Computational Seismology and Grid Computational Seismology and Grid Computational Seismology and Grid Computing – – Application and Potential Application and Potential Computing – Application and Potential Computing Shiann- -Jong Lee Jong Lee Shiann Institute of Earth Sciences Academia Sinica ISGC2008 2008/04/10
Outline Outline � High performance computing in Earth Sciences � High performance computing in Earth Sciences Computing, Visualization and Storage Computing, Visualization and Storage � Computational seismology � Computational seismology Examples from earthquake source, path and site studies Examples from earthquake source, path and site studies � Application and potential of Gird computing in � Application and potential of Gird computing in seismology seismology
High performance computing in High performance computing in High performance computing in Computational Seismology Computational Seismology Computational Seismology � Why high performance computing � Why high performance computing - Computation Computation - Computation - Visualization Visualization - - Storage Storage - Visualization � HPC in Computational � HPC in Computational Seismology Seismology - Earth Simulator (Japan) Earth Simulator (Japan) - Storage - Caltech GPS Dell Cluster (USA) Caltech GPS Dell Cluster (USA) - - ERI SGI ERI SGI Altix Altix System (Japan) System (Japan) -
The Earth Simulator (2002) The Earth Simulator (2002) The Earth Simulator (2002) http://www.es.jamstec.go.jp/index.en.html
Caltech GPS Dell Cluster (2006) Caltech GPS Dell Cluster (2006) Caltech GPS Dell Cluster (2006) http://citerra.caltech.edu/wiki/ - 512 dual-processor quad-core nodes - 4096 MPI processes - 6144 Gb memory
ERI SGI Altix Altix System (2003) System (2003) ERI SGI Altix System (2003) ERI SGI http://wwweic.eri.u-tokyo.ac.jp/computer/
Computational Seismology Computational Seismology Computational Seismology � Source Studies � Source Studies - Real Real- -time Grid time Grid- -based CMT: based CMT: distributed computing distributed computing - - Finite Finite- -fault source inversion: fault source inversion: parallel computing, parallel computing, storage, storage, visualization visualization - � Path Studies � Path Studies - Finite Finite- -frequency tomography study: frequency tomography study: parallel computing, parallel computing, storage storage - - - Green Green’ ’s function database: s function database: storage storage � Site and Comprehensive Simulation � Site and Comprehensive Simulation - 3 3- -D, full waveform modeling: D, full waveform modeling: parallel computing parallel computing, , visualization visualization - - Real Real- -time analysis: time analysis: high performance computing, high performance computing, storage storage - - Hazard analysis, earthquake database: Hazard analysis, earthquake database: high performance computing, high performance computing, storage storage - • Parallel computing is the simultaneous use of multiple compute resources to solve a computational problem. • Distributed computing is a science which solves a large problem by giving small parts of the problem to many computers to solve and then combining the solutions for the parts into a solution for the problem.
Strong Ground Motion Simulation of the Strong Ground Motion Simulation of the 1999 Chi- -Chi, Taiwan, Earthquake Chi, Taiwan, Earthquake 1999 Chi
Rupture process Inversion results Inversion results 0.5 12 6 3 2 1 0 Slip(m) Slip distribution
Wave- -Field Snapshot Field Snapshot Wave
Synthetic vs. Observation Synthetic vs. Observation
Numerical modeling of seismic wave Numerical modeling of seismic wave propagation in the Taipei basin propagation in the Taipei basin 2002, 331 earthquake (Mw 7.1) 1999, Chi-Chi earthquake (Mw 7.6) 1986, Hualien offshore earthquake (Mw 7.3)
Taipei Basin Taipei Basin (a) Map view of the Taipei basin. The depth of the basement is represented by gray colors. The red line shows the JhongShan freeway across the basin. The location of the world’s current tallest building, Taipei 101, is indicated in the eastern part of the basin. (b) Perspective view of the two major discontinuities in the Taipei basin: The SongShan formation and the basin basement. Surface topography around the basin is shown at the top of the figure.
