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 Concept Videos

Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by

You might also read

Related Articles

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

Sort by
Same author

Transport in semiconductor nanowire superlattices described by coupled quantum mechanical and kinetic models.

Journal of physics. Condensed matter : an Institute of Physics journal·2013
Same author

Electromechanical interactions in a carbon nanotube based thin film field emitting diode.

Nanotechnology·2011
Same author

Degradation and failure of field emitting carbon nanotube arrays.

Journal of nanoscience and nanotechnology·2011
Same author

Zero-range model of traffic flow.

Physical review. E, Statistical, nonlinear, and soft matter physics·2005
Same author

On computational control of flow in airblast atomisers for pulmonary drug delivery.

International journal of pharmaceutics·2002

Related Experiment Videos

Parallelization of the Wolff single-cluster algorithm.

J Kaupuzs1, J Rimsāns, R V N Melnik

  • 1Institute of Mathematics and Computer Science, University of Latvia, 29 Rainja Boulevard, LV-1459 Riga, Latvia. kaupuzs@latnet.lv

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|April 7, 2010
PubMed
Summary
This summary is machine-generated.

A new parallel implementation of the Wolff algorithm using OpenMP speeds up simulations of the 3D Ising model. This enhanced method enables accurate critical temperature determination and simulation of larger lattices.

Related Experiment Videos

Area of Science:

  • Computational physics
  • Statistical mechanics
  • Parallel computing

Background:

  • The Wolff single-cluster algorithm is crucial for simulating lattice spin models.
  • Efficient parallelization is needed to handle large-scale simulations and complex models.
  • Accurate determination of critical temperatures is essential for understanding phase transitions.

Purpose of the Study:

  • To develop and test a parallel OpenMP implementation of the Wolff single-cluster algorithm.
  • To evaluate the performance and scalability of the parallel algorithm for the 3D Ising model.
  • To demonstrate the applicability of the method for accurate critical temperature determination and large lattice simulations.

Main Methods:

  • Implementation of the Wolff single-cluster algorithm using OpenMP for parallel processing.
  • Development of a sophisticated shuffling scheme for high-quality pseudorandom number generation.
  • Application of an iterative method for precise critical temperature calculation.
  • Performance evaluation through speedup measurements on multi-core processors.

Main Results:

  • Achieved speedups of approximately 1.79x on two processors and 2.67x on four processors for a 3D Ising model lattice of size L=1024.
  • Estimated potential speedups of up to 3x on four processors for O(n) models with n>=2.
  • Demonstrated the ability to simulate larger lattices due to increased available shared memory.

Conclusions:

  • The developed OpenMP implementation offers significant performance improvements over serial codes for the 3D Ising model.
  • The methodology is generalizable to other lattice spin models, enhancing simulation capabilities.
  • The parallel algorithm facilitates more accurate and efficient studies of critical phenomena in statistical physics.