Nature is multiscale
Multiscale modelling = combining models
of these processes, given that each has its
own scale.
Multiscale computing = doing this on a
computer, e.g. with simulation codes.
Borgdorff et al., JPDC, vol. 73,
no. 4, April 2013, pp. 465-483.
Defining multiscale computing: coupling scales
Each scale needs a model, but how can we combine them?
4 stages of
construction:
● Modelling
● Architecture
● Implementation
● Execution
Monolithic
+ Add models by extending a code.
+ Models can be integrated at a very
deep level in the code.
- The code becomes larger.
- The code becomes less portable.
- Adding new features becomes
increasingly costly.
+ Models are separate codes, and
can be swapped and updated easily.
+ Models can be run on different
computational resources.
+ Coupling models can be done
using an externally mandated ruleset.
- Coupling models may initially take a
little more effort.
Multi-model
Multiscale computing matters in a range of domains
Includes projects from
EU, NIH, NSF and
DOE.
Groen et al., IEEE CiSE, 2014.
Technologies for Code Coupling
MUSCLE 2: optimized for complex coupling
schemes, supports formalisms.Borgdorff et al., J. Comput. Sci. 5 (5), 719-731, 2014.
www.qoscosgrid.org/trac/muscle
MPWide: optimized for speed, flexibility and wide
area networks.http://www.github.com/djgroen/MPWide
Groen et al. J Open Research Software 1e9, 2013.
FabSim: optimized for using multiple remote
machines and non-concurrent coupling workflows.http://www.github.com/djgroen/FabSim
For a survey, see: Groen, Zasada & Coveney, IEEE CiSE 16 (2), 34-43, 2014.
Multiscale applications: Cerebrovascular bloodflow
HemeLB-PyNS multiscale simulations
using a desktop and a supercomputer.
3D-1D coupling.
Cyclic, concurrent.
<1% overhead for 512+4 cores.
HemeLB-Chaste multiscale
simulations using a desktop and a
supercomputer.
Fluid-Solid interactions.
Cyclic, not concurrent.
Groen et al., Interface Focus 3(2), 2013.
Bernabeu et al., Interface Focus 3(2), 2013.
Bernabeu et al., in prep.
Aim: Develop quantitative coarse-grained models of clay-polymer
nanocomposites.
Uses:
● Predict thermodynamically favourable states.
● Predict elasticity.
We require:
● Accurate potentials.
● Realistic structures.
● Task farming.
Multiscale applications: Clay-polymer nanocomposites
Suter, Groen and Coveney, Adv. Mat. 27 (6) 966-984, 2015.
Multiscale applications: Clay-polymer nanocomposites
● Montmorillonite clay +
Polyvinyl alcohol (PVA).
● Polymers have 30 monomers.
● Simulation box contains 8
tactoids, each with 4 platelets.
● Example: intercalation of PVA in
a clay tactoid.
Multiscale computing becomes increasingly
important to accurately model large physical
systems.
The software is there to conveniently combine
different models, and run them on large
supercomputers where needed.
Conclusions
This work was funded by the EU FP7 projects MAPPER and CRESTA, the EPSRC
funded 2020 Science project and by the Qatar National Research Foundation.
Thank you for your time
FabSim: optimized for using multiple remote machines
and running many applications at once.http://www.github.com/djgroen/FabSim
AHE:optimized for (web) applications with many users.http://www.realitygrid.org/AHE/
QosCosGrid: optimized for reserving resources and
automatically allocating jobs to them.http://www.qoscosgrid.org
Technologies for Automation
Technologies for Code Coupling
MUSCLE 2: optimized for complex coupling
schemes, supports formalisms.http://www.qoscosgrid.org/trac/muscle
MPWide: optimized for speed, flexibility and wide
area networks.http://www.github.com/djgroen/MPWide
Groen et al. JORS 1e9, 2013.
MPIMPI: widely installed, optimized for speed, but
supports only local sites.http://www.openmpi.org
For details, see: Groen, Zasada & Coveney, IEEE CiSE 16 (2), 34-43, 2014.
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