@inproceedings{f0a4a4659109452e84c035d1ffb46fc8,
title = "SCiMA: A Generic Single-Cycle Compute-in-Memory Acceleration Scheme for Matrix Computations",
abstract = "This work proposes a new generic Single-cycle Compute-in-Memory (CiM) Accelerator for matrix computation named SCiMA. SCiMA is developed on top of the existing commodity Spin-Orbit Torque Magnetic Random-Access Memory chip. Every sub-array's peripherals are transformed to realize a full set of single-cycle 2-and 3-input in-memory bulk bitwise functions specifically designed to accelerate a wide variety of graph and matrix multiplication tasks. We explore SCiMA's efficiency by selecting a complex matrix processing operation, i.e., calculating determinant as an essential and under-explored application in the CiM domain. The cross-layer device-to-architecture simulation framework shows the presented platform can reduce energy consumption by 70.43% compared with the most recent CiM designs implemented with the same memory technology. SCiMA also achieves up to 2.5x speedup compared with current CiM platforms.",
keywords = "Computing in-memory, Determinant, SOT-MRAM",
author = "Sepehr Tabrizchi and Shaahin Angizi and Arman Roohi",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022 ; Conference date: 27-05-2022 Through 01-06-2022",
year = "2022",
doi = "10.1109/ISCAS48785.2022.9937332",
language = "English (US)",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "576--580",
booktitle = "IEEE International Symposium on Circuits and Systems, ISCAS 2022",
address = "United States",
}