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

A parallel distributed data CPHF algorithm for analytic Hessians.

Yuri Alexeev1, Michael W Schmidt, Theresa L Windus

  • 1Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, PO Box 999, Mail Stop K1-96, Richland, Washington 99352-0999, USA.

Journal of Computational Chemistry
|March 8, 2007
PubMed
Summary
This summary is machine-generated.

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

Electron repulsion integral evaluation over f-type functions on GPUs via OpenMP offloading.

The Journal of chemical physics·2026
Same author

Hierarchical Truncations for Many-Body Expansion Potentials.

Journal of chemical theory and computation·2026
Same author

Speeding Up Hartree-Fock in JuliaChem with Density Fitting.

Journal of chemical theory and computation·2026
Same author

Multiscale Modeling of Transport-Mediated Catalytic Reactions in Linear Nanopores: PNB Conversion in MSN.

Journal of chemical theory and computation·2026
Same author

Theoretical study of Si/C alternately substituted annulenes with a belt structure.

Physical chemistry chemical physics : PCCP·2025
Same author

Artificial intelligence for quantum computing.

Nature communications·2025
Same journal

The Anionic States of Ubiquinone Characterized by Second-Order Approximate Coupled-Cluster Theory.

Journal of computational chemistry·2026
Same journal

Hydrogen Bond Energy Estimation in Large Molecular Clusters via the Method of Synergistic Cyclic Cooperativity: A Software Update H-BEE 2.0.

Journal of computational chemistry·2026
Same journal

The Intricate Mechanism of Nitric Oxide Synthase.

Journal of computational chemistry·2026
Same journal

A Molecular "Thermometer" for Measuring Effective Non-Local Exchange.

Journal of computational chemistry·2026
Same journal

Insights to Orientation Dependence of Molecular Conduction Modeled by High-Level Quantum Embedding.

Journal of computational chemistry·2026
Same journal

AutoSTOP-RT-TDDFT: Adaptive and Selected Real-Time Time-Dependent Density Functional Theory for Simulation of X-Ray Absorptions.

Journal of computational chemistry·2026
See all related articles

A new Hessian calculation algorithm improves computational efficiency for chemical reactions. This scalable, distributed method enhances performance for large biological systems by optimizing data handling and parallel processing.

Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Biophysics

Background:

  • Hessian calculations are crucial for characterizing potential energy surfaces in chemical systems.
  • Analytic Hessian evaluation is computationally intensive and memory-demanding.

Purpose of the Study:

  • To present a new scalable distributed data analytic Hessian algorithm.
  • To improve the efficiency and performance of Hessian calculations.

Main Methods:

  • Developed a distributed data parallel coupled perturbed Hartree-Fock (CPHF) algorithm.
  • Implemented matrix distribution across processors and an efficient static load balancing scheme.
  • Minimized network communication time and optimized analytic Hessian steps.

Main Results:

Related Experiment Videos

  • The new algorithm demonstrates good performance on large biological systems.
  • Achieved efficient workload distribution and reduced computational overhead.
  • Successfully scaled the Hessian calculation for complex chemical systems.

Conclusions:

  • The presented algorithm offers a computationally efficient approach to Hessian calculations.
  • Scalable distributed methods are vital for analyzing complex chemical and biological systems.
  • This work provides a valuable tool for computational chemistry research.