IEEE Access (Jan 2024)

CMOS-Based Single-Cycle in-Memory XOR/XNOR

  • Shamiul Alam,
  • Jack Hutchins,
  • Nikhil Shukla,
  • Kazi Asifuzzaman,
  • Ahmedullah Aziz

DOI
https://doi.org/10.1109/ACCESS.2024.3384752
Journal volume & issue
Vol. 12
pp. 49528 – 49534

Abstract

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Big data applications are on the rise, and so is the number of data centers. The ever-increasing massive data pool needs to be periodically backed up in a secure environment. Moreover, a massive amount of securely backed-up data is required for training binary convolutional neural networks for image classification. XOR and XNOR operations are essential for large-scale data copy verification, encryption, and classification algorithms. The disproportionate speed of existing compute and memory units makes the von Neumann architecture inefficient to perform these Boolean operations. Compute-in-memory (CiM) has proved to be an optimum approach for such bulk computations. The existing CiM-based XOR/XNOR techniques either require multiple cycles for computing or add to the complexity of the fabrication process. Here, we propose a CMOS-based hardware topology for single-cycle in-memory XOR/XNOR operations. Our design provides at least $2\times $ improvement in the latency compared with other existing CMOS-compatible solutions. We verify the proposed system through circuit/system-level simulations and evaluate its robustness using a 5000-point Monte Carlo variation analysis. This all-CMOS design paves the way for practical implementation of CiM XOR/XNOR at scaled technology nodes.

Keywords