Literature DB >> 27497550

Accurate reaction-diffusion operator splitting on tetrahedral meshes for parallel stochastic molecular simulations.

I Hepburn1, W Chen1, E De Schutter1.   

Abstract

Spatial stochastic molecular simulations in biology are limited by the intense computation required to track molecules in space either in a discrete time or discrete space framework, which has led to the development of parallel methods that can take advantage of the power of modern supercomputers in recent years. We systematically test suggested components of stochastic reaction-diffusion operator splitting in the literature and discuss their effects on accuracy. We introduce an operator splitting implementation for irregular meshes that enhances accuracy with minimal performance cost. We test a range of models in small-scale MPI simulations from simple diffusion models to realistic biological models and find that multi-dimensional geometry partitioning is an important consideration for optimum performance. We demonstrate performance gains of 1-3 orders of magnitude in the parallel implementation, with peak performance strongly dependent on model specification.

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Substances:

Year:  2016        PMID: 27497550     DOI: 10.1063/1.4960034

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  5 in total

1.  Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers.

Authors:  Weiliang Chen; Erik De Schutter
Journal:  Front Neuroinform       Date:  2017-02-10       Impact factor: 4.081

2.  CoreNEURON : An Optimized Compute Engine for the NEURON Simulator.

Authors:  Pramod Kumbhar; Michael Hines; Jeremy Fouriaux; Aleksandr Ovcharenko; James King; Fabien Delalondre; Felix Schürmann
Journal:  Front Neuroinform       Date:  2019-09-19       Impact factor: 4.081

3.  3D mesh processing using GAMer 2 to enable reaction-diffusion simulations in realistic cellular geometries.

Authors:  Christopher T Lee; Justin G Laughlin; Nils Angliviel de La Beaumelle; Rommie E Amaro; J Andrew McCammon; Ravi Ramamoorthi; Michael Holst; Padmini Rangamani
Journal:  PLoS Comput Biol       Date:  2020-04-06       Impact factor: 4.475

4.  Applications and Challenges of Machine Learning to Enable Realistic Cellular Simulations.

Authors:  Ritvik Vasan; Meagan P Rowan; Christopher T Lee; Gregory R Johnson; Padmini Rangamani; Michael Holst
Journal:  Front Phys       Date:  2020-01-21

5.  Metaball skinning of synthetic astroglial morphologies into realistic mesh models for visual analytics and in silico simulations.

Authors:  Marwan Abdellah; Alessandro Foni; Eleftherios Zisis; Nadir Román Guerrero; Samuel Lapere; Jay S Coggan; Daniel Keller; Henry Markram; Felix Schürmann
Journal:  Bioinformatics       Date:  2021-07-12       Impact factor: 6.937

  5 in total

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