A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms

Abstract

The transistor celebrated its 75${}^{\text{th}}$ birthday in 2022. The continued scaling of the transistor defined by Moore's Law continues, albeit at a slower pace. Meanwhile, computing demands and energy consumption required by modern artificial intelligence (AI) algorithms have skyrocketed. As an alternative to scaling transistors for general-purpose computing, the integration of transistors with unconventional technologies has emerged as a promising path for domain-specific computing. In this article, we provide a full-stack review of probabilistic computing with p-bits as a representative example of the energy-efficient and domain-specific computing movement. We argue that p-bits could be used to build energy-efficient probabilistic systems, tailored for probabilistic algorithms and applications. From hardware, architecture, and algorithmic perspectives, we outline the main applications of probabilistic computers ranging from probabilistic machine learning and AI to combinatorial optimization and quantum simulation. Combining emerging nanodevices with the existing CMOS ecosystem will lead to probabilistic computers with orders of magnitude improvements in energy efficiency and probabilistic sampling, potentially unlocking previously unexplored regimes for powerful probabilistic algorithms.

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Cited by in corpus (27)

• CMOS + stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning
• Training Deep Boltzmann Networks with Sparse Ising Machines
• Experimental demonstration of an integrated on-chip p-bit core utilizing stochastic Magnetic Tunnel Junctions and 2D-MoS2 FETs
• All-to-all reconfigurability with sparse and higher-order Ising machines
• Probabilistic-Bits based on Ferroelectric Field-Effect Transistors for Stochastic Computing
• Lanthanide molecular nanomagnets as probabilistic bits
• Voltage-insensitive stochastic magnetic tunnel junctions with double free layers
• Double-Free-Layer Stochastic Magnetic Tunnel Junctions with Synthetic Antiferromagnets
• Stochastic Reservoir Computers
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