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Paragon: QoS-aware scheduling for heterogeneous datacenters

Delimitrou, Christina, Kozyrakis, Christos·2013·Proceedings of the eighteenth international conference on Architectural support for programming languages and operating systems

Abstract

Large-scale datacenters (DCs) host tens of thousands of diverse applications each day. However, interference between colocated workloads and the difficulty to match applications to one of the many hardware platforms available can degrade performance, violating the quality of service (QoS) guarantees that many cloud workloads require. While previous work has identified the impact of heterogeneity and interference, existing solutions are computationally intensive, cannot be applied online and do not scale beyond few applications.

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Metadata

Authors
Delimitrou, C., & Kozyrakis, C.
Venue
Proceedings of the eighteenth international conference on Architectural support for programming languages and operating systems
Publisher
ACM
Published
2013-03-16
Pages
77-88
OpenAlex
W2102709380
Cited by
617
References
1
FWCI
50.31
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Paragon: QoS-aware scheduling for heterogeneous datacenters. https://app.cochat.ai/papers/10.1145/2451116.2451125
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Delimitrou, C., & Kozyrakis, C. (2013). Paragon: QoS-aware scheduling for heterogeneous datacenters. Proceedings of the eighteenth international conference on Architectural support for programming languages and operating systems. https://doi.org/10.1145/2451116.2451125

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.