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Coordinating Computation and I/O in Massively Parallel Sequence Search

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4 Author(s)
Heshan Lin ; Dept. of Comput. Sci., Virginia Tech, Blacksburg, VA, USA ; Xiaosong Ma ; Wuchun Feng ; Samatova, N.F.

With the explosive growth of genomic information, the searching of sequence databases has emerged as one of the most computation and data-intensive scientific applications. Our previous studies suggested that parallel genomic sequence-search possesses highly irregular computation and I/O patterns. Effectively addressing these runtime irregularities is thus the key to designing scalable sequence-search tools on massively parallel computers. While the computation scheduling for irregular scientific applications and the optimization of noncontiguous file accesses have been well-studied independently, little attention has been paid to the interplay between the two. In this paper, we systematically investigate the computation and I/O scheduling for data-intensive, irregular scientific applications within the context of genomic sequence search. Our study reveals that the lack of coordination between computation scheduling and I/O optimization could result in severe performance issues. We then propose an integrated scheduling approach that effectively improves sequence-search throughput by gracefully coordinating the dynamic load balancing of computation and high-performance noncontiguous I/O.

Published in:

Parallel and Distributed Systems, IEEE Transactions on  (Volume:22 ,  Issue: 4 )

Date of Publication:

April 2011

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