The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Energy management for commercial servers
Abstract
Servers: high-end, multiprocessor systems running commercial workloads, have typically included extensive cooling systems and resided in custom-built rooms for high-power delivery. Recently, as transistor density and demand for computing resources have rapidly increased, even these high-end systems face energy-use constraints. Commercial-server energy management now focuses on conserving power in the memory and microprocessor subsystems. Because their workloads are typically structured as multiple application programs, system-wide approaches are more applicable to multiprocessor environments in commercial servers than techniques that primarily apply to single-application environments, such as those based on compiler optimizations.
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Cites
Managing energy and server resources in hosting centers
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Power and energy management for server systems
Bianchini, R., & Rajamony, R. (2004) · Computer · doi:10.1109/mc.2004.217 · Cited by 453
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The Case for Power Management in Web Servers
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Self-citationEnergy-Efficient Server Clusters
Elnozahy, E. N., Kistler, M., & Rajamony, R. (2003) · Lecture Notes in Computer Science · doi:10.1007/3-540-36612-1_12 · Cited by 246
Self-citationEnergy conservation policies for web servers
Elnozahy, M., Kistler, M., & Rajamony, R. (2003) · Cited by 210
Self-citationDesign and implementation of power-aware virtual memory
Huang, H., Pillai, P. S., & Shin, K. G. (2003) · Cited by 161
IBM Memory Expansion Technology (MXT)
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Cited by
Data Center Energy Consumption Modeling: A Survey
Dayarathna, M., Wen, Y., & Fan, R. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2481183 · Cited by 1,165
pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems
Verma, A., Ahuja, P., & Neogi, A. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-89856-6_13 · Cited by 649
MANTIS OS: An Embedded Multithreaded Operating System for Wireless Micro Sensor Platforms
Bhatti, S., Carlson, J., Dai, H., Deng, J., Rose, J., Sheth, A., Shucker, B., Gruenwald, C., Torgerson, A., & Han, R. (2005) · Mobile Networks and Applications · doi:10.1007/s11036-005-1567-8 · Cited by 437
Processing data where it makes sense: Enabling in-memory computation
Mutlu, O., Ghose, S., Gómez-Luna, J., & Ausavarungnirun, R. (2019) · Microprocessors and Microsystems · doi:10.1016/j.micpro.2019.01.009 · Cited by 300
Scalable high performance main memory system using phase-change memory technology
Qureshi, M. K., Srinivasan, V., & Rivers, J. A. (2009) · ACM SIGARCH Computer Architecture News · doi:10.1145/1555815.1555760 · Cited by 294
Metadata
- Authors
- Lefurgy, C., Rajamani, K., Rawson, F., Felter, W., Kistler, M., & Keller, T. W.
- Venue
- Computer
- Published
- 2003-12
- Volume
- 36
- Issue
- 12
- Pages
- 39-48
- ISSN
- 0018-9162 (ISSN-L)
- OpenAlex
- W2110860124
- Cited by
- 473
- References
- 16
- FWCI
- 23.44
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Energy management for commercial servers. https://app.cochat.ai/papers/10.1109/mc.2003.1250880
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- Lefurgy, C., Rajamani, K., Rawson, F., Felter, W., Kistler, M., & Keller, T. W. (2003). Energy management for commercial servers. Computer. https://doi.org/10.1109/mc.2003.1250880
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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.
