article · ACM SIGMETRICS Performance Evaluation Review · 2013
Elastic paging
Cited by 1Abstract and details only
Abstract
We study a generalization of the classic paging problem where memory capacity can vary over time - a property of many modern computing realities, from cloud computing to multi-core and energy-optimized processors. We show that good performance in the "classic" case provides no performance guarantees when memory capacity fluctuates: roughly speaking, moving from static to dynamic capacity can mean the difference between optimality within a factor 2 in space, time and energy, and suboptimality by an arbitrarily large factor. Surprisingly, several classic paging algorithms still perform remarkably well, maintaining that factor 2 optimality even if faced with adversarial capacity fluctuations - without taking those fluctuations into explicit account!
Cite this paper
Peserico, E. (2013). Elastic paging. ACM SIGMETRICS Performance Evaluation Review, 41(1), 349–350. https://doi.org/10.1145/2494232.2479781
Peserico, Enoch. “Elastic paging.” ACM SIGMETRICS Performance Evaluation Review, vol. 41, no. 1, 2013, pp. 349–50, https://doi.org/10.1145/2494232.2479781.
Peserico, Enoch. 2013. “Elastic paging.” ACM SIGMETRICS Performance Evaluation Review 41 (1): 349–50. https://doi.org/10.1145/2494232.2479781.
Peserico, E. (2013) ‘Elastic paging’, ACM SIGMETRICS Performance Evaluation Review, 41(1), pp. 349–350. Available at: https://doi.org/10.1145/2494232.2479781.
@article{peserico2013elastic,
title = {{Elastic paging}},
author = {Peserico, Enoch},
journal = {ACM SIGMETRICS Performance Evaluation Review},
volume = {41},
number = {1},
pages = {349--350},
year = {2013},
doi = {10.1145/2494232.2479781}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.