我们预计当该硬件规模扩大时，将对加速各种概率性人工智能应用产生重大影响。