Fusion Status Report

INFSO-RI-508833

Enabling Grids for E-sciencE

www.eu-egee.org

Fusion Status Report

Francisco Castejón ([email protected])

CIEMAT. Madrid, Spain.

Grid Users Forum, CERN, March 2006 2


INFSO-RI-508833

Outline

• Strategy.• Fusion Deployment and VO setup.

– The problem of the name

• Present Applications: Computing in Plasma Physics.• Future Applications in the grid. • Data storage and handling.• Conclusions.



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Strategy• Computing:

– Identify common Codes suitable for GRID. (Ongoing)

– Adapt codes to the GRID. (Ongoing)

– Set up VO (Ongoing)

– Production phase.

Data handling: Define strategies for data storage. & database organization.Protocol for data Access.



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ITER: Making decisions in real Time !!

Data Acquisition and Storage (Grid, Supercomputers)

Data Analysis and Reduction: Artificial Intelligence, Neural Network, Pattern Recognition

Simulations: Large codes in different platforms (Grid, Supercomputers)

Decision for present/next shot

One half an hour shot every one hour and a half: Decisions in real time.



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ITER Partners

Distributed Participation. Distributed Participation. Data access. Remote Control Data access. Remote Control

Rooms?Rooms?



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International Tokamak (ITPA) and Stellarator (SIA) collaborations.

USA:USA:

Alcator C-Mod (MIT)Alcator C-Mod (MIT)

DIII-D (San Diego)DIII-D (San Diego)

NSTX (Princeton)NSTX (Princeton)

NCSX (Princeton)NCSX (Princeton)

HSX (Wisconsin)HSX (Wisconsin)

QPS (Oak-Ridge)QPS (Oak-Ridge)

USA Fusion GridUSA Fusion Grid

Russia:Russia:

T-10 (Kurchatov)T-10 (Kurchatov)

Globus (Ioffe)Globus (Ioffe)

T-11M (TRINITI)T-11M (TRINITI)

L-2 (Gen. Inst. Phys.)L-2 (Gen. Inst. Phys.)

EGEE ProjectEGEE Project

EU:EU:

JET (EFDA)JET (EFDA)

ASDEX (Ger.)ASDEX (Ger.)

TORE SUPRA (Fran.)TORE SUPRA (Fran.)

MAST (UK)MAST (UK)

TEXTOR (Ger.)TEXTOR (Ger.)

TCV (Switz.)TCV (Switz.)

FTU (Italy)FTU (Italy)

W7-X (Ger.)W7-X (Ger.)

TJ-II (Spain)TJ-II (Spain)


Japan:Japan:

JT-60 (Naka)JT-60 (Naka)

LHD (Toki)LHD (Toki)

CHS (Nagoya)CHS (Nagoya)

H-J (Kyoto)H-J (Kyoto)

GRID Project ?GRID Project ?

China, Brazil, Korea, India:China, Brazil, Korea, India:

KSTAR (Korea) KSTAR (Korea)

TCBRA (Bra.) TCBRA (Bra.)

H-7 (China)H-7 (China)

U2A (China)U2A (China)

SST1 (India) SST1 (India)




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PARTNERS and Resources for VO

• SW Federation: CIEMAT, BIFI, UCM, INTA (Spain) • Kurchatov (Russia). • Culham Laboratory- UKAEA (UK) • KISTI (South Korea). • ENEA (Italy).• CEA-Cadarache (France).• …

Experience in using and developing Fusion Applications.Experience in porting applications and developing Grid Technologies.

Connection with EELA (Some fusion partners: Brazil,Mexico,Argentina)

Needed: Join IPP-Max Planck (Germany) and other EFDA Associations. Also needed: contact with USA, China, Japan,…



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VO Deployment

• Present: CIEMAT: 27 KSpecInts; BIFI: 8 KSpecInts; INTA: 6 KSpecInts

Resource Broker in BIFI (Spain) VO Manager: I. Campos (BIFI. Spain)

http://grid.bifi.unizar.es/egee/fusion-vo/

http://www-fusion.ciemat.es/collaboration/egee/

• Within less than 6 months:

JET: 38 KSpecInts; BIFI: 32 KSpecInts; CEA-Cadarache ?

KISTI?, INTA?, ENEA?

• Within less than 6 months:

JET: 38 KSpecInts; BIFI: 32 KSpecInts; CEA-Cadarache ?

KISTI?, INTA?, ENEA?

