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Parallel algorithms for graph cycle extraction using the cyclical conjunction operator.

G Cerruela García1, I Luque Ruiz, M A Gómez-Nieto

  • 1Department of Computing and Numerical Analysis, University of Córdoba, Campus Universitario de Rabanales, Edificio C2, Planta-3, E-14071 Córdoba, Spain.

Journal of Chemical Information and Computer Sciences
|November 26, 2002
PubMed
Summary
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This study explores parallel processing to reduce computational costs for extracting cycles from complex graphs. A dynamically distributed fine-grain algorithm is proposed for efficient cycle extraction.

Area of Science:

  • Computer Science
  • Graph Theory
  • Parallel Computing

Background:

  • Extracting all cycles from complex graphs is computationally expensive.
  • Existing algorithms face challenges in efficiency and scalability.

Purpose of the Study:

  • To investigate the viability of parallel processing for graph cycle extraction.
  • To identify key factors influencing the parallelization of cycle extraction algorithms.

Main Methods:

  • The study utilized a cyclical conjunction operator for iterative cycle extraction.
  • Parallelization factors such as granularity, synchronization, and load distribution were analyzed.
  • Algorithm implementation was performed using SGI MP and OpenMP libraries.

Main Results:

Related Experiment Videos

  • Tests were conducted on two granularities and four load distributions.
  • The research identified optimal parameters for parallel algorithm design.
  • A dynamically distributed fine-grain algorithm demonstrated effectiveness.

Conclusions:

  • Parallel processing significantly reduces the computational cost of graph cycle extraction.
  • A proposed dynamically distributed fine-grain algorithm achieves efficient cycle finding within acceptable timeframes.