Ising-ReRAM: A Low Power Ising Machine ReRAM Crossbar for NP Problems

TL;DR

This paper presents a ReRAM-based Ising machine architecture implemented in CMOS technology that efficiently solves NP-Complete problems like 3-SAT with high accuracy and promising energy scalability.

Contribution

It introduces a novel ReRAM crossbar implementation of an Ising model for 3-SAT, demonstrating high accuracy and scalable energy profiling for large problem instances.

Findings

Achieved 91% accuracy in matrix representation of 3-SAT.

Measured linear energy growth for sub-matrix problem structures.

Demonstrated potential for scalable NP-Complete problem solving architectures.

Abstract

Computational workloads are growing exponentially, driving power consumption to unsustainable levels. Efficiently distributing large-scale networks is an NP-Complete problem equivalent to Boolean satisfiability (SAT), making it one of the core challenges in modern computation. To address this, physics and device inspired methods such as Ising systems have been explored for solving SAT more efficiently. In this work, we implement an Ising model equivalence of the 3-SAT problem using a ReRAM crossbar fabricated in the Skywater 130 nm CMOS process. Our ReRAM-based algorithm achieves $91.0\%$ accuracy in matrix representation across iterative reprogramming cycles. Additionally, we establish a foundational energy profile by measuring the energy costs of small sub-matrix structures within the problem space, demonstrating under linear growth trajectory for combining sub-matrices into larger problems. These results demonstrate a promising platform for developing scalable architectures to accelerate NP-Complete problem solving.