• Beginning of 2007:

JET: 32 additional cores; BIFI: 32 additional cores; CIEMAT ?;

CEA-Cadarache ?(second phase already committed).

• Beginning of 2007:

JET: 32 additional cores; BIFI: 32 additional cores; CIEMAT ?;

CEA-Cadarache ?(second phase already committed).



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VO Deployment: The problem of the name.

• Russian Grid has adopted the same name of Fusion, as we have done.

• The works that are sent by our resource broker go to such Grid.

• Our VO deployment is hindered.• They should change the name in short term (~1 week). A

suitable name: Fusion-RIDG• Otherwise: We have to change the name. Consequences

on Russian certificates.



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COMPUTING in the GRID: Present Applications

– Applications with distributed calculations: Monte Carlo, Separate estimates, …

– Multiple Ray Tracing: e. g. TRUBA. – Stellarator Optimization: VMEC– Transport and Kinetic Theory: Monte Carlo Codes.



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Multiple Ray Tracing: TRUBA

Single Ray (1 PE): Single Ray (1 PE): Hamiltonian Hamiltonian Ray Tracing Equations.Ray Tracing Equations.

Beam Beam Simulation: Simulation:

Bunch of rays Bunch of rays with beam waist with beam waist far from the far from the critical layer critical layer (100-200 rays)(100-200 rays)

Bunch of rays Bunch of rays with beam waist with beam waist close to the close to the critical layer critical layer (100-200 rays) x (100-200 rays) x (100-200 wave (100-200 wave numbers) numbers) ~10~1055

GRID GRID PROBLEMPROBLEM



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TRUBA: Multiple Ray Tracing

TRUBA for EBW: TRUBA for EBW: -Real geometry in TJ-II:Coming from a supercomputer Real geometry in TJ-II:Coming from a supercomputer (VMEC).(VMEC).

- A single Non-relativistic ray (about 18’).A single Non-relativistic ray (about 18’).- A single relativistic ray (about 40’).A single relativistic ray (about 40’).

- Some problems with Geometry libraries.Some problems with Geometry libraries.

- Ported to the grid using Grid Way (for the moment). Ported to the grid using Grid Way (for the moment). -See:See:J. L. VJ. L. Vázquez-Poleti. “Massive Ray Tracing ázquez-Poleti. “Massive Ray Tracing in Fusion Plasmas on EGEE”. User Forum, in Fusion Plasmas on EGEE”. User Forum, 2006.2006.



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Optimised Stellarators QPS and NCSXSupercomputer Optimization

NCSXQPS



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Stellarator optimization in the Grid

-A lot of different Magnetic Configurations operating nowadays.

OPTIMIZATION NECESITY BASED ON KNOWLEDGE OF STELLARATOR PHYSICS.

Every variant computed on a separate processor (~10’) VMEC (Variational Momentum Equilibrium Code)

120 Fourier parameters are varied.

-A lot of different Magnetic Configurations operating nowadays.

OPTIMIZATION NECESITY BASED ON KNOWLEDGE OF STELLARATOR PHYSICS.

Every variant computed on a separate processor (~10’) VMEC (Variational Momentum Equilibrium Code)

120 Fourier parameters are varied.

rB(ψ,θ,ϕ ) =

rBm,n

m,n∑ (ψ )ei(mθ−nϕ )

R(ψ ) = Rm,nm,n∑ (ψ )cos(mθ −nϕ )

Z(ψ ) = Zm,nm,n∑ (ψ )sin(mθ −nϕ )

Plasma configuration may be optimised numerically by variation of the field parameters.

Plasma configuration may be optimised numerically by variation of the field parameters.



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VMEC on Kurchatov GRID

• LCG-2 - based Russian Data Intensive Grid consortium resources.

• About 7.500 cases computed (about 1.500 was not VMEC-computable, i.e. no equilibrium).

• Each case took about 20 minutes. • Up to 70 simultaneous jobs running on the grid.• Genetic Algorith used to select the optimum case.

- See:See:V. Voznesensky. “Genetic Optimisations in Grid”. V. Voznesensky. “Genetic Optimisations in Grid”. User Forum, 2006.User Forum, 2006.

• LCG-2 - based Russian Data Intensive Grid consortium resources.

• About 7.500 cases computed (about 1.500 was not VMEC-computable, i.e. no equilibrium).

• Each case took about 20 minutes. • Up to 70 simultaneous jobs running on the grid.• Genetic Algorith used to select the optimum case.

