Annealing

A 28-nm Digital Compute-in-Memory Ising Annealer With Asynchronous Random Number Generator for Traveling Salesman Problem

A 28-nm Digital Compute-in-Memory Ising Annealer With Asynchronous Random Number Generator for Traveling Salesman Problem 150 150

Abstract:

This work presents a compact digital compute-in-memory (DCIM) Ising annealer targeting large-scale combinatorial optimization. A centroid-based weight mapping method combined with hierarchical clustering reduces the memory capacity required for traveling salesman problem (TSP) weights, enabling efficient mapping with limited on-chip storage. An asynchronous random number generator (ARNG) based on dual …

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FIMA: A Scalable Ferroelectric Compute-in-Memory Annealer for Accelerating Boolean Satisfiability

FIMA: A Scalable Ferroelectric Compute-in-Memory Annealer for Accelerating Boolean Satisfiability 150 150

Abstract:

In-memory compute kernels present a promising approach for addressing data-centric workloads. However, their scalability—particularly for computationally intensive tasks solving combinatorial optimization problems such as Boolean satisfiability (SAT), which are inherently difficult to decompose—remains a significant challenge. In this work, we propose a ferroelectric nonvolatile memory (NVM)-based compute-in-memory …

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RXO-LDPC: A Physics-Inspired Relaxation Oscillator-Based Solver Leveraging Six-Body Spin Interactions for Soft Decoding of LDPC Codes

RXO-LDPC: A Physics-Inspired Relaxation Oscillator-Based Solver Leveraging Six-Body Spin Interactions for Soft Decoding of LDPC Codes 150 150

Abstract:

Physics-inspired computing harnesses continuous-time (CT) operation, massive parallelism, and direct compute load mapping to coupled CMOS-based spins to accelerate solving complex optimization problems. This work advances the field by introducing relaxation oscillator (RXO)-low-density parity check (LDPC), a combinatorial optimization problem (COP) engine that natively supports six-body spin interactions for …

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