The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Power aware page allocation
Open accessAbstract
One of the major challenges of post-PC computing is the need to reduce energy consumption, thereby extending the lifetime of the batteries that power these mobile devies. Memory is a particularly important target for efforts to improve energy efficiency. Memory technology is becoming available that offers power management features such as the ability to put individual chips in any one of several different power modes. In this paper we explore the interaction of page placement with static and dynamic hardware policies to exploit these emerging hardware features. In particular, we consider page allocation policies that can be employed by an informed operating system to complement the hardware power management strategies. We perform experiments using two complementary simulation environments: a trace-driven simulator with workload traces that are representative of mobile computing and an execution-driven simulator with a detailed processor/memory model and a more memory-intensive set of benchmarks (SPEC2000). Our results make a compelling case for a cooperative hardware/software approach for exploiting power-aware memory, with down to as little as 45% of the Energy Delay for the best static policy and 1% to 20% of the Energy Delay for a traditional full-power memory.
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Karlin, A. R., Manasse, M. S., Rudolph, L., & Sleator, D. D. (1988) · Algorithmica · doi:10.1007/bf01762111 · Cited by 631 · cited 1×
“A particularly valuable approach is based on the \ski rent-to-buy" problem formulation for competitive algorithms [22, 25].”
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Cited by
A Survey of Energy Efficient Network Protocols for Wireless Networks
Jones, C. E., Sivalingam, K. M., Agrawal, P., & Chen, J. C. (2001) · Wireless Networks · doi:10.1023/a:1016627727877 · Cited by 837
Ensemble-level Power Management for Dense Blade Servers
Ranganathan, P., Leech, P., Irwin, D., & Chase, J. (2006) · ACM SIGARCH Computer Architecture News · doi:10.1145/1150019.1136492 · Cited by 357
Autonomic Power & Performance Management for Large-Scale Data Centers
Khargharia, B., Hariri, S., Szidarovszky, F., Houri, M., El-Rewini, H., Khan, S. U., Ahmad, I., & Yousif, M. S. (2007) · 2007 IEEE International Parallel and Distributed Processing Symposium · doi:10.1109/ipdps.2007.370510 · Cited by 60
A survey of architectural techniques for DRAM power management
Mittal, S. (2012) · International Journal of High Performance Systems Architecture · doi:10.1504/ijhpsa.2012.050990 · Cited by 46
Metadata
- Authors
- Lebeck, A. R., Fan, X., Zeng, H., & Ellis, C.
- Venue
- ACM SIGPLAN Notices
- Published
- 2000-11
- Volume
- 35
- Issue
- 11
- Pages
- 105-116
- ISSN
- 0362-1340 (ISSN-L)
- 1558-1160
- OpenAlex
- W2100384468
- Cited by
- 370
- References
- 1
- FWCI
- 31.89
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Lebeck, A. R., Fan, X., Zeng, H., & Ellis, C. (2000). Power aware page allocation. ACM SIGPLAN Notices. https://doi.org/10.1145/356989.356999
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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.