- See:See:V. Voznesensky. “Genetic Optimisations in Grid”. V. Voznesensky. “Genetic Optimisations in Grid”. User Forum, 2006.User Forum, 2006.



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Kinetic Transport• Following independent particle orbits

• Montecarlo techniques: Particles distributed according to experimental density and ion temperature profiles (Maxwellian distribution function)

• SUITABLE PROBLEM FOR CLUSTER AND GRID TECHNOLOGIES

rVD =

rE ×

rB

B2 +m2q

2v2 −v⊥2( )

rB×∇

rB

B3



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Kinetic Transport

Example of orbit in the real 3D Example of orbit in the real 3D TJ-II Geometry (single PE). TJ-II Geometry (single PE).

~1 GBy data, 24 h x 512 PE~1 GBy data, 24 h x 512 PE

Distribution function of parallel Distribution function of parallel velocity at a given position velocity at a given position (Data Analysis).(Data Analysis).



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Kinetic transport

No collisions: 0.5 ms of trajectory takes 1 sec. CPU..No collisions: 0.5 ms of trajectory takes 1 sec. CPU..

Collisions: 1 ms of trajectory takes 4 sec CPU. Collisions: 1 ms of trajectory takes 4 sec CPU. Particle life: 150 - 200 ms. Single particle Particle life: 150 - 200 ms. Single particle ~ 10 min.~ 10 min.

Necessary statistics for TJ-II 10Necessary statistics for TJ-II 1077 particles. particles.



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COMPUTING in the GRID: Future applications

– EDGE2D Application for tokamaks

– Transport Analysis of multiple shots (typically 104 shots) or Predictive Transport with multiple models: e. g. ASTRA. CIEMAT(Spa) + IPP(Ger) + Kurchatov(Rus) + EFDA(UE) + …

– Neutral Particle Dynamics: EIRENE:CIEMAT(Spa) + IPP(Ger)



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JET – Flagship of Worldwide Fusion: EDGE2D Equilibrium code.



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Cross section of present EU D-shaped tokamaks compared to the ITER project

EDGE2D: Determine plasma shape from Measurements: Plasma current, Pressure,

Magnetic field…

rj ×

rB=

r∇p

-EDGE2D code solves the 2 D fluid equations for the conservation of energy, momentum and particles in the plasma edge region.

-Ions, electrons and all ionisation stages of multiple species are considered.

-Interaction with the vessel walls is simulated by coupling to monte-carlo codes, to provide the neutral ion and impurity sources.



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Massive Transport Calculations

For Instance: Enhanced heat Confinement in TJ-II. Lower heat diffusivity for low electron density and high absorbed power density.

A different case on every PE.

0

0.5

1

1.5

2

-15 -10 -5 0 5 10 15

Pe-2562Pe-2565Pe-2558Pe-2560Pe-2559

<r> (cm)

0

0.5

1

1.5

-15 -10 -5 0 5 10 15

2562256525582560.2559

<r> (cm)0

0.2

0.4

0.6

0.8

1

1.2

-15 -10 -5 0 5 10 15

25592560255825652562

<r> (cm)

0.1

1

10

0 5 10 15

Chi-2562Chi-2565Chi-2558Chi-2560Chi-2559

r (cm)0

1

2

3

4

5

0.5 1 1.5n

0T

e-3/2 (1019 m-3 keV-3/2)



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EIRENEEIRENE CodeCode

Trayectory of a He atom in TJ-II. Vertical and horizontal proyections. It starts in the green point and is absorbed in the plasma by an ionization process. The real 3D geometry of TJ-II vacuum chamber is considerd.



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DATA HANDLING

Storage: Large data flux: 104 sensors x 20-50 kHz sampling= 1-10 GBy per second raw datax 0.5 h= 3 TBy per shot in ITER every 1,5 h

Data Access & Sharing in Large Cooperative Experiments:Strategy to be defined:-Database with distributed access or distributed storage?-The evolution of technologies until ITER works.

If distributed storage: We need a standard representation for experimental data in LCG-2/gLite CE middleware.Storage should allow to do some basic processing: neural network, clustering…



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DAS Tools: Visualization, DAQ and processing

To add grid-aware protocols for:

• Data navigation and mining

• Data exchange

• Data search

• Event catch



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Conclusions

• VO of Fusion grid is almost ready (the problem of the name).

• Effort to get more partners in and outside EFDA is being done.

• Several applications are running in the grid.• Future applications for the grid are identified.• A deep discussion and investigation on large

amount of data handling is needed. • Cook book for data handling in the grid is desirable.

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