MFE%20Simulation%20Data%20Management

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MFE Simulation Data Management

• SLAC DMW 2004
• March 16, 2004
• W. W. Lee and S. Klasky
• Princeton Plasma Physics Laboratory
• Princeton, NJ

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Spatial Temporal Scales Present Major Challenge
to Theory Simulations

• Huge range of spatial and temporal scales.
• Overlap in scales often means strong
  (simplified) ordering not possible
• Different codes/theory for different scales.
• 5years Integration of physics into Fusion
  Simulation Project

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Major Fusion Codes
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Data Rates of Major Fusion Codes
Code (GB) now / 5yr Runtime now/5yr (hr) Processors Now/5yr Mbs Now/5yr
GTC 4,000 / 100,000 300/150 2048 80/ 1600
Gyro 10 / 100 30/30 512/2048 .8/ 8
GS2 10 / 100 30/30 512/2048 .8 / 8
Degas2 .1 1 10 .2
Transp .05 3 1 .04
Nimrod 5/ 50 20/20 128 .6/ 6
M3D 10 / 100 20/20 128 1.1/ 11
NSTX .25/shot 1/ 4 0.25 40 9, 36
Total (TB) 4.3 / 101
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Plasma Turbulence Simulation

• Gyrokinetic Particle-In-Cell Simulation
• -- Reduced Vlasov-Maxwell Equations
• Simulations on MPP Platforms
• -- Cray T3E IBM SP (NERSC), Cray-X1
  (ORNL),
• SX6 (Earth Simulator, Japan)
• Simulation of Burning Plasmas
• -- International Tokamak Experimental Reactor
  (ITER)
• Integrated Fusion Simulation Project (MFE)
• Visualization -- turbulence evolution
  particle orbits

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Gyrokinetic Approximation

• Gyromotion
• Polarization provides quasineutrality

W. W. Lee, PF 83 JCP 87
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(No Transcript)
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18
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(Ethier)

• Earth Simulator

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Ion Temperature Gradient Driven Turbulence
Particle Trajectories
Electrostatic Potential
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Data Management challenges

• GTC is producing TBs of data
• Data rates 80Mbs now, 1.6Gbs 5 years.
• Need QOS to stream data.
• This data needs to be post-processed
• Essential to parallelize the post-processing
  routines to handle our larger datasets.
• We need a cluster to post process this data.
• M (supercomputer processors) x N (cluster
  processors) problem.
• QOS becomes more important to sustain this
  post-processing.
• The post-processed data needs to be shared among
  collaborators
• Different sections of the post-processed data may
  go to different users .
• Post-processed data, along with other metadata
  should be archived into a relational database.

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Post processing of GTC Data.

• Particle Data
• No compression possible.
• Sent to 1 cluster for visualization/analysis.
• Work being done with K. Ma, U.C. Davis Visualize
  a million particles.
• Gain new insights into the theory.
• Field Data
• Geometric/Temporal compression of the data is
  possible.
• Data needs to be streamed to a local cluster at
  PPPL.
• Reduced subset needs to be sent to PPPL
  collaborators.
• Use Logistic Network. Beck, UT-K
• Data transfer needs to be automatic, and
  integrated into a dataflow/webflow for use with
  parallel analysis routines.
• We desire to see post-processed data during the
  simulation.

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After the analysis

• Post-processed data needs to be saved into a
  relational database
• How do we query this abstract data to compare it
  with experiments?
• 3D correlation functions
• Processing of TBs of data/run now, 100s of TBs
  of data/run in 5 years.
• Data mining techniques will be necessary to
  understand this data.