Intelligent Sampling: A Novel Approach to Optimize Workload Scheduling in Large-Scale Heterogeneous Computing Continuum-Reference-Cited by-同舟云学术

Intelligent Sampling: A Novel Approach to Optimize Workload Scheduling in Large-Scale Heterogeneous Computing Continuum

Published:2023-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Service-Oriented System Engineering (SOSE)
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Author:

Pujol Victor Casamayor¹^ORCID,Morichetta Andrea¹^ORCID,Nastic Stefan¹^ORCID

Affiliation:

1. Distributed Systems Group,TU Wien,Austria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10254733/10254738/10254740.pdf?arnumber=10254740

Reference40 articles.

1. MLaaS in the wild: Workload analysis and scheduling in Large-Scale heterogeneous GPU clusters;weng;19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22),2022

2. HEROS: Energy-Efficient Load Balancing for Heterogeneous Data Centers

3. AuctionWhisk: Using an auction‐inspired approach for function placement in serverless fog platforms

4. A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services

5. A Novel Middleware for Efficiently Implementing Complex Cloud-Native SLOs

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2. Markov Blanket Composition of SLOs;2024 IEEE International Conference on Edge Computing and Communications (EDGE);2024-07-07

3. Invited Paper: DeepSLOs for the Computing Continuum;Proceedings of the 2024 Workshop on Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating algorithms for Distributed systems;2024-06-17