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A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
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Efficient Out of Core Sorting Algorithms for the Parallel Disks Model.

Vamsi Kundeti1, Sanguthevar Rajasekaran

  • 1Department of Computer Science and Engineering, University of Connecticut Storrs, CT 06269, USA.

Journal of Parallel and Distributed Computing
|October 29, 2011
PubMed
Summary
This summary is machine-generated.

We introduce dirty sequence accumulation to improve sorting efficiency on the Parallel Disks Model (PDM). This method significantly reduces parallel I/Os, enhancing read parallelism and sorting speed.

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Area of Science:

  • Computer Science
  • Algorithms
  • Parallel Computing

Background:

  • Existing sorting algorithms on the Parallel Disks Model (PDM) often have high constants due to limited read parallelism.
  • Irregular run consumption during merges hinders read parallelism and increases sorting time on PDM.

Purpose of the Study:

  • To develop efficient sorting algorithms for the Parallel Disks Model (PDM).
  • To address the limitations of existing merge-based algorithms concerning read parallelism.

Main Methods:

  • Introduction of a novel technique: dirty sequence accumulation.
  • Analytical demonstration of reduced parallel I/O requirements.
  • Experimental verification using standard R-Way merge.

Main Results:

  • Dirty sequence accumulation improves read parallelism on PDM.
  • The proposed method analytically reduces parallel I/Os needed for sorting.
  • Experimental results show a significant reduction in parallel I/Os compared to standard methods.

Conclusions:

  • Dirty sequence accumulation is an effective strategy for enhancing sorting performance on PDM.
  • The novel approach brings sorting efficiency closer to theoretical lower bounds.
  • This work offers practical improvements for sorting in parallel disk environments.