research-article

Designing Energy-Efficient Decision Tree Memristor Crossbar Circuits Using Binary Classification Graphs

Authors:

Sunny RajAuthors Info & Claims

ICCAD '22: Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design

Article No.: 36, Pages 1 - 9

https://doi.org/10.1145/3508352.3549448

Published: 22 December 2022 Publication History

Abstract

We propose a method to design in-memory, energy-efficient, and compact memristor crossbar circuits for implementing decision trees using flow-based computing. We develop a new tool called binary classification graph, which is equivalent to decision trees in accuracy but uses bit values of input features to make decisions instead of thresholds. Our proposed design is resilient to manufacturing errors and can scale to large crossbar sizes due to the utilization of sneak paths in computations. Our design uses zero transistor and one memristor (0T1R) crossbars with only two resistance states of high and low, which makes it resilient to resistance drift and radiation degradation. We test the performance of our designs on multiple standard machine learning datasets and show that our method utilizes circuits of size 5.23 × 10^-3 mm² and uses 20.5 pJ per decision, and outperforms state-of-the-art decision tree acceleration algorithms on these metrics.

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Cited By

Sinha PChavan ARaj S(2024)Designing Energy-Efficient PATH-based Decision Tree Memristor Crossbar Circuits2024 IEEE 24th International Conference on Nanotechnology (NANO)10.1109/NANO61778.2024.10628690(209-213)Online publication date: 8-Jul-2024
https://doi.org/10.1109/NANO61778.2024.10628690

Index Terms

Designing Energy-Efficient Decision Tree Memristor Crossbar Circuits Using Binary Classification Graphs
1. Applied computing
  1. Physical sciences and engineering
    1. Electronics
2. Hardware

Index terms have been assigned to the content through auto-classification.

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cover image ACM Conferences

ICCAD '22: Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design

October 2022

1467 pages

ISBN:9781450392174

DOI:10.1145/3508352

Conference Chair:
Tulika Mitra
National University of Singapore
,
Program Chairs:
Evangeline Young
The Chinese University of Hong Kong
,
Jinjun Xiong
University at Buffalo (UB)

Copyright © 2022 ACM.

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Published: 22 December 2022

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ICCAD '22: IEEE/ACM International Conference on Computer-Aided Design

October 30 - November 3, 2022

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Cited By

Sinha PChavan ARaj S(2024)Designing Energy-Efficient PATH-based Decision Tree Memristor Crossbar Circuits2024 IEEE 24th International Conference on Nanotechnology (NANO)10.1109/NANO61778.2024.10628690(209-213)Online publication date: 8-Jul-2024
https://doi.org/10.1109/NANO61778.2024.10628690

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