A Python Framework for SPICE Circuit Simulation of In-Memory Analog Computing Circuits

TL;DR

This paper introduces IMAC-Sim, a Python-based SPICE simulation framework designed for exploring and optimizing in-memory analog computing circuits, considering device-level parameters and interconnect parasitics.

Contribution

The paper presents IMAC-Sim, a novel simulation tool that automates circuit generation, evaluates performance metrics, and incorporates partitioning techniques for IMAC architectures.

Findings

IMAC-Sim accurately models device and circuit-level parameters.

The framework evaluates power, latency, and accuracy of IMAC circuits.

Partitioning techniques improve reliability in IMAC simulations.

Abstract

With the increased attention to memristive-based in-memory analog computing (IMAC) architectures as an alternative for energy-hungry computer systems for data-intensive applications, a tool that enables exploring their device- and circuit-level design space can significantly boost the research and development in this area. Thus, in this paper, we develop IMAC-Sim, a circuit-level simulator for the design space exploration and multi-objective optimization of IMAC architectures. IMAC-Sim is a Python-based simulation framework, which creates the SPICE netlist of the IMAC circuit based on various device- and circuit-level hyperparameters selected by the user, and automatically evaluates the accuracy, power consumption and latency of the developed circuit using a user-specified dataset. IMAC-Sim simulates the interconnect parasitic resistance and capacitance in the IMAC architectures, and is also equipped with horizontal and vertical partitioning techniques to surmount these reliability challenges. In this abstract, we perform controlled experiments to exhibit some of the important capabilities of the IMAC-Sim.