DOI

The longest increasing subsequence (LIS) problem is a classical problem in theoretical computer science and mathematics. Most existing parallel algorithms for this problem have very restrictive slackness conditions which prevent scalability to large numbers of processors. Other algorithms are scalable, but not work-optimal w.r.t. the fastest sequential algorithm for the LIS problem, which runs in time O(n log n) for n numbers in the comparison-based model. In this paper, we propose a new parallel algorithm for the LIS problem. Our algorithm solves the more general problem of semi-local comparison of permutation strings of length n in time O(n 1.5 / p) on p processors, has scalable communication cost of O(n/ √p) and is synchronisation- efficient. Furthermore, we achieve scalable memory cost, requiring O(n/ √p) of storage on each processor. When applied to LIS computation, this algorithm is superior to previous approaches since computation, communication, and memory costs are all scalable. © 2010 Springer-Verlag Berlin Heidelberg.
Язык оригиналаанглийский
Название основной публикацииParallel Processing and Applied Mathematics (PPAM 2009)
Страницы176-185
Число страниц10
ТомPART 1
DOI
СостояниеОпубликовано - 5 авг 2010

Серия публикаций

НазваниеLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ИздательSpringer Nature
Том6067
ISSN (печатное издание)0302-9743

ID: 127758167