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Serving and Optimizing Machine Learning Workflows on ...
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arXiv
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由 Y Wu 著作2022被引用 21 次 — Lastly, to serve and optimize ML workflows on heterogeneous infrastructures, a flexible runtime is critical such that the optimizer may explore ...
Serving and Optimizing Machine Learning Workflows on ...
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由 Y Wu 著作2022被引用 21 次 — We design and implement JellyBean, a system for serving and optimizing machine learning inference workflows on heterogeneous infrastructures.
[PDF] Serving and Optimizing Machine Learning Workflows ...
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JellyBean is designed and implemented, a system for serving and optimizing machine learning inference workflows on heterogeneous infrastructures that ...
Serving and Optimizing Machine Learning Workflows on ...
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We design and implement JellyBean, a framework for serving and optimizing machine learning inference workflows on heterogeneous infrastructures. Given service- ...
Publications | Yao Lu
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Zhuo, Y. Lu. Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures. International Conference on Very Large Data Bases (VLDB).
Matthew Lentz
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2024年10月7日 — Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures. Proc. VLDB Endow. 16(3): 406-419 (2022). [i4]. view.
Matthew Lentz | Scholars@Duke profile: Publications
Duke University
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Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures. Journal Article Proceedings of the VLDB Endowment · November 1, 2022 With ...
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Danyang Zhuo
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Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures · no code implementations • 10 May 2022 • Yongji Wu, Matthew Lentz, Danyang ...
Yongji Wu
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Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures. Y Wu, M Lentz, D Zhuo, Y Lu. Proceedings of the VLDB Endowment, Vol. 16 ...
Curated collection of papers in machine learning systems
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[VLDB'23] Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures ... [ATC'22] Serving Heterogeneous Machine Learning Models on ...
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