The nearing end of Moore's Law has been driving the development of domain-specific hardware tailored to solve a special set of problems. Along these lines, probabilistic computing with inherently stochastic building blocks (p-bits) have shown significant promise, particularly in the context of hard optimization and statistical sampling problems. p-bits have been proposed and demonstrated in different hardware substrates ranging from small-scale stochastic magnetic tunnel junctions (sMTJs) in asynchronous architectures to large-scale CMOS in synchronous architectures. Here, we design and implement a truly asynchronous and medium-scale p-computer (with $\approx$ 800 p-bits) that closely emulates the asynchronous dynamics of sMTJs in Field Programmable Gate Arrays (FPGAs). Using hard instances of the planted Ising glass problem on the Chimera lattice, we evaluate the performance of the asynchronous architecture against an ideal, synchronous design that performs parallelized (chromatic) exact Gibbs sampling. We find that despite the lack of any careful synchronization, the asynchronous design achieves parallelism with comparable algorithmic scaling in the ideal, carefully tuned and parallelized synchronous design. Our results highlight the promise of massively scaled p-computers with millions of free-running p-bits made out of nanoscale building blocks such as stochastic magnetic tunnel junctions.
翻译:摩尔法律的接近尾声一直在推动开发针对特定领域的硬件以解决一系列特殊问题。 沿着这些线条,我们设计和实施一个真正零星和中等规模的计算机(使用800美元方块)的概率计算方法(使用800美元方位)显示了巨大的希望, 特别是在硬优化和统计抽样问题的背景下。 p比特已经提出, 并表现在不同的硬件基层中, 从小型蒸碎式磁隧道连接点(sMTJs)到同步结构中的大规模CMOS。 我们利用固定式结构的硬性岩玻璃问题(sMTJs)到同步结构中的大型CMOS。 在这里,我们设计和实施一个真正零星和中等规模的计算机(使用800美元方位方位)的超同步和中等规模的计算机计算机(使用800美元方位),它密切地模仿了实地可编程的SMTJs的无序动态。 我们发现,尽管没有精确的平流式的平流式模型,但我们的平流式的平流式的平流式结构也实现了平行的同步。