Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Parallel Processing

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...

Accelerating Fluids

Accelerating Fluids

When a fluid is in constant acceleration, the pressure and buoyant force equations are modified. Suppose a beaker is placed in an elevator accelerating upward with a constant acceleration, a. In the beaker, assume there is a thin cylinder of height h with an infinitesimal cross-sectional area, ΔS.
The motion of the liquid within this infinitesimal cylinder is considered to obtain the pressure difference. Three vertical forces act on this liquid:

Newtonian Fluid: Problem Solving

Newtonian Fluid: Problem Solving

Newtonian fluids exhibit a constant viscosity, meaning their shear stress and shear strain rate are directly proportional. This property ensures a predictable and stable response to applied forces, maintaining a linear relationship between force and flow. Examples include water, air, and light oils, consistently demonstrating this proportional behavior regardless of external conditions.
A velocity gradient forms within the fluid when a Newtonian fluid is placed between two parallel plates, with...

Molecular Comparison of Gases, Liquids, and Solids

Molecular Comparison of Gases, Liquids, and Solids

Particles in a solid are tightly packed together (fixed shape) and often arranged in a regular pattern; in a liquid, they are close together with no regular arrangement (no fixed shape); in a gas, they are far apart with no regular arrangement (no fixed shape). Particles in a solid vibrate about fixed positions (cannot flow) and do not generally move in relation to one another; in a liquid, they move past each other (can flow) but remain in essentially constant contact; in a gas, they move...

Distribution of Molecular Speeds

Distribution of Molecular Speeds

The motion of molecules in a gas is random in magnitude and direction for individual molecules, but a gas of many molecules has a predictable distribution of molecular speeds. This predictable distribution of molecular speeds is known as the Maxwell-Boltzmann distribution. The distribution of molecular speeds in liquids is comparable to that of gases but not identical and can help to understand the phenomenon of the boiling and vapor pressure of a liquid. Consider that a molecule requires a...

Chemical Shift: Internal References and Solvent Effects

Chemical Shift: Internal References and Solvent Effects

In an NMR sample, precise measurement of the absolute absorption frequencies of nuclei is difficult. A standard internal reference compound is added, and the frequency difference between the reference signal and sample signals is measured.
The internal reference compound generally used in NMR spectroscopy is tetramethylsilane (TMS). TMS is preferred because it is chemically inert, soluble in NMR solvents, and easily removable. Also, the highly shielded methyl protons in TMS yield an intense...

You might also read

Related Articles

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

Sort by

Same author

Membrane permeation by NAF144-67 is determined by C-terminal electrostatics and N-terminal insertion.

The Journal of chemical physics·2026

Same author

Targeting primary and metastatic ovarian cancer with a peptide derived from the human NAF-1/CISD2 protein.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie·2026

Same author

The scientific legacy of Martin Karplus from the perspective of his collaborators.

Biophysical journal·2026

Same author

Determining Pathways of Minimum Work: Simple Examples.

Molecular physics·2025

Same author

Membrane-Embedded Anti-Cancer Peptide Causes a Minimal Structural Perturbation That Is Sufficient to Enhance Phospholipid Flip-Flop and Charge Permeation Rates.

Life (Basel, Switzerland)·2025

Same author

How Does an Anti-Cancer Peptide Passively Permeate the Plasma Membrane of a Cancer Cell and Not a Normal Cell?

The journal of physical chemistry. B·2025

Search research articles

Related Experiment Video

Updated: May 15, 2026

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Revisiting Molecular Dynamics on a CPU/GPU system: Water Kernel and SHAKE Parallelization.

A Peter Ruymgaart¹, Ron Elber

¹Department of Chemistry and Biochemistry, Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX 78712.

Journal of Chemical Theory and Computation

|December 25, 2012

Summary

We developed GPU and Open-MP parallel implementations for Molecular Dynamics (MD) simulations, significantly accelerating water-specific force calculations and bond constraints. Our optimized code achieves performance comparable to GROMACS, with excellent energy conservation.

More Related Videos

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

Related Experiment Videos

Last Updated: May 15, 2026

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

Area of Science:

Computational Chemistry
Molecular Dynamics Simulations
High-Performance Computing

Background:

Molecular Dynamics (MD) simulations are crucial for understanding molecular behavior.
Efficient computation of forces and bond constraints is essential for accurate and fast MD simulations.
Leveraging Graphics Processing Units (GPUs) and parallel computing (Open-MP) can significantly enhance simulation speed.

Purpose of the Study:

To develop and present parallel implementations of water-specific force calculations and bond constraints for MD simulations.
To optimize these calculations for typical laboratory computing environments (CPU + GPU).
To achieve performance comparable to highly optimized existing codes like GROMACS.

Main Methods:

Graphics Processing Unit (GPU) and Open-MP parallel implementations for force calculations and bond constraints.
Utilization of water-specific lists for efficient non-bonded interactions.
Implementation of constrained dynamics (CG SHAKE) entirely on the GPU, partially in double precision.
Parallel execution of SHAKE on multiple Open-MP cores or solely on the GPU.

Main Results:

Achieved a speed-up factor of over 40 on the GPU for systems >20,000 atoms using water-specific lists, a four-fold increase from previous implementations.
Demonstrated excellent energy conservation alongside significant speed improvements.
Enabled an increase in the simulation time step to 2.0 fs with maintained energy conservation.
Identified the reciprocal part of Particle Mesh Ewald (PME) as the new computational bottleneck.

Conclusions:

The developed GPU and Open-MP implementations offer substantial speedups for MD simulations, particularly for systems involving water.
The CG SHAKE algorithm provides an efficient and accurate method for enforcing bond constraints on the GPU.
These optimizations push the boundaries of computational efficiency in MD, paving the way for larger and more complex simulations.