Paper Info
Title
Finding Common RNA Secondary Structures: A Case Study on the Dynamic Parallelization of a Data-driven Recurrence
Abstract
This paper presents the dynamic parallelization of a sequential algorithm for finding common RNA secondary structures that initially does not appear to be amenable to parallelization. A critical insight into the problem structure, which at first appears to be inherently top-down, leads to the development of a revised sequential algorithm that uses both bottom-up tabulation and top-down memoization. This novel combined approach proves well-suited for parallelization, overcoming the inherent difficulties in parallelizing the original top-down algorithm. The improved algorithm also eliminates two factors from the space complexity to fit into quadratic space, enabling the comparison of lengthy and complex RNA structures. Experimental results demonstrate that the parallel algorithm scales well, achieving speedup of up to 32X using 64 processors for contrived worst-case data containing structures having up to 1600 nested arcs. This algorithm illustrates the significant benefits that can be achieved by designing an underlying sequential dynamic programming algorithm with parallelizability in mind, instead of directly parallelizing an existing sequential algorithm. Our results also show the usefulness of combining both bottom-up and top-down perspectives when designing a parallel dynamic programming algorithm.
Year
DOI
Venue
2012
10.1109/IPDPSW.2012.89
Parallel and Distributed Processing Symposium Workshops & PhD Forum
Keywords
Field
DocType
parallel dynamic programming algorithm,top-down perspective,top-down memoization,existing sequential algorithm,dynamic parallelization,underlying sequential dynamic programming,parallel algorithm scale,secondary structures,case study,finding common rna,original top-down algorithm,improved algorithm,revised sequential algorithm,sequential algorithm,data-driven recurrence,rna,algorithm design and analysis,dynamic programming,parallel algorithms,computational complexity,space complexity,parallel algorithm
Dynamic programming,Algorithm design,Simplex algorithm,Computer science,Parallel algorithm,Parallel computing,Algorithm,Sequential algorithm,Memoization,Criss-cross algorithm,Computational complexity theory,Distributed computing
Conference
ISSN
ISBN
Citations 
2164-7062
978-1-4673-0974-5
0
PageRank 
References 
Authors
0.34
5
3
Name
Order
Citations
PageRank
Steven T. Stewart100.34
Eric Aubanel2579.75
Patricia A. Evans316114.12