research-article

DENT: A Tool for Tagging Stack Overflow Posts with Deep Learning Energy Patterns

Authors:

Shriram Shanbhag,

Sridhar Chimalakonda,

Vibhu Saujanya Sharma,

Vikrant KaulgudAuthors Info & Claims

ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Pages 2157 - 2161

https://doi.org/10.1145/3611643.3613092

Published: 30 November 2023 Publication History

Abstract

Energy efficiency has become an important consideration in deep learning systems. However, it remains a largely under-emphasized aspect during the development. Despite the emergence of energy-efficient deep learning patterns, their adoption remains a challenge due to limited awareness. To address this gap, we present DENT (Deep Learning Energy Pattern Tagger, a Chrome extension used to add "energy pattern tags" to the deep learning related questions from Stack Overflow. The idea of DENT is to hint to the developers about the possible energy-saving opportunities associated with the Stack Overflow post through energy pattern labels. We hope this will increase awareness about energy patterns in deep learning and improve their adoption. A preliminary evaluation of DENT achieved an average precision of 0.74, recall of 0.66, and an F1-score of 0.65 with an accuracy of 66%. The demonstration of the tool is available at https://youtu.be/S0Wf_w0xajw and the related artifacts are available at https://rishalab.github.io/DENT/

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Cited By

Duran PCastaño JGómez CMartínez-Fernández Sd'Amorim M(2024)GAISSALabel: A Tool for Energy Labeling of ML ModelsCompanion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering10.1145/3663529.3663811(622-626)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3663529.3663811

Index Terms

DENT: A Tool for Tagging Stack Overflow Posts with Deep Learning Energy Patterns
1. Software and its engineering
  1. Software notations and tools
    1. Software maintenance tools

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Published In

cover image ACM Conferences

ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering

November 2023

2215 pages

ISBN:9798400703270

DOI:10.1145/3611643

General Chair:
Satish Chandra
Google, USA
,
Program Chairs:
Kelly Blincoe
University of Auckland, New Zealand
,
Paolo Tonella
USI Lugano, Switzerland

Copyright © 2023 ACM.

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Published: 30 November 2023

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ESEC/FSE '23: 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering

December 3 - 9, 2023

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Cited By

Duran PCastaño JGómez CMartínez-Fernández Sd'Amorim M(2024)GAISSALabel: A Tool for Energy Labeling of ML ModelsCompanion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering10.1145/3663529.3663811(622-626)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3663529.3663811

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