TY - GEN
T1 - Online Parallel Paging with Optimal Makespan
AU - Agrawal, Kunal
AU - Bender, Michael A.
AU - Das, Rathish
AU - Kuszmaul, William
AU - Peserico, Enoch
AU - Scquizzato, Michele
N1 - Publisher Copyright:
© 2022 Owner/Author.
PY - 2022/7/11
Y1 - 2022/7/11
N2 - The classical paging problem can be described as follows: given a cache that can hold up to k pages (or blocks) and a sequence of requests to pages, how should we manage the cache so as to maximize performance-or, in other words, complete the sequence as quickly as possible. Whereas this sequential paging problem has been well understood for decades, the parallel version, where the cache is shared among p processors each issuing its own sequence of page requests, has been much more resistant. In this problem we are given p request sequences R1, R2, ?, Rp, each of which accesses a disjoint set of pages, and we ask the question: how should the paging algorithm manage the cache to optimize the completion time of all sequences (i.e., the makespan). As for the classical sequential problem, the goal is to design an online paging algorithm that achieves an optimal competitive ratio, using O(1) resource augmentation. In a recent breakthrough, Agrawal et al. [SODA '21] showed that the optimal (deterministic) competitive ratio C for this problem is in the range O(log p) = C = O(log2 p). This paper closes that gap, showing how to achieve a competitive ratio C = O(log p). Our techniques reveal surprising combinatorial differences between the problem of optimizing makespan and that of optimizing the closely related metric of mean completion time; and yet our algorithm manages to be simultaneously asymptotically optimal for both tasks.
AB - The classical paging problem can be described as follows: given a cache that can hold up to k pages (or blocks) and a sequence of requests to pages, how should we manage the cache so as to maximize performance-or, in other words, complete the sequence as quickly as possible. Whereas this sequential paging problem has been well understood for decades, the parallel version, where the cache is shared among p processors each issuing its own sequence of page requests, has been much more resistant. In this problem we are given p request sequences R1, R2, ?, Rp, each of which accesses a disjoint set of pages, and we ask the question: how should the paging algorithm manage the cache to optimize the completion time of all sequences (i.e., the makespan). As for the classical sequential problem, the goal is to design an online paging algorithm that achieves an optimal competitive ratio, using O(1) resource augmentation. In a recent breakthrough, Agrawal et al. [SODA '21] showed that the optimal (deterministic) competitive ratio C for this problem is in the range O(log p) = C = O(log2 p). This paper closes that gap, showing how to achieve a competitive ratio C = O(log p). Our techniques reveal surprising combinatorial differences between the problem of optimizing makespan and that of optimizing the closely related metric of mean completion time; and yet our algorithm manages to be simultaneously asymptotically optimal for both tasks.
KW - multicores
KW - online algorithms
KW - paging
KW - parallel paging
UR - https://www.scopus.com/pages/publications/85134374685
U2 - 10.1145/3490148.3538577
DO - 10.1145/3490148.3538577
M3 - Conference contribution
AN - SCOPUS:85134374685
T3 - Annual ACM Symposium on Parallelism in Algorithms and Architectures
SP - 205
EP - 216
BT - SPAA 2022 - Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures
PB - Association for Computing Machinery
T2 - 34th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2022
Y2 - 11 July 2022 through 14 July 2022
ER -