Towards Demystifying Serverless Machine Learning Training
Summary: Systematic study of ML training on FaaS vs IaaS; LambdaML enables fair benchmarking and optimization/synchronization options. Key result: serverless helps only for low-communication, fast-converging models; overall FaaS is faster but not cheaper than IaaS. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiawei Jiang (ETH Zurich)
- 2. Shaoduo Gan (ETH Zurich)
- 3. Yue Liu (ETH Zurich)
- 4. Fanlin Wang (ETH Zurich)
- 5. Gustavo Alonso (ETH Zurich)
- 6. Ana Klimovic (ETH Zurich)
- 7. Ankit Singla (ETH Zurich)
- 8. Wentao Wu (Microsoft)
- 9. Ce Zhang (ETH Zurich)
BibTeX Citation
@inproceedings{jiang_sigmod21,
title = {{Towards Demystifying Serverless Machine Learning Training}},
author = {Jiang, Jiawei and Gan, Shaoduo and Liu, Yue and Wang, Fanlin and Alonso, Gustavo and Klimovic, Ana and Singla, Ankit and Wu, Wentao and Zhang, Ce},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3459240},
url = {https://dl.acm.org/doi/10.1145/3448016.3459240},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,114 | Serverless Data Science - Are We There Yet? A Case Study of Model Serving | 2022 | SIGMOD | 5.6982359e-05 |
| 8,101 | SDP_PIPE: A Semi-Decentralized Framework for Heterogeneity-aware Pipeline-parallel Training | 2023 | VLDB | 5.4870581e-05 |
| 9,000 | Optimizing Inference Serving on Serverless Platforms | 2022 | VLDB | 5.3350531e-05 |
| 9,881 | The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format | 2024 | SIGMOD | 5.2040783e-05 |
| 10,236 | FaaSBoard: Efficient Graph Processing with a Disaggregated Architecture on Serverless Services | 2026 | SIGMOD | 5.093636e-05 |
| 10,912 | ArrayMorph: Optimizing Hyperslab Queries on the Cloud for Machine Learning Pipelines | 2025 | VLDB | 5.093636e-05 |
| 11,089 | Nitro: Boosting Distributed Reinforcement Learning with Serverless Computing | 2025 | VLDB | 5.093636e-05 |
| 11,112 | Off-the-shelf Data Analytics on Serverless | 2024 | CIDR | 5.093636e-05 |
| 11,587 | CDI-E: An Elastic Cloud Service for Data Engineering | 2022 | VLDB | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 9,469 | How Can We Train Deep Learning Models Across Clouds and Continents? An Experimental Study | 2024 | VLDB |
| 2 | 4,987 | Releasing Cloud Databases from the Chains of Performance Prediction Models | 2017 | CIDR |
| 3 | 3,543 | A Comparison of Platforms for Implementing and Running Very Large Scale Machine Learning Algorithms | 2014 | SIGMOD |
| 4 | 10,236 | FaaSBoard: Efficient Graph Processing with a Disaggregated Architecture on Serverless Services | 2026 | SIGMOD |
| 5 | 1,937 | Elastic Machine Learning Algorithms in Amazon SageMaker | 2020 | SIGMOD |
| 6 | 1,007 | Serverless Computing: One Step Forward, Two Steps Back | 2019 | CIDR |
| 7 | 1,784 | Lambada: Interactive Data Analytics on Cold Data Using Serverless Cloud Infrastructure | 2020 | SIGMOD |
| 8 | 11,112 | Off-the-shelf Data Analytics on Serverless | 2024 | CIDR |
| 9 | 9,000 | Optimizing Inference Serving on Serverless Platforms | 2022 | VLDB |
| 10 | 7,114 | Serverless Data Science - Are We There Yet? A Case Study of Model Serving | 2022 | SIGMOD |