XbarSim: A Decomposition-Based Memristive Crossbar Simulator
Anzhelika Kolinko, Md Hasibul Amin, Ramtin Zand, Jason Bakos

TL;DR
XbarSim is a fast, open-source circuit-level simulator for memristive crossbars that enables efficient analysis of in-memory computing architectures, supporting parasitic modeling and batch processing.
Contribution
It introduces XbarSim, a novel LU decomposition-based simulator that significantly accelerates memristive crossbar analysis compared to traditional tools.
Findings
Achieves orders of magnitude speedup over HSPICE
Supports modeling of interconnect parasitics
Enables batch processing of inputs
Abstract
Given the growing focus on memristive crossbar-based in-memory computing (IMC) architectures as a potential alternative to current energy-hungry machine learning hardware, the availability of a fast and accurate circuit-level simulation framework could greatly enhance research and development efforts in this field. This paper introduces XbarSim, a domain-specific circuit-level simulator designed to analyze the nodal equations of memristive crossbars. The first version of XbarSim, proposed herein, leverages the lower-upper (LU) decomposition approach to solve the nodal equations for the matrices associated with crossbars. The XbarSim is capable of simulating interconnect parasitics within crossbars and supports batch processing of the inputs. Through comprehensive experiments, we demonstrate that the XbarSim can achieve orders of magnitude speedup compared to HSPICE across various sizes…
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Taxonomy
TopicsAdvanced Memory and Neural Computing · Neural dynamics and brain function · Neural Networks and Reservoir Computing
