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Computer Science > Emerging Technologies

arXiv:2304.09252 (cs)
[Submitted on 18 Apr 2023]

Title:IMAC-Sim: A Circuit-level Simulator For In-Memory Analog Computing Architectures

Authors:Md Hasibul Amin, Mohammed E. Elbtity, Ramtin Zand
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Abstract:With the increased attention to memristive-based in-memory analog computing (IMAC) architectures as an alternative for energy-hungry computer systems for machine learning 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 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. Moreover, 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. IMAC-Sim is a flexible tool that supports a broad range of device- and circuit-level hyperparameters. In this paper, we perform controlled experiments to exhibit some of the important capabilities of the IMAC-Sim, while the entirety of its features is available for researchers via an open-source tool.
Subjects: Emerging Technologies (cs.ET); Hardware Architecture (cs.AR); Machine Learning (cs.LG)
Cite as: arXiv:2304.09252 [cs.ET]
  (or arXiv:2304.09252v1 [cs.ET] for this version)
  https://doi.org/10.48550/arXiv.2304.09252
Journal reference: Proceedings of the Great Lakes Symposium on VLSI 2023 (GLSVLSI '23), Association for Computing Machinery, New York, NY, USA, 659-664
Related DOI: https://doi.org/10.1145/3583781.3590264

Submission history

From: Md Hasibul Amin [view email]
[v1] Tue, 18 Apr 2023 19:22:34 UTC (3,446 KB)
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