About scales and physics in the cosmos€¦ · Breanndan O Nuaillan. AMUSE philosophy Build on...
Transcript of About scales and physics in the cosmos€¦ · Breanndan O Nuaillan. AMUSE philosophy Build on...
The Jungle UniverseAbout scales and physics in the cosmos
Simon Portegies ZwartSterrewacht Leiden
Observation of
the early universe
(WMAP)
Abel1689
Stephen's quintuplet
The universe is multiphysics
The universe is multiscale
Jungle scales
Size scale covers anythin from:● 13.8 billion light years to kmsize
● that covers 24 orders of magnitude
● 13.8 billion years to seconds● that covers 18 orders of magnitude
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=F−∇ pρ
ν ∇ 2u
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),,(),,(),,(
),,(4
1
4
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4
i
igraviinuc
i
YTPPr
GmT
m
T
YTPYTPYTPm
L
YTPrm
r
r
Gm
m
P
∇−=∂∂
++=∂∂
=∂∂
−=∂∂
π
εεε
ρπ
π
ν
F = G m1 m2
r 2
)(νν
ν k
jS =
ννν
τSI
d
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s
+−=
Sir Arthur Eddington
Sir Isaac Newton
CloudeLouise NavierGeorge Gabriel Stokes
Subrahanyan ChandrasekharJames Clark Maxwell
Abacus (500BC,
compute speed ~10FLOP)
Sumerian cuneform clay tabletdated around 1,200BCexplaining the periodic behavior the planet Venus around 1,600BC(compute speed ~ 1 FLOP)
Prehistoric computational astrophysics
”...'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question."
Jun & GRAPE4
von Neuman & IAS
~30 000 000 times faster
500BC
2003
1960
Stellar evolution
Gravity
gasdynamicshydrodynamics
Radiative transportMaxwell equations
DAS4
LGM
Computational challenges
● High performance (desktop) computing● Distributed (wide area) computing
● Problem solving environments (software)● Data acquisition● Data mining● Visualization● Virtual collaboration
19082000
10mFlops
Manchester mark1 (1948, 550 FLOPs) Software by Tom Kilburn
Software operated computers
The next generation problem solving environments
● Specialization (higher resolution)● Optimization (highperformance)● Diversification (wide range of applications)● Hybridization (multi physics)● Preservation (containment of existing codes)
The Astrophysical Multipurpose
Software Environment
AMUSE
http://amusecode.org
Scientific research and development team
● Marco Spaans ● Gijs Nelemans● Vincent Icke● Onno Pols● Lex Kaper
● Steve McMillan● Paul Groot● Eline Tolstoy● Evert Glebbeek● Rien vd Weijgeart● Rob Knop● John Fregeau● Breanndan O Nuaillan
AMUSE philosophy● Build on community codes● Standarized interfaces● Automate as much as possible● Builds on lessons learned from previous generations● Core Team:
– Inti Pelupessy (postdoc)
– Arjen van Elteren (software engineer)
– Marcel Marosvolgi, Nathan de Vries (programmers)
– David Jansen (user support)
AMUSE design
Gravity
HydrodynamicsStellar Evolution
Radiative Transfer
Unit handling
Data conversion
Initial conditions
INPUT OUTPUT
Compare models
AMUSE
Combining existing codes
With an extensive support framework
To provide a generic framework
For doing astrophysical experiments
www.amusecode.org
Next Level
Legacy Interfaces
AMUSE http://amusecode.org
C/C++ code Fortran Code
MPI
Message Channel
RTGD HD SE
Particles
Python Script
Units
● Layers having different roles
● Written in C/C++, Java Fortran and Python
Pelupessy etal in prep
User script Community codeMessage passing script Message passing source
evolve()
Send request
Send request
evolve()Confirm request
Evolve() done
Send answer
Send request
Confirm request
Confirm requestConfirm request
Send answer
Process 1 Process 2
Two examples
● Formation of J1903+0327 (ApJ in press: ArXive:11032275)– Gravitational dynamics + Stellar evolution
● Evolution of young star cluster (to be submitted)– Gravitational dynamics + Stellar evolution + Hydro
dynamics
NGC3603 cluster
By HST
Simulating Embedded star clusters
Numerical ingredients● Gravitational dynamics
– Direct Nbody integration (PhiGRAPE)
– GPU or GRAPE equipped pc
● Stellar evolution– Henyey stellar evolution (MESA)
– Beowulf computer cluster
● Gas dynamics– Smoothed particles hydrodynamics (Fi)
– Super computer
Evolution of a gas rich star clusterSFE=0.05 f
fb=0.1
SFE=0.50 ffb=0.01
AMUSE Today
● Automated referencing● Unit conversion● Online documentation● Suite of examples● Intricate module coupling via Hamiltonian
splitting
Wishlist for AMUSE● Runtime crashrecovery● Selfconsistent code restart● Initial conditions repository● Extensive data mining and analysis toolbox● Highperformance AMUSE● AMUSE on the grid (PDRA Niels Drost VU)● Asynchronous communication support● Load balancing on heterogeneous architectures● Data tunneling protocol