Serverless Performance Optimization
Serverless Performance Optimization is a performance optimization methodology that specifically addresses the unique constraints and characteristics of serverless computing environments, distinguishing itself from traditional optimization approaches by focusing on event-driven execution, cold start mitigation, resource allocation granularity, and ephemeral state management inherent to Function-as-a-Service platforms.
58
Publications
2.7K
Citations
194
Authors
87
Institutions
Publications per year
2017–2026
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Parents
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Characterizing serverless platforms with serverlessbench
Tianyi Yu, Qingyuan Liu, Dong Du et al. · 2020 · 184 citations
BATCH: Machine Learning Inference Serving on Serverless Platforms with Adaptive Batching
Ahsan Ali, Riccardo Pinciroli, Feng Yan et al. · 2020 · 170 citations
Towards Demystifying Serverless Machine Learning Training
2021 · 102 citations · Full text
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Microsoft (United States)
Redmond, United States
3 h-index
3 publications
159 citations
Purdue University West Lafayette
West Lafayette, United States
3 h-index
11 publications
312 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
3 publications
88 citations

University of Waterloo
Waterloo, Canada
3 h-index
5 publications
231 citations
Northeastern University
Boston, United States
2 h-index
5 publications
195 citations

Beijing Institute of Technology
Beijing, China
2 h-index
3 publications
77 citations

York University
Toronto, Canada
2 h-index
3 publications
139 citations

University of British Columbia
Vancouver, Canada
2 h-index
2 publications
74 citations
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Repository · 4 publications · 279 citations
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2 publications · 72 citations
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1 publications · 15 citations
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1 publications · 17 citations
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1 publications · 37 citations
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