Shriram Shanbhag
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/
- Brunno Abreu, Mateus Grellert, and Sergio Bampi. 2022. A framework for designing power-efficient inference accelerators in tree-based learning applications. Engineering Applications of Artificial Intelligence, 109 (2022), 104638.
Google Scholar
Digital Library
- Lasse F Wolff Anthony, Benjamin Kanding, and Raghavendra Selvan. 2020. Carbontracker: Tracking and predicting the carbon footprint of training deep learning models. arXiv preprint arXiv:2007.03051.
Google Scholar
- Stefanie Beyer and Martin Pinzger. 2015. Synonym suggestion for tags on stack overflow. In 2015 IEEE 23rd International Conference on Program Comprehension. 94–103.
Google ScholarDigital Library
- Cody Blakeney, Xiaomin Li, Yan Yan, and Ziliang Zong. 2020. Parallel blockwise knowledge distillation for deep neural network compression. IEEE Transactions on Parallel and Distributed Systems, 32, 7 (2020), 1765–1776.
Google ScholarCross Ref
- Jordi Cabot, Javier Luis Cánovas Izquierdo, Valerio Cosentino, and Belén Rolandi. 2015. Exploring the use of labels to categorize issues in open-source software projects. In 2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER). 550–554.
Google ScholarCross Ref
- Ruichu Cai, Boyan Xu, Zhenjie Zhang, Xiaoyan Yang, Zijian Li, and Zhihao Liang. 2018. An Encoder-Decoder Framework Translating Natural Language to Database Queries. In IJCAI.
Google Scholar
- Ana Cardoso-Cachopo and Arlindo L Oliveira. 2007. Semi-supervised single-label text categorization using centroid-based classifiers. In Proceedings of the 2007 ACM symposium on Applied computing. 844–851.
Google ScholarDigital Library
- Yu-Hsin Chen, Tushar Krishna, Joel S Emer, and Vivienne Sze. 2016. Eyeriss: An energy-efficient reconfigurable accelerator for deep convolutional neural networks. IEEE journal of solid-state circuits, 52, 1 (2016), 127–138.
Google ScholarDigital Library
- Luis Cruz and Rui Abreu. 2019. Catalog of energy patterns for mobile applications. Empirical Software Engineering, 24, 4 (2019), 2209–2235.
Google ScholarDigital Library
- Xuefeng Du, Xin Wang, Gabriel Gozum, and Yixuan Li. 2022. Unknown-Aware Object Detection: Learning What You Don’t Know from Videos in the Wild. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 13678–13688.
Google ScholarCross Ref
- Maarten Grootendorst. 2020. KeyBERT: Minimal keyword extraction with BERT.. https://doi.org/10.5281/zenodo.4461265
Google ScholarCross Ref
- Hu Guan, Jingyu Zhou, and Minyi Guo. 2009. A class-feature-centroid classifier for text categorization. In Proceedings of the 18th international conference on World wide web. 201–210.
Google ScholarDigital Library
- Awni Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, and Adam Coates. 2014. Deep speech: Scaling up end-to-end speech recognition. arXiv preprint arXiv:1412.5567.
Google Scholar
- Junda He, Bowen Xu, Zhou Yang, DongGyun Han, Chengran Yang, and David Lo. 2022. PTM4Tag: Sharpening Tag Recommendation of Stack Overflow Posts with Pre-trained Models. In 2022 IEEE/ACM 30th International Conference on Program Comprehension (ICPC).
Google ScholarDigital Library
- Faria Huq, Masum Hasan, Md Mahim Anjum Haque, Sazan Mahbub, Anindya Iqbal, and Toufique Ahmed. 2022. Review4Repair: Code review aided automatic program repairing. Information and Software Technology, 143 (2022), 106765.
Google ScholarDigital Library
- Von Ithipathachai and Maral Azizi. 2022. Are tags’ it?’ analysis of the impact of tags on StackOverflow questions. In Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing. 1483–1490.
Google Scholar
- Eray Mert Kavuk and Ayse Tosun. 2020. Predicting Stack Overflow question tags: a multi-class, multi-label classification. In Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops. 489–493.
Google ScholarDigital Library
- Can Li, Ling Xu, Meng Yan, and Yan Lei. 2020. TagDC: A tag recommendation method for software information sites with a combination of deep learning and collaborative filtering. Journal of Systems and Software, 170 (2020), 110783.
Google ScholarCross Ref
- Zhi-Gang Liu, Paul N Whatmough, Yuhao Zhu, and Matthew Mattina. 2022. S2TA: Exploiting Structured Sparsity for Energy-Efficient Mobile CNN Acceleration. In 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA). 573–586.
