QuakeSim Project: Portals and Web Services for
Transcript QuakeSim Project: Portals and Web Services for
QuakeSim Project: Portals
and Web Services for
QuakeSim Project Summary
Goal is to provide a distributed environment
for connecting scientific computing and data
resources with Web based user interfaces.
QuakeSim’s IT development includes
Portals for user interfaces.
Web Services for running remote
applications and accessing databases
Databases for semantic fault models and
InSAR data (USC)
Some QuakeSim Applications and Their Data
Fault models are used to calculate surface displacements (Disloc)
using Okada method.
Simplex is the inverse.
These help researchers refine their fault models from observed
displacements, or model displacements associated with faults.
Finite element code for detailed modeling of fault stresses,
seismic displacements, uses fault models as input.
Coupled to mesh generation tools
Can (for example) calculate post- and co-seismic displacements.
Time series analysis code, can be applied to GPS and seismic
Identifies signal components (possibly associated with underlying
physical causes) with no fixed parameters.
Portlets + Client Stubs
WSDL WSDL WSDL WSDL
Host 1 (QT or GRWS)
Host 2 (Comp Grid)
Host 3 (GIS)
Daily RDAHMM Updates
Daily analysis and
of GPS data from
April 21, 2006:
We can also anlyze
real-time GPS data
from the CRTN.
Real time state
Disloc model of Northridge
fault. Disloc used in Gerry
Simila’s geophysics classes
Integrating QuakeSim and UAVSAR
July 29, 2008 M 5.4
Chino Hills Earthquake
Used QuakeSim to model
displacements from the
Passed on KML file to
with UAVSAR image
Will continue to merge
projects using the Los
Angeles ShakeOut in
mid–November as a
TeraGrid Supercomputing Resources (GPIR)
portlet and plotting
QuakeSim and Web 2.0
Export all observations and computational
results as KML, GeoRSS.
Use Social Networks to share projects, results,
papers, proposals, etc.
Facebook and OpenSocial have open APIs.
Use social (Google) gadgets to deliver your Web
components to everyone.
Use Google’s APIs to integrate your services with
Calendar, Blogspot, YouTube, etc.
Email: [email protected]
QuakeSim Web Site:
Portal SourceForge Page:
QuakeSim work is funded by NASA AIST (A.
Donnellan, PI) and ACCESS (Y. Bock, PI)
Indiana University developers: Galip Aydin,
Xiaoming Gao, Zhigang Qi
Robert Granat (JPL), Jay Parker (JPL), Maggi
Glasscoe (JPL), John Rundle (UC-Davis), Harout
Nazerian (JPL), Rami Al-Ghanmi (USC), Dennis
Mcleod (USC), Paul Jamason (Scripps), Ruey-Juin
Chang (Scripps), Gerry Simila (CSUN)
Stop Talking Now, Champ
Web 2.0 Approach
JSR 168 Portlets
Server-side integration and
AJAX, client-side integration and
RSS, Atom, JSON
REST (GET, PUT, DELETE, POST)
Open Social Containers (Orkut,
LinkedIn, Shindig); Facebook;
User Centric Gateways
Social Networking Portals
Workflow managers (Taverna, Kepler, Mash-ups
Grid computing: Globus, condor, etc
Cloud computing: Amazon WS Suite,
Q: What Is Web 2.0?
A: IT for everyone
Too much of “Enterprise” computing requires
specialized knowledge and specialized tools.
Result: specialization of tasks within teams like
Waste of talent: scientists can write code, just don’t
have time to waste on difficult operating
What then is Web 2.0 in detail?
What Is a Gadget?
Simple gadgets for getting a Grid proxy credential and running remote
commands. Both run on my own Web server.
Google Reader and GeoRSS
Google Maps and GeoRSS
Google Earth and KML
Cloud Computing and Gateways
Cloud computing is the combination of virtualization (Xen,
VMWare, OpenVZ,…) with Web Services
Web Services control the life cycle of the virtual machines.
The virtual machines are under the control of the application
UC-D can distribute the VC Service VM, for example
Examples include Amazon EC2, Eucalyptus (UCSD), and Virtual
Data clouds focus on data virtualization
Google’s BigTable, Facebook’s Cassandra
Apache’s Hadoop and related projects (HBase, HDFS)
MPI on clouds
Mounting high performance file systems
What Would You Want a Cloud?
Application Developers: Reproducible operating
Develop your application and be sure it will be
deployed under the same conditions.
Distribute reproducible results.
Have control of your operating environment
Move applications closer to data