Name: Philip J. Maechling

Description: I work as the Information Technology Architect at the Southern California Earthquake Center. I have 20 years of professional software development experience on commercial, areospace, and scientific software systems. My system development experience includes commercial two-way radio development, military command and control system development with Hughes and TRW, real-time earthquake monitoring system development at Caltech, and large-scale high performance computing environments with SCEC, USC, and the TeraGrid.

I am currently working in a research group that is pursuing a geoscientific research program that utilizes high performance computing-based geophysical simulations. At SCEC, my software development work is focused on developing and using grid-based scientific workflow systems. I have collaborated with groups at ISI, USC HPCC, and San Diego Supercomputer Center to implement a large-scale workflow system that allows SCEC researchs to execute thousands of jobs and manage thousands of data files across a "virtual organization" that includes SCEC, USC, and several TeraGrid sites. SCEC is currently scaling up its simulation program through a series of increasingly complex and challeging simulations in order to demonstrate our readiness to use the petascale comptuing capabilities that are in the National Science Foundation development plans. These large scale computing systems provide an opportunity for SCEC perform simulation-based geoscience at a scale never before possible.

Research Interests:

• Software and System Development
• Scientific Workflows
• Parallel Programming Techiques
• Anelastic Earthquake Waveform Modeling:
  • Finite Difference
  • Finite Element
  • Spectral Element
• Dynamic Rupture Modeling
• Probablistic Seismic Hazard Analysis
• Modeling Building Response to Seismic Waves
• Real-time Earthquake Monitoring

ftp://pipeline.gps.caltech.edu/pub/users/hudnut/ShakeOut-kinematic/Graves_v1.1.0/ShakeOut_v1.1.0.avi

ftp://pipeline.gps.caltech.edu/pub/users/hudnut/ShakeOut-kinematic/Graves_v1.1.0/ShakeOut_v1.1.0.mov

1. Problem:

In order to understand earthquake hazards, scientist want to be able to predict ground motions that are produced by an earthquake. In simple terms, ground motions from an earthquake are expected to decrease with distance, that is, the ground motion waves are attenuated with distance from the earthquake. However, ground motion observations (seismograms) show that the decay with distance is non-uniform and depends on many factors including the geological characteristics of the area, and the rupture characteristics of the earthquake.

Geoscientists have develop numerical modeling codes that simulate earthquake wave propagation through geological structures. These codes have improved to the point that, at low frequencies (<1Hz), the codes can reproduce observed seismograms very accurately.

The simulations cannot, however, reproduce observed seismograms at frequencies of interest to building engineerings (>10Hz). This inability to model high frequencies is due to a number of factors. There are uncertainties in the geological structures that are used in the simulations, so improvements in the geological models may improve the results. Also, the processing requirements for higher frequencies are very demanding. Typically, regular-gridded finite difference codes are used in these simulation. For these codes, each doubling in frequency results in an increase in processing by a factor of 16.

In order to continue to improve the result of these simulations, we must either improve the efficiences of the codes used, or run on faster computers, or both.

1. Simulation Methods:

Earthquake wave propagation simulations are performed with a variety of modeling techniques including finite difference, finite element, and spectral element methods. Each method has advantages and dis-advantages. Our most commonly used code is a finite differnece code (AWM-Olsen) that uses a regular mesh and has shown scaling to over 40,000 processors.

The codes solves wave equations that relate a pressure wave and a media velocity with a "distrubance" in the media which is the earthquake. The inputs to a simulation are a "velocity mesh" which represent the "material properties" of the earth in the region being studied. Also, an earthquake source description is used. This typically specifies a time varying set of velocities at a set of mesh points. The geoscience behind earthquake source descriptions is one of the more complex aspects of the simulation.

The outputs of the simulation are typically velocity or displacment vectors at all the surface mesh points. A time history of these data points is saved and the time history can be plotted as seismogram and compared to observed seismograms for verification.

1. Parallel and Distributed Computing Techniques:

The AWM-Olsen code is a parellel finite difference code. It is fourth order is space and second order in time. It uses an explict solver for the wave equations partial differential equations. The MPI calls are a blocking point-to-point communications (mpi_send and mpi_recv).

1. Data Visualization and Analysis:

A variety of visualizations techniques are used. Nearly all visualizations show time varying images. Seismograms are visualized and the key issue for seismogram is geo-referencing the data. Surface ground motion is of interest. Typically, animations will show either instantaneous ground motions, or cummulative ground motions. Both styles have their uses. 4D volume data visualizations are of significant interest but the data sets are so large that these are very difficult to produce. Several outstanding examples of earthquake simulatation visualization is posted at the SDSC Visualization Services web site.

1. Managing Parallelism of Petascale Computers through new Programming Models -Partitioned Global Address Space Programming Models
2. High Performance Grid-based Workflows that Explot Data Locality
3. Converting Finite Difference AWM to use the PetScPartial Differential Equation Solver Libraries
4. An Optimized variable-grid finite difference method for seismic forward modeling.

