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http://www.phy.ornl.gov/tsi/. Organization of Talk: TSI Project Description TSI-ISIC Collaborations Ongoing TSI-SDM Projects A Look Ahead. Investigator Team. Cross-Cutting Team Long-Term Collaborations Structured like SciDAC. TOPS. - PowerPoint PPT Presentation
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Organization of Talk: TSI Project Description TSI-ISIC Collaborations Ongoing TSI-SDM Projects A Look Ahead
http://www.phy.ornl.gov/tsi/
Investigator Team
Radiation Transport/Radiation Hydrodynamics
Blondin (NC State) Bruenn (FAU) Hayes (UCSD) Mezzacappa (ORNL) Swesty (SUNYSB)
Nuclear Structure Computationsfor EOS and Neutrino-Nucleus/Nucleon Interactions
Dean (ORNL, UT) Fuller (UCSD) Haxton (INT, Washington) Lattimer (SUNYSB) Prakash (SUNYSB) Strayer (ORNL, UT)
Linear System/Eigenvalue Problem Solution Algorithms for Radiation Transport and Nuclear Structure Computation
Dongarra (UT, ORNL) Saied (UIUC, NCSA) Saylor (UIUC, NCSA)
Visualization
Baker (NCSA) Toedte (ORNL)
Cross-Cutting Team Long-Term CollaborationsStructured like SciDAC
Supernova Science
Blondin Bruenn Fuller Haxton Hayes Lattimer Meyer (Clemson) Mezzacappa Swesty
TOPS
TOPS
SDM
CCAPERCTSTT
GoalGoal Ascertain the explosion mechanism(s). Reproduce supernova phenomenology (element synthesis; neutrino, gravitational wave, and gamma ray signatures; neutron star kicks; gamma ray burst connection)
RelevanceRelevance Dominant source of many elements in the Universe. Given sufficiently well developed models, serve as laboratories for fundamental nuclear and particle physics that cannot be explored in terrestrial laboratories. Driving application in computational science (radiation transport, hydrodynamics, nuclear physics, applied mathematics, computer science, visualization).
ParadigmParadigm Result from stellar core collapse and bounce in massive stars. Radiatively driven (perhaps some are MHD driven, or both).
Need Boltzmann SolutionNeed Angular DistributionNeed Spectrum
“Gray” Schemes InadequateSpectrum ImposedLimited Angular Information (Few Moments)Parameterized (No First Principle Solution)
The bar is high! (10% effects can make or break explosions.)
Janka and Mueller
Herant et al.
Mezzacappa et al.
Fryer and Heger
Burrows, Hayes, and Fryxell
Swesty TSITSIYear 1Year 1
TSITSIYear 2Year 2
TSITSIYear 3Year 3
TSITSIYear 2Year 2
Gra
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Gra
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Neutrino EnergyNeutrino Energy
Past Transport in 2D ModelsD: DiffusionFLD: Flux-Limited DiffusionMGFLD: Multigroup FLDMGBT: Boltzmann Transport
What is the Recipe for Explosion?
Are there multiple mechanisms? Neutrino-driven supernovae MHD-driven supernovae Supernovae driven by both neutrinos and MHD effects
One mechanism for a class of stars?
Is the mechanism tailored to the individual star?
Neutrino Heating
Convection
Rotation
Magnetic Fields
GeneralRelativity
HydrodynamicsExplicit Differencing
Reactive FlowsNewtonian
General Relativistic
RadiationTransport
Implicit DifferencingMGFLD
PreconditionersSparse System Solvers
MGBTPreconditioners
Sparse System Solvers(Matrix Free)
Nuclear,Weak Interaction
PhysicsThermodynamics
(Composition),Neutrino Sources and Interactions
Supernova Science
Implicit Time DifferencingExtremely Short Neutrino-Matter Coupling Time ScalesNeutrino-Matter EquilibrationNeutrino Transport Time Scales
Nonlinear Algebraic EquationsLinearizeSolve via Multi-D Newton-Raphson Method
Large Sparse Linear Systems
ISIC Collaborations: TOPSISIC Collaborations: TOPS
Progress:Sparse Approximate Inverses for 2D MGFLD (Saylor, Smolarski, Swesty; J. Comp. Phys.)ADI-Like Preconditioner for Boltzmann Transport (D’Azevedo et al.; Precond 2001, NLAA)
AGILE-BOLTZRAN, V2D codes turned over to TOPS for analysis and development.
Boltzmann Equation nonlinearintegro-PDE
Memory Requirements (assuming matrix-free methods): 10s Gb up to 1/2 Tb
TSI Code: F90 + MPI Code Object-Oriented Design for Interoperability and Reuse Application Framework:
IBEAM = Interoperability Based Environment for Adaptive Meshes NASA HPCC-Funded Project (PI: Swesty)
AMR: PARAMESH
ISIC Collaborations: CCTTSSISIC Collaborations: CCTTSS
Goal: Develop our framework to be CCA-compliant.Initiated discussions with ANL, LLNL, and ORNL members of CCTTSS.
