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    ERA: Efficient serial and parallel suffix tree construction for very long strings

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    Type
    Article
    Authors
    Mansour, Essam
    Allam, Amin cc
    Skiadopoulos, Spiros G.
    Kalnis, Panos cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Computer Science Program
    Date
    2011-09-01
    Permanent link to this record
    http://hdl.handle.net/10754/561870
    
    Metadata
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    Abstract
    The suffix tree is a data structure for indexing strings. It is used in a variety of applications such as bioinformatics, time series analysis, clustering, text editing and data compression. However, when the string and the resulting suffix tree are too large to fit into the main memory, most existing construction algorithms become very inefficient. This paper presents a disk-based suffix tree construction method, called Elastic Range (ERa), which works efficiently with very long strings that are much larger than the available memory. ERa partitions the tree construction process horizontally and vertically and minimizes I/Os by dynamically adjusting the horizontal partitions independently for each vertical partition, based on the evolving shape of the tree and the available memory. Where appropriate, ERa also groups vertical partitions together to amortize the I/O cost. We developed a serial version; a parallel version for shared-memory and shared-disk multi-core systems; and a parallel version for shared-nothing architectures. ERa indexes the entire human genome in 19 minutes on an ordinary desktop computer. For comparison, the fastest existing method needs 15 minutes using 1024 CPUs on an IBM BlueGene supercomputer.
    Citation
    Mansour, E., Allam, A., Skiadopoulos, S., & Kalnis, P. (2011). ERA. Proceedings of the VLDB Endowment, 5(1), 49–60. doi:10.14778/2047485.2047490
    Publisher
    VLDB Endowment
    Journal
    Proceedings of the VLDB Endowment
    DOI
    10.14778/2047485.2047490
    arXiv
    1109.6884
    ae974a485f413a2113503eed53cd6c53
    10.14778/2047485.2047490
    Scopus Count
    Collections
    Articles; Computer Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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