Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

On the parallelization of linkmap from the LINKAGE/FASTLINK package.

A Rai1, N Lopez-Benitez, J D Hargis

  • 1Department of Computer Science, Texas Tech University, Lubbock, 79409, USA.

Computers and Biomedical Research, an International Journal
|October 6, 2000
PubMed
Summary

Parallel computing speeds up genetic linkage calculations. A dynamic task allocation strategy for the Linkmap program significantly improved performance, nearing maximum speedup potential.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Long-Range Transverse-Momentum Correlations and Radial Flow in Pb-Pb Collisions at the LHC.

Physical review letters·2026
Same author

Search for Quasiparticle Scattering in the Quark-Gluon Plasma with Jet Splittings in pp and Pb-Pb Collisions at sqrt[s_{NN}]=5.02  TeV.

Physical review letters·2025
Same author

First Measurement of A=4 Hypernuclei and Antihypernuclei at the LHC.

Physical review letters·2025
Same author

Probing Strangeness Hadronization with Event-by-Event Production of Multistrange Hadrons.

Physical review letters·2025
Same author

Measurements of Chemical Potentials in Pb-Pb Collisions at sqrt[s_{NN}]=5.02  TeV.

Physical review letters·2024
Same author

Observation of Medium-Induced Yield Enhancement and Acoplanarity Broadening of Low-p_{T} Jets from Measurements in pp and Central Pb-Pb Collisions at sqrt[s_{NN}]=5.02  TeV.

Physical review letters·2024

Area of Science:

  • Computational Biology
  • Genetics
  • High-Performance Computing

Background:

  • Genetic linkage calculations are computationally intensive, especially with large pedigrees.
  • Existing software like LINKAGE/FASTLINK faces performance limitations due to exponential time increases with pedigree size.

Purpose of the Study:

  • To develop a parallel implementation of the Linkmap program for efficient genetic likelihood calculations.
  • To evaluate static and dynamic task allocation strategies in a heterogeneous computing environment.

Main Methods:

  • Parallel implementation of the Linkmap program.
  • Utilized static and dynamic task allocation strategies for distributing computations across a heterogeneous platform.

Main Results:

Related Experiment Videos

  • The parallel implementation demonstrated significant performance improvements.
  • The dynamic strategy achieved performance gains close to the theoretical maximum speedup.

Conclusions:

  • Parallel processing is effective for accelerating complex genetic linkage analyses.
  • Dynamic task allocation offers superior performance for Linkmap in heterogeneous environments.