Coordinating computation and I/O in massively parallel sequence search

Heshan Lin, Xiaosong Ma, Wuchun Feng, Nagiza F. Samatova

Research output: Contribution to journalArticle

33 Citations (Scopus)


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.

Original languageEnglish
Article number5473216
Pages (from-to)529-543
Number of pages15
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number4
Publication statusPublished - 14 Jan 2011
Externally publishedYes



  • bioinformatics
  • parallel genomic sequence search
  • parallel I/O
  • Scheduling

ASJC Scopus subject areas

  • Hardware and Architecture
  • Signal Processing
  • Computational Theory and Mathematics

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