MAPLE: Model Aggregation and Prediction for Learned Ecosystem
Authors: 
Chetan Phalak, Dheeraj Chahal, Aniruddha Sen, Mayank Mishra, Rekha SinghalAuthors Info & Claims
Pages 17 - 18
Abstract
Many Artificial Intelligence (AI) applications are composed of multiple machine learning (ML) and deep learning (DL) models. Intelligent process automation (IPA) requires a combination (sequential or parallel) of models to complete an inference task. These models have unique resource requirements and hence exploring cost-efficient high performance deployment architecture especially on multiple clouds, is a challenge. We propose a high performance framework MAPLE, to support the building of applications using composable models. The MAPLE framework is an innovative system for AI applications to (1) recommend various model compositions (2) recommend appropriate system configuration based on the application's non-functional requirements (3) estimate the performance and cost of deployment on cloud for the chosen design.
References
[1]
Youngmin Baek, Bado Lee, Dongyoon Han, Sangdoo Yun, and Hwalsuk Lee. 2019. Character region awareness for text detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 9365--9374.
[2]
Dheeraj Chahal, Ravi Ojha, Manju Ramesh, and Rekha Singhal. 2020. Migrating Large Deep Learning Models to Serverless Architecture. In 2020 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) . 111--116. https://doi.org/10.1109/ISSREW51248.2020.00047
[3]
Dheeraj Chahal, Manju Ramesh, Ravi Ojha, and Rekha Singhal. 2021. High Performance Serverless Architecture for Deep Learning Workflows. In 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid) . IEEE, 790--796.
[4]
Daniel Crankshaw, Gur-Eyal Sela, Xiangxi Mo, Corey Zumar, Ion Stoica, Joseph Gonzalez, and Alexey Tumanov. 2020. InferLine: Latency-Aware Provisioning and Scaling for Prediction Serving Pipelines (SoCC '20). Association for Computing Machinery, New York, NY, USA, 477--491. https://doi.org/10.1145/3419111.3421285
[5]
Zhi Tian, Weilin Huang, He Tong, Pan He, and Yu Qiao. 2016. Detecting Text in Natural Image with Connectionist Text Proposal Network, Vol. 9912. 56--72. https://doi.org/10.1007/978--3--319--46484--8_4
Index Terms
- MAPLE: Model Aggregation and Prediction for Learned Ecosystem
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Information
Published In
July 2022
166 pages
ISBN:9781450391597
DOI:10.1145/3491204
- General Chairs:
- Dan Feng,
- Steffen Becker,
- Program Chairs:
- Nikolas Herbst,
- Philipp Leitner
Copyright © 2022 Owner/Author.
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Association for Computing Machinery
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Published: 19 July 2022
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ICPE '22
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ICPE '22: ACM/SPEC International Conference on Performance Engineering
April 9 - 13, 2022
Bejing, China
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ICPE '22 Paper Acceptance Rate 14 of 58 submissions, 24%;
Overall Acceptance Rate 252 of 851 submissions, 30%
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