schliessen

Filtern

 

Bibliotheken

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

Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutio... Full description

Journal Title: Frontiers in Neuroinformatics Feb 10, 2017
Main Author: Chen, Weiliang
Other Authors: De Schutter, Erik
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: ISSN: 1662-5196 ; DOI: 10.3389/fninf.2017.00013
Zum Text:
SendSend as email Add to Book BagAdd to Book Bag
Staff View
recordid: gale_ofa480655965
title: Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers.(Report)
format: Article
creator:
  • Chen, Weiliang
  • De Schutter, Erik
subjects:
  • Stochastic Analysis – Usage
  • Neurosciences – Research
  • Purkinje Cells – Research
ispartof: Frontiers in Neuroinformatics, Feb 10, 2017
description: Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutions that benefit from the boost in performance of modern supercomputers. In this paper, we describe an MPI-based, parallel operator-splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its application to real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecule density and mesh quality. In the best scenario, a parallel simulation with 2,000 processes runs more than 3,600 times faster than its serial SSA counterpart, and achieves more than 20-fold speedup relative to parallel simulation with 100 processes. In a more realistic scenario with dynamic calcium influx and data recording, the parallel simulation with 1,000 processes and no load balancing is still 500 times faster than the conventional serial SSA simulation.
language: eng
source:
identifier: ISSN: 1662-5196 ; DOI: 10.3389/fninf.2017.00013
fulltext: fulltext
issn:
  • 1662-5196
  • 16625196
url: Link


@attributes
ID635757576
RANK0.07
NO1
SEARCH_ENGINEprimo_central_multiple_fe
SEARCH_ENGINE_TYPEPrimo Central Search Engine
LOCALfalse
PrimoNMBib
record
control
sourcerecordid480655965
sourceidgale_ofa
recordidTN_gale_ofa480655965
sourceformatXML
sourcesystemPC
pqid1872583157
galeid480655965
display
typearticle
titleParallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers.(Report)
creatorChen, Weiliang ; De Schutter, Erik
ispartofFrontiers in Neuroinformatics, Feb 10, 2017
identifierISSN: 1662-5196 ; DOI: 10.3389/fninf.2017.00013
subjectStochastic Analysis – Usage ; Neurosciences – Research ; Purkinje Cells – Research
languageeng
source
descriptionStochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutions that benefit from the boost in performance of modern supercomputers. In this paper, we describe an MPI-based, parallel operator-splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its application to real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecule density and mesh quality. In the best scenario, a parallel simulation with 2,000 processes runs more than 3,600 times faster than its serial SSA counterpart, and achieves more than 20-fold speedup relative to parallel simulation with 100 processes. In a more realistic scenario with dynamic calcium influx and data recording, the parallel simulation with 1,000 processes and no load balancing is still 500 times faster than the conventional serial SSA simulation.
version6
lds50peer_reviewed
links
openurl$$Topenurl_article
openurlfulltext$$Topenurlfull_article
search
scope
0gale_onefilea
1OneFile
creatorcontrib
0Chen, Weiliang
1De Schutter, Erik
titleParallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers.(Report)
subject
0Stochastic analysis–Usage
1Neurosciences–Research
2Purkinje cells–Research
general
010.3389/fninf.2017.00013
1English
2Frontiers Research Foundation
3Cengage Learning, Inc.
sourceidgale_ofa
recordidgale_ofa480655965
issn
01662-5196
116625196
rsrctypearticle
creationdate2017
startdate20170210
enddate20170210
recordtypearticle
addtitleFrontiers in Neuroinformatics
searchscopeOneFile
lsr30VSR-Enriched:[pages, description, galeid, vol, pqid]
sort
titleParallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers.(Report)
authorChen, Weiliang ; De Schutter, Erik
creationdate20170210
lso0120170210
facets
frbrgroupid-170655302695259942
frbrtype5
newrecords20170221
languageeng
creationdate2017
topic
0Stochastic Analysis–Usage
1Neurosciences–Research
2Purkinje Cells–Research
collectionOneFile (GALE)
prefilterarticles
rsrctypearticles
creatorcontrib
0Chen, Weiliang
1De Schutter, Erik
jtitleFrontiers in Neuroinformatics
toplevelpeer_reviewed
delivery
delcategoryRemote Search Resource
fulltextfulltext
addata
aulast
0Chen
1De Schutter
aufirst
0Weiliang
1Erik
au
0Chen, Weiliang
1De Schutter, Erik
atitleParallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers.
jtitleFrontiers in Neuroinformatics
risdate20170210
issn1662-5196
formatjournal
genrearticle
ristypeJOUR
pubFrontiers Research Foundation
doi10.3389/fninf.2017.00013
lad01gale_ofa
pages13
volume11
date2017-02-10