The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Quasar: resource-efficient and QoS-aware cluster management
Abstract
Cloud computing promises flexibility and high performance for users and high cost-efficiency for operators. Nevertheless, most cloud facilities operate at very low utilization, hurting both cost effectiveness and future scalability.
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Citations
Cites
The PARSEC benchmark suite: characterization and architectural implications
Bienia, C., Kumar, S., Singh, J. P., & Li, K. (2008) · Proceedings of the 17th international conference on Parallel architectures and compilation techniques · doi:10.1145/1454115.1454128 · Cited by 3,444
Dean, J., & Barroso, L. A. (2013) · Communications of the ACM · doi:10.1145/2408776.2408794 · Cited by 1,852
Cited by
Large-scale cluster management at Google with Borg
Verma, A., Pedrosa, L., Korupolu, M., Oppenheimer, D., Tune, E., & Wilkes, J. (2015) · Proceedings of the Tenth European Conference on Computer Systems · doi:10.1145/2741948.2741964 · Cited by 1,468
Resource Management with Deep Reinforcement Learning
Mao, H., Alizadeh, M., Menache, I., & Kandula, S. (2016) · Proceedings of the 15th ACM Workshop on Hot Topics in Networks · doi:10.1145/3005745.3005750 · Cited by 1,353
Gan, Y., Zhang, Y., Cheng, D., Shetty, A., Rathi, P., Katarki, N., Bruno, A., Hu, J., Ritchken, B., Jackson, B., et al. (2019) · Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems · doi:10.1145/3297858.3304013 · Cited by 665
Self-citationHeracles: improving resource efficiency at scale
Lo, D., Cheng, L., Govindaraju, R., Ranganathan, P., & Kozyrakis, C. (2015) · Proceedings of the 42nd Annual International Symposium on Computer Architecture · doi:10.1145/2749469.2749475 · Cited by 466
Self-citationAdaptive deep learning model selection on embedded systems
Taylor, B., Marco, V. S., Wolff, W., Elkhatib, Y., & Wang, Z. (2018) · Proceedings of the 19th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems · doi:10.1145/3211332.3211336 · Cited by 90
Metadata
- Authors
- Delimitrou, C., & Kozyrakis, C.
- Venue
- Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
- Publisher
- ACM
- Published
- 2014-02-24
- Pages
- 127-144
- OpenAlex
- W2160121678
- Cited by
- 702
- References
- 2
- FWCI
- 63.55
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Quasar: resource-efficient and QoS-aware cluster management. https://app.cochat.ai/papers/10.1145/2541940.2541941
- The paper
- Delimitrou, C., & Kozyrakis, C. (2014). Quasar: resource-efficient and QoS-aware cluster management. Proceedings of the 19th international conference on Architectural support for programming languages and operating systems. https://doi.org/10.1145/2541940.2541941
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