North Taiwan SEM Mesh North Taiwan SEM Mesh Taipei basin mesh Topography Basin Moho 3D Velocity Realistic Topography Caltech's Division of Geological & Caltech's Division of Geological & Planetary Sciences Dell cluster Planetary Sciences Dell cluster 512 dual-processor quad-core nodes 512 dual-processor quad-core nodes
2004/10/23 Taipei Earthquake (M L 3.8) 2004/10/23 Taipei Earthquake (M L 3.8) Synthetic vs. Observation PGA Simulation Velocity waveform Band-pass filtered between 0.8 and 10 sec
Computational Visualization Computational Visualization � Southern California Earthquake Center (SCEC) – SDSC Visualization Services The TeraShake simulations modeled the earth shaking that would rattle Southern California if a 230 kilometer section of the San Andreas fault ruptured producing a magnitude 7.7 earthquake. � The Earth Simulator Center - Atmosphere & Ocean Simulation Research Group We carry out simulation researches using CFES (CGCM for the Earth Simulator) to understand the mechanism of the variability and to study the predictability in the coupled atmosphere–ocean system.
I-Lan Doublet Event Taipei Basin 2005/03/06, M L = 5.9 N 102km Doublet event m k 8 8 Topography Basin Moho 3D Velocity 100km
Community mesh model Community mesh model for the whole Taiwan for the whole Taiwan N N 380 km Central Range Western Plain Longitudinal 100 km Valley 210 km Coastal Range EURASIAN PLATE slow Seismic Wave Velocity o h o ? M ? ? ? PHILIPPINE SEA PLATE ! resolution of the mesh at the surface: ! ------------------------------------- ! ! spectral elements along X = 448 ! spectral elements along Y = 864 ! GLL points along X = 1793 ! GLL points along Y = 3457 ! average distance between points along X in m = 116.8700 fast ! average distance between points along Y in m = 109.9049
HPC Cluster in IES HPC Cluster in IES HPC Cluster in IES � IBM Blade Server : 20 MPI processes (2004) � IBM Blade Server : 20 MPI processes (2004) � PC Cluster: 32 MPI processes (2007) � PC Cluster: 32 MPI processes (2007)
Application and potential of Application and potential of Gird computing in seismology Gird computing in seismology What’ ’s Grid Computing? s Grid Computing? What
’s Grid Computing? s Grid Computing? What’ What
Grid- -based Computing Pathway based Computing Pathway Grid ASGC Grid Resource Visualization, Analysis Community models IES or elsewhere Machines (ASGC, IES) Hazard map Problem definition Grid computing Numerical Numerical Input Input output output • Rupture model (source) Computing Computing • Simulation region Numerical (Path and Site) visualization • Physical properties (Maximum frequency, Minimum Data Grid Velocity and so on) Storage Storage Result output Result output
Grid- -based Visualization Framework based Visualization Framework Grid 4D visualization of Oct. 23, 2004 Taipei earthquake Parallel I/O Reduction Sorting Transport TCP/IP Rendering Receive Buffer ... ... ... ... Grid Resources Visualization Machine (modified from SCEC CME project)
Summary Summary � � High performance computing have succeeded in applying to High performance computing have succeeded in applying to seismology, such as source, path, site effect studies and seismology, such as source, path, site effect studies and comprehensive 3- -D simulation. D simulation. comprehensive 3 � � However, constructing a realistic earthquake simulation from However, constructing a realistic earthquake simulation from source and path models of constituent phenomena and source and path models of constituent phenomena and executing that simulation on suitable computing platforms executing that simulation on suitable computing platforms becomes increasingly complex. becomes increasingly complex. � � We are finding possible collaborations between researchers in We are finding possible collaborations between researchers in the information technology areas and earthquake scientists to the information technology areas and earthquake scientists to deal with more and more complex seismologic problems. deal with more and more complex seismologic problems. � � The Grid technique is therefore one of the best candidate for The Grid technique is therefore one of the best candidate for computational seismology studies in the near future. computational seismology studies in the near future.
Thank you 4D Visualization of the 1999 Chi-Chi, Taiwan, Earthquake Mw 7.6 For more information: http://www.earth.sinica.edu.tw/~sjlee/index.htm
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