An Annealing Accelerator for Ising Spin Systems Based on In-Memory Complementary 2D FETs

Metaheuristic algorithms such as simulated annealing (SA) are often implemented for optimization in combinatorial problems, especially for discreet problems. SA employs a stochastic search, where high-energy transitions (hill-climbing) are allowed with a temperature-dependent probability to escape local optima. Ising spin glass systems have properties such as spin disorder and frustration and provide a discreet combinatorial problem with a high number of metastable states and ground-state degeneracy. In this work, subthreshold Boltzmann transport is exploited in complementary 2D field-effect transistors (p-type WSe2 and n-type MoS2) integrated with an analog, nonvolatile, and programmable floating-gate memory stack to develop in-memory computing primitives necessary for energy- and area-efficient hardware acceleration of SA for Ising spin systems. Search acceleration of >800x is demonstrated for 4 x 4 ferromagnetic, antiferromagnetic, and spin glass systems using SA compared to an exhaustive search using a brute force trial at miniscule total energy expenditure of approximate to 120 nJ. The hardware-realistic numerical simulations further highlight the astounding benefits of SA in accelerating the search for larger spin lattices.

Automated summary

This research explores the use of subthreshold Boltzmann transport and specific hardware acceleration for optimization calculations of Ising spin systems, demonstrating a search acceleration of up to 800x with SA compared to exhaustive search methods.