The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
PARTIES: QoS-Aware Resource Partitioning for Multiple Interactive Services
Open accessAbstract
Multi-tenancy in modern datacenters is currently limited to a single latency-critical, interactive service, running alongside one or more low-priority, best-effort jobs. This limits the efficiency gains from multi-tenancy, especially as an increasing number of cloud applications are shifting from batch jobs to services with strict latency requirements. We present PARTIES, a QoS-aware resource manager that enables an arbitrary number of interactive, latency-critical services to share a physical node without QoS violations. PARTIES leverages a set of hardware and software resource partitioning mechanisms to adjust allocations dynamically at runtime, in a way that meets the QoS requirements of each co-scheduled workload, and maximizes throughput for the machine. We evaluate PARTIES on state-of-the-art server platforms across a set of diverse interactive services. Our results show that PARTIES improves throughput under QoS by 61% on average, compared to existing resource managers, and that the rate of improvement increases with the number of co-scheduled applications per physical host.
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Cites
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The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
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Large-scale cluster management at Google with Borg
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“The irst approach is to simply disallow interactive services from sharing resources with other applications to avoid interference [42, 43, 51, 53].”
BackgroundDelay scheduling: a simple technique for achieving locality and fairness in cluster scheduling
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Self-citation
Cited by
DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency
Stojkovic, J., Zhang, C., Goiri, Í., Torrellas, J., & Choukse, E. (2025) · 2025 IEEE International Symposium on High Performance Computer Architecture (HPCA) · doi:10.1109/hpca61900.2025.00102 · Cited by 112
Metadata
- Authors
- Chen, S., Delimitrou, C., & Martínez, J. F.
- Venue
- Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems
- Publisher
- ACM
- Published
- 2019-04-04
- Pages
- 107-120
- OpenAlex
- W2926143647
- Cited by
- 267
- References
- 44
- FWCI
- 23.21
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Chen, S., Delimitrou, C., & Martínez, J. F. (2019). PARTIES: QoS-Aware Resource Partitioning for Multiple Interactive Services. Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems. https://doi.org/10.1145/3297858.3304005
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