Computational Seismology and Grid Computational Seismology and Grid - - PowerPoint PPT Presentation

Computational Seismology and Grid Computing – Application and Potential Computational Seismology and Grid Computational Seismology and Grid Computing Computing – – Application and Potential Application and Potential

Shiann Shiann-

• Jong Lee

Jong Lee

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 Computational Seismology High performance computing in High performance computing in Computational Seismology Computational Seismology

• Why high performance computing

Why high performance computing

• Computation

Computation

• Visualization

Visualization

• Storage

Storage

• HPC in Computational

HPC in Computational Seismology Seismology

• Earth Simulator (Japan)

Earth Simulator (Japan)

• Caltech GPS Dell Cluster (USA)

Caltech GPS Dell Cluster (USA)

• ERI SGI

ERI SGI Altix Altix System (Japan) System (Japan)

Computation Visualization Storage

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 System (2003) ERI SGI ERI SGI Altix Altix System (2003) System (2003)

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 1999 Chi-

• Chi, Taiwan, Earthquake

Chi, Taiwan, Earthquake

Inversion results Inversion results

0.5 1 2 3 12 6

Slip(m)

Slip distribution Rupture process

Wave Wave-

• Field Snapshot

Field Snapshot

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

1999, Chi-Chi earthquake (Mw 7.6) 2002, 331 earthquake (Mw 7.1)

1986, Hualien

• ffshore earthquake

(Mw 7.3)

(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.

Taipei Basin Taipei Basin

North Taiwan SEM Mesh North Taiwan SEM Mesh

Realistic Topography Taipei basin mesh Caltech's Division of Geological & Planetary Sciences Dell cluster

512 dual-processor quad-core nodes

Caltech's Division of Geological & Planetary Sciences Dell cluster

512 dual-processor quad-core nodes

Topography Basin Moho 3D Velocity

2004/10/23 Taipei Earthquake (M 2004/10/23 Taipei Earthquake (ML

L 3.8)

3.8)

PGA Simulation Synthetic vs. Observation

Velocity waveform Band-pass filtered between 0.8 and 10 sec

Computational Visualization Computational Visualization

Southern California Earthquake Center (SCEC) – SDSC Visualization Services 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. 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.

Topography Basin Moho 3D Velocity

100km 102km 8 8 k m

Taipei Basin

N

Doublet event

I-Lan Doublet Event 2005/03/06, ML = 5.9

! 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 ! average distance between points along Y in m = 109.9049

fast slow Seismic Wave Velocity

N N

380 km 210 km 100 km

? ? ? ?

Coastal Range Longitudinal Valley Central Range Western Plain

PHILIPPINE SEA PLATE EURASIAN PLATE

Community mesh model Community mesh model for the whole Taiwan for the whole Taiwan

M

• h

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)

What What’ ’s Grid Computing? s Grid Computing?

Application and potential of Application and potential of Gird computing in seismology Gird computing in seismology

What What’ ’s Grid Computing? s Grid Computing?

Result output Result output

• Rupture model

(source)

• Simulation region

(Path and Site)

• Physical properties

(Maximum frequency, Minimum Velocity and so on)

Problem definition

Input Input

Community models Grid computing

ASGC Grid Resource

Data Grid

Computing Computing Storage Storage IES or elsewhere

Grid Grid-

• based Computing Pathway

based Computing Pathway

Hazard map Numerical visualization

Visualization, Analysis Machines (ASGC, IES) Numerical Numerical

• utput
• utput

Grid Grid-

• based Visualization Framework

based Visualization Framework

Reduction TCP/IP Rendering Sorting Transport ... ... ... ... Receive Buffer Parallel I/O

Grid Resources Visualization Machine

(modified from SCEC CME project)

4D visualization of

• Oct. 23, 2004

Taipei earthquake

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 comprehensive 3-

• D simulation.

D simulation.

• 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.

4D Visualization of the 1999 Chi-Chi, Taiwan, Earthquake Mw 7.6 For more information: http://www.earth.sinica.edu.tw/~sjlee/index.htm

Thank you