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Ferroelectric compute-in-memory annealer for combinatorial optimization problems.

Authors :
Yin, Xunzhao
Qian, Yu
Vardar, Alptekin
Günther, Marcel
Müller, Franz
Laleni, Nellie
Zhao, Zijian
Jiang, Zhouhang
Shi, Zhiguo
Shi, Yiyu
Gong, Xiao
Zhuo, Cheng
Kämpfe, Thomas
Ni, Kai
Source :
Nature Communications; 3/18/2024, Vol. 15 Issue 1, p1-11, 11p
Publication Year :
2024

Abstract

Computationally hard combinatorial optimization problems (COPs) are ubiquitous in many applications. Various digital annealers, dynamical Ising machines, and quantum/photonic systems have been developed for solving COPs, but they still suffer from the memory access issue, scalability, restricted applicability to certain types of COPs, and VLSI-incompatibility, respectively. Here we report a ferroelectric field effect transistor (FeFET) based compute-in-memory (CiM) annealer for solving larger-scale COPs efficiently. Our CiM annealer converts COPs into quadratic unconstrained binary optimization (QUBO) formulations, and uniquely accelerates in-situ the core vector-matrix-vector (VMV) multiplication operations of QUBO formulations in a single step. Specifically, the three-terminal FeFET structure allows for lossless compression of the stored QUBO matrix, achieving a remarkably 75% chip size saving when solving Max-Cut problems. A multi-epoch simulated annealing (MESA) algorithm is proposed for efficient annealing, achieving up to 27% better solution and ~ 2X speedup than conventional simulated annealing. Experimental validation is performed using the first integrated FeFET chip on 28nm HKMG CMOS technology, indicating great promise of FeFET CiM array in solving general COPs.Yin et al. realize a FeFET based compute-in-memory annealer as an efficient combinatorial optimization solver through algorithm-hardware co-design with a FeFET chip, matrix lossless compression, and a multi-epoch simulated annealing algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20411723
Volume :
15
Issue :
1
Database :
Complementary Index
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
176133090
Full Text :
https://doi.org/10.1038/s41467-024-46640-x