Google ScholarCross Ref
- Suman Kalyan Maity, Abhishek Panigrahi, Sayan Ghosh, Arundhati Banerjee, Pawan Goyal, and Animesh Mukherjee. 2019. DeepTagRec: A content-cum-user based tag recommendation framework for stack overflow. In European Conference on Information Retrieval. 125–131.
Google ScholarDigital Library
- Nitin Rathi, Priyadarshini Panda, and Kaushik Roy. 2018. STDP-based pruning of connections and weight quantization in spiking neural networks for energy-efficient recognition. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 38, 4 (2018), 668–677.
Google ScholarCross Ref
- Tiago Santos, Keith Burghardt, Kristina Lerman, and Denis Helic. 2020. Can Badges Foster a More Welcoming Culture on Q&A Boards? Proceedings of the International AAAI Conference on Web and Social Media, 14, 1 (2020), May, 969–973.
Google Scholar
- Shriram Shanbhag, Sridhar Chimalakonda, Vibhu Saujanya Sharma, and Vikrant Kaulgud. 2022. eTagger-An Energy Pattern Tagging Tool for GitHub Issues in Android Projects. In 2022 IEEE International Conference on Software Maintenance and Evolution (ICSME). 484–488.
Google ScholarCross Ref
- Shriram Shanbhag, Sridhar Chimalakonda, Vibhu Saujanya Sharma, and Vikrant Kaulgud. 2022. Towards a Catalog of Energy Patterns in Deep Learning Development. In The International Conference on Evaluation and Assessment in Software Engineering 2022. 150–159.
Google ScholarDigital Library
- Akhila Sri Manasa Venigalla and Sridhar Chimalakonda. 2021. StackEmo: towards enhancing user experience by augmenting stack overflow with Emojis. In Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. 1550–1554.
Google ScholarDigital Library
- Shaowei Wang, David Lo, Bogdan Vasilescu, and Alexander Serebrenik. 2014. EnTagRec: An Enhanced Tag Recommendation System for Software Information Sites. In 2014 IEEE International Conference on Software Maintenance and Evolution (ICSME). 291–300.
Google Scholar
- Shaowei Wang, David Lo, Bogdan Vasilescu, and Alexander Serebrenik. 2018. EnTagRec++: An enhanced tag recommendation system for software information sites. Empirical Software Engineering, 23, 2 (2018), 800–832.
Google ScholarDigital Library
- Di Wu, Xiao-Yuan Jing, Hongyu Zhang, Bing Li, Yu Xie, and Baowen Xu. 2021. Generating API tags for tutorial fragments from stack overflow. Empirical Software Engineering, 26, 4 (2021), 1–37.
Google ScholarDigital Library
- Tien-Ju Yang, Yu-Hsin Chen, and Vivienne Sze. 2017. Designing energy-efficient convolutional neural networks using energy-aware pruning. In Proceedings of the IEEE conference on computer vision and pattern recognition. 5687–5695.
Google ScholarCross Ref
- Jian Zhang, Hailong Sun, Yanfei Tian, and Xudong Liu. 2018. Semantically enhanced tag recommendation for software CQAs via deep learning. In Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings. 294–295.
Google ScholarDigital Library
- Pingyi Zhou, Jin Liu, Zijiang Yang, and Guangyou Zhou. 2017. Scalable tag recommendation for software information sites. In 2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER). 272–282.
Google ScholarCross Ref
Index Terms
- DENT: A Tool for Tagging Stack Overflow Posts with Deep Learning Energy Patterns
Recommendations
Towards a Catalog of Energy Patterns in Deep Learning Development
EASE '22: Proceedings of the 26th International Conference on Evaluation and Assessment in Software EngineeringThe exponential rise of deep learning, aided by the availability of several frameworks and specialized hardware, has led to its application in a wide variety of domains. The availability of GPUs has made it easier to train networks with a huge number ...
Automated Summarization of Stack Overflow Posts
ICSE '23: Proceedings of the 45th International Conference on Software EngineeringSoftware developers often resort to Stack Overflow (SO) to fill their programming needs. Given the abundance of relevant posts, navigating them and comparing different solutions is tedious and time-consuming. Recent work has proposed to automatically ...
Mining energy traces to aid in software development: an empirical case study
ESEM '14: Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and MeasurementContext: With the advent of increased computing on mobile devices such as phones and tablets, it has become crucial to pay attention to the energy consumption of mobile applications.
Goal: The software engineering field is now faced with a whole new ...
Comments