Abstract
Data explosion is an increasingly prevalent problem in every field of science. Traditional out-of-core models that assume a single disk have been found inadequate to handle voluminous data. As a result, models that employ multiple disks have been proposed in the literature. For example, the Parallel Disk Systems (PDS) model assumes D disks and a single computer. It is also assumed that a block of data from each of the D disks can be fetched into the main memory in one parallel I/O operation.
In this article, we survey sorting and selection algorithms that have been devised for out-of-core models assuming multiple disks. We also consider practical implementations of parallel disk models.
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Rajasekaran, S. (2002). Sorting and Selection on Parallel Disk Models. In: Abello, J., Pardalos, P.M., Resende, M.G.C. (eds) Handbook of Massive Data Sets. Massive Computing, vol 4. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0005-6_24
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DOI: https://doi.org/10.1007/978-1-4615-0005-6_24
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