Chourasia, A. 1, Cutchin, S. M., Olsen, K.B., Minster, B., Day, S., Cui, Y., Maechling, P., Moore. R., Jordan. T. (2006): Insights gained through visualization for large earthquake simulations. Discovering the Unexpected, Computer Graphics and Application Journal (PDF)

Deelman, E., G. Mehta, R. Graves, L. Zhao, N. Gupta, P. Maechling, T. Jordan (2006), Managing Large-Scale Workflow Execution from Resource Provisioning to Provenance tracking: The CyberShake Example", IEEE e-Science and Grid Computing 2006, Amsterdam, Netherlands, December 2006 (PDF)

Kristekova, M., J. Kristek, P. Moczo, and S. M. Day (2006). Misfit criteria for quantitative comparison of seismograms, Bull. Seism. Soc. Am., Vol 96, 1836-1850 (PDF)

Deelman, E. and Yolanda Gil, (2006) Managing Large-Scale Scientific Workflows in Distributed Environments: Experiences and Challenges, Proceedings of the Workshop on Scientific Workflows and Business Workflow Standards in e-Science, The Second IEEE International Conference on e-Science and Grid Computing, Amsterdam, The Netherlands, December 4-6, 2006. (PDF)

Maechling P., E. Deelman, G. Mehta, R. Graves, L. Zhao, N. Gupta (2006) SCEC CyberShake Workflows - Automating Probabilistic Seismic Hazard Analysis Calculations, Workflows for e-Science, D. Gannon, E. Deelman, M. Shields, I. Taylor (Eds), Springer 2007, XXII, 530 p., 181 illus., Hardcover ISBN: 978-1-84628-519-6 (PDF)

Gil, Yolanda, Varun Ratnakar, Ewa Deelman, Marc Spraragen, and Jihie Kim (2006) Wings for Pegasus: A Semantic Approach to Creating Very Large Scientific Workflows, Proceedings of the OWL: Experiences and Directions 2006 (OWLED-06), Athens, GA, November 10-11, 2006 (PDF)

Olsen, K. B., S. M. Day, J. B. Minster, Y. Cui, A. Chourasia, M. Faerman, R. Moore, P. Maechling, and T. Jordan (2006), Strong shaking in Los Angeles expected from southern San Andreas earthquake, Geophys. Res. Lett., 33, L07305, doi:10.1029/2005GL025472 (PDF)

T. Tu, H. Yu, L. Ramirez-Guzman, J. Bielak, O. Ghattas, K-L Ma, and D.R. O'Hallaron, “From Mesh Generation to Scientific Visualization: An End-to-End Approach to Parallel Supercomputing,” Proc. ACM/IEEE SC2006, Tampa, FL, 2006. (PDF)

Dalguer, L. A., and S. M. Day (2006). Staggered-grid split-node method for spontaneous rupture simulation, J. Geophys. Res. , 112, B02302, doi:10.1029/2006JB004467 (PDF)

T. Tu, H. Yu, J. Bielak, O. Ghattas, J. C. Lopez, K-L. Ma, D. R. O'Hallaron, L. Ramirez-Guzman, N. Stone, R. Taborda-Rios, J. Urbanic (2006),"Remote Runtime Steering of Integrated Terascale Simulation and Visualization" Proc. ACM/IEEE SC2006, Tampa, FL, 2006. (PDF)

Day, S. M., L. A. Dalguer, N. Lapusta, and y. Liu, (2005). Comparison of finite difference and boundary integral solutions to three-dimensional spontaneous rupture, J. Geophys. Res., Vol. 110, B12307, doi:10.1029/2005JB003813. (PDF)

Maechling, P., H. Chalupsky, M. Dougherty, E. Deelman, Y. Gil, S. Gullapalli, V. Gupta, C. Kesselman, J. Kim, G. Mehta, B. Mendenhall, T. Russ, G. Singh, M. Spraragen, G. Staples, K. Vahi (2005) Simplifying Construction of Complex Workflows for Non-Expert Users of the Southern California Earthquake Center Community Modeling Environment,ACM SIGMOD Special issue on Scientific Workflows, Record Vol. 34 No. 3, 24-30 (PDF)

Maechling, P., V. Gupta, N. Gupta, E. H. Field, D. Okaya, and T. H. Jordan (2005) Grid Computing in the SCEC Community Modeling Environment, Seismological Research Letters, 76,No. 5, 581-587 (PDF)

Field, E.H., N. Gupta, V. Gupta, M., P. Maechling, and T.H Jordan (2005) Hazard Map Calculations Using GRID Computing , Seism. Res. Lett.,76, No. 5, 565-573.(PDF)

Field, E.H., N. Gupta, V. Gupta, M. Blanpied, P. Maechling, and T.H Jordan (2005b). Hazard Calculations for the WGCEP-2002 Forecast Using OpenSHA and Distributed Object Technologies, Seismological Research Letters 76, 161-167. (PDF)

• Philip Maechling's Full Curriculum Vitae
• Philip Maechling's Current Resume

1. Jordan , T.H., Maechling P., and SCEC/CME Collaboration (2003) The SCEC Community Modeling Environment – An Information Infrastructure for System-Level Earthquake Science, Seism. Res. Lett., 74 No. 3, 44-46. (PDF)
2. Kanamori, H., Maechling, P., and Hauksson, E. (1999) Continuous Monitoring of Ground Motion Parameters, Bull. Seism. So. Am. 89, 311-316
3. Hauksson, E., P. Maechling, and H. Kanamori (1994). Real-time earthquake monitoring using Terrascope, Seis. Res. Lett. 65, p. 47.