J.-N. Leboeuf V.K. Decyk R.E. Waltz J. Candy W. Dorland Z. Lin S. Parker Y. Chen W.M. Nevins B.I....
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Transcript of J.-N. Leboeuf V.K. Decyk R.E. Waltz J. Candy W. Dorland Z. Lin S. Parker Y. Chen W.M. Nevins B.I....
![Page 1: J.-N. Leboeuf V.K. Decyk R.E. Waltz J. Candy W. Dorland Z. Lin S. Parker Y. Chen W.M. Nevins B.I. Cohen A.M. Dimits D. Shumaker W.W. Lee S. Ethier J. Lewandowski.](https://reader036.fdocuments.in/reader036/viewer/2022062500/5697bfda1a28abf838cafdcf/html5/thumbnails/1.jpg)
J.-N. LeboeufV.K. Decyk
R.E. WaltzJ. Candy
W. Dorland Z. Lin
S. ParkerY. Chen
W.M. NevinsB.I. CohenA.M. DimitsD. Shumaker
W.W. LeeS. EthierJ. LewandowskiW. Wang
![Page 2: J.-N. Leboeuf V.K. Decyk R.E. Waltz J. Candy W. Dorland Z. Lin S. Parker Y. Chen W.M. Nevins B.I. Cohen A.M. Dimits D. Shumaker W.W. Lee S. Ethier J. Lewandowski.](https://reader036.fdocuments.in/reader036/viewer/2022062500/5697bfda1a28abf838cafdcf/html5/thumbnails/2.jpg)
The Plasma Microturbulence Project
Our Goal:Understanding plasma microturbulencethrough direct numerical simulation
• Plasma microturbulence is a critical issue to magnetic fusion program
– Controls energy confinement Determines size and cost of a
burning plasma experiment
• Direct numerical Simulation is the right tool to study microturbulence
– Far better diagnostics than those available on experiments
– Excellent resolution can be achieved on existing computers
Our Game plan:• Code Development
– Enhanced Fidelity
– Increased Efficiency
– Common data analysis & visualization system
• Code Validation
– Against each other’s codes
– Against experiment & theory
• Expanding our user community
– Web-based applications– Collaborations with theory
and experimental communities
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Plasma Microturbulence is an Interesting Scientific Problem
Quasi-2-D turbulence in a 3-D toroidal geometry exhibits inverse cascades and other features of 2-D turbulent systems
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Largest runs with ‘GTC’ code required 1 billion particles and 125 million grid points using 1024 processors on the IBM-SP at NERSC
Plasma Microturbulence SimulationsRequire State-of-the-Art Computers
Scaling of Plasma Microturbulence with System Size
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Enhanced Code Fidelity
• Physics relevant for plasma confinement:
– Ion-scale Physics– Electron Dynamics– Turbulent Electric &
Magnetic Field– Realistic Geometry & Plasma
Size
• Accurate implementation demands:
– Excellent spatial resolution– High-order time integration– Advanced data-management
and visualization dealing with large data sets
QuickTime™ and a decompressor
are needed to see this picture.
Simulation Data from GYRO Code
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Code Efficiency is a Critical Issue
Scaling of Particle-in-Cell Code (‘GTC’)Plasma Microturbulence
Project Codes:– Are largest users of computer
cycles within the Fusion Energy Sciences Program
– PMP codes Scale ~ Linearly with Number of Processors
– Production code efficiencies of 10-20% are achieved
Actively working with SciDAC Performance Evaluation Research Center to improve code efficiency
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Advanced Visualization and Data Analysis Challenges
Terabytes of data are now generated at remote location (Data Management, Data Grid technologies)
Advanced visualization techniques needed to help identify key features in the data (Parallel Visualization)
Data must be efficiently analyzed to compute derived quantities
121 Milliongrid points
Temperature
Time
Particle in Cell Turbulence Simulation
Heat Potential
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Data Management, Data Analysis & Visualization
• Terabytes/simulation is Data management issue
– Interactions with SciDAC Fusion Collaboratory
• Data must be analyzed– To validate codes– To gain insight
• Interactive data analysis– New insights from analyzing
data in new ways• Visualization of analyzed data
– Multi-dimensional data sets– Efficient means of
communicating between computers to people
Turbulent FluctuationSpectrum