Assess Code Performance on Parallel Platforms Identify Code Optimizations to Increase Performance
TSI Code SuiteHydrodynamics:
VH-1 (PPM)ZEPHYR (Finite Difference)
Neutrino Transport:AGILE-BOLTZTRAN: 1D General Relativistic Adaptive Mesh
Hydrodynamics with 1D Boltzmann TransportV2D: 2D MGFLD Transport Code V3D: 3D MGFLD Transport Code (Under Development)2D/3D Boltzmann Code (Under Development)
Re
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H-1
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ISIC Collaborations: PERCISIC Collaborations: PERC
VH-1 numerical hydrodynamics algorithmscales well.
Adaptive Quadratures (Direction Cosines) for Multidimensional Radiation Transport
Results for 1D Boltzmann Transporton Milne Problem (D’Azevedo):
Greatest challenge to completing 3D Boltzmann simulations is memory.Minimize number of quadratures to minimize memory needs while maintaining physical resolution. (Also important for 1D/2D MGBT.)Optimization Problem
ISIC Collaborations: TSTTISIC Collaborations: TSTT
Extended Core
Compact Core
Identify Optimal Paths in Our Collaborative Visualization Server-Client ModelMaximize Bandwidth along these Paths (Not Achieved Using Current Protocols)
Collaboration with Supporting Base Projects: NetworkingCollaboration with Supporting Base Projects: Networking
Participated in ORNL Workshop on DoE High-Performance Network R&D and Applications
Convey TSI Needs to Networking Team Participate in White Paper to Define and Develop Interface between Efforts
ISIC Collaborations: SDMISIC Collaborations: SDM
Use PROBE environment for staging data between simulation platforms and end-user visualization platforms. Develop new data analysis techniques/tools tailored to our application, allowing (a) data reduction and (b) discovery potential. Use of agent technology for distributed data analysis (data analysis must be done in parallel to achieve reasonable throughputs).
QuickTime™ and aCompact Video decompressor
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QuickTime™ and aCompact Video decompressor
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QuickTime™ and aCompact Video decompressor
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QuickTime™ and aCompact Video decompressor
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Latest TSI 2D/3D Models:
Hydrodynamics only.Focused on understanding 2D/3D flow and its coupling to shock wave.Convectively stable.
2D model exhibits bipolar explosion (due to nonlinear flow-shock interaction).
3D model exhibits similar “long-wavelength” behavior. Key finding.New “rolling” flows identified.
AAS Meeting; Ap.J. SubmittedAAS Meeting; Ap.J. Submitted
2D Model2D Model
3D Model3D Model
SDM: Data NeedsSDM: Data Needs
3D Hydrodynamics Run5 Variables (Density, Entropy, Three Fluid Velocities)1024 X 1024 X 1024 Cartesian Grid1000 Time Steps
20 Terabyte Dataset
StingrayRS/6000 S80
MarlinRS/6000 H70
Origin 2000Reality Monster
ExternalEsnet Router
IBM and Compaq SupercomputersProbeProduction
Production HPSS
ProbeHPSSCAVE
Other ProbeNodes
Bulk Storage
Data Reduction, pre-Vis ManipulationRendering
SDM: PROBESDM: PROBE
Utilize PROBE until data manipulations, partitioning of manipulations, and bandwidths are known. PROBE is adaptable!
SDM: Data AnalysisSDM: Data Analysis Data Reduction Scientific Discovery
Original density distribution at finaltime “slice.”
Density distribution at last slice reconstructed from 30 principalcomponents. (First slice reconstructed from 3!)
ServerServer ClientClient
PCA Data Reduction Networking Technologies
PCA Data ReconstructionIntegrate into collaborative visualization?
New Windows on the Universe?
Scientific DiscoveryCan we use current data analysis tools to better understand and better quantify supernova physics?Can we develop new tools that will provide a new view of supernova physics?
Team of Agents Divides Up Data
SDM: AgentsSDM: Agents
Current data analysis techniques performed on a 10 Gb dataset would take 3 years to complete!
Need for distributed data analysis.
Agents perform analysis on subsets of data.Merge results via peer-to-peer agent collaboration and negotiation.
+ GUI/environment for the selection and (distributed) use of data analysis tools and the display of pre- and post-processed data.
Both data analysis and visualization can employ agent technology.
SDM: A Look AheadSDM: A Look Ahead
We have a testbed! Existing 2D/3D datasets. Three TSI nodes: NCSA, NCSU, ORNL.
Testbed for collaborative visualization tools.Testbed for networking.
PROBE being used to postprocess the data. PCA has been used successfully for data reduction. Agents have been used in a cross-platform demo utilizing this data.
Continue to explore possibilities.Continue extensive interactions between TSI modelers and SDM data analysts.
Can we integrate data analysis and agent technology (distributed data analysis) with collaborative visualization?
Will existing tools/new tools lead to scientific discovery?New views on the data?Better quantification of supernova dynamics?
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