@inproceedings{02ac185d171543da911ef50c0f3d39a0,
title = "Green Paging and Parallel Paging",
abstract = "We study two fundamental variants of the classic paging problem: green paging and parallel paging. In green paging one can choose the exact memory capacity in use at any given instant, between a maximum of k and a minimum of k/p pages; the goal is to minimize the integral of this number over the time required to complete a computation (note that running at lower capacity is not necessarily better, since might disproportionately increase the total completion time). In parallel paging, a memory of k pages is shared between p processors, each carrying out a separate computation; the goal is to minimize the respective completion times. We show how these two different problems are strictly related: any efficient solution to green paging can be converted into an efficient solution to parallel paging, and any lower bound for green paging can be converted into a lower bound for parallel paging - -in both cases in a black-box fashion. Exploiting this relation, we provide tight upper and lower bounds of (log p) on the competitive ratio with O(1) resource augmentation for both problems.",
keywords = "green computing, online algorithms, paging, shared cache",
author = "Kunal Agrawal and Bender, \{Michael A.\} and Rathish Das and William Kuszmaul and Enoch Peserico and Michele Scquizzato",
note = "Publisher Copyright: {\textcopyright} 2020 Owner/Author.; 32nd ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2020 ; Conference date: 15-07-2020 Through 17-07-2020",
year = "2020",
month = jul,
day = "6",
doi = "10.1145/3350755.3400231",
language = "English",
series = "Annual ACM Symposium on Parallelism in Algorithms and Architectures",
publisher = "Association for Computing Machinery",
pages = "493--495",
booktitle = "SPAA 2020 - Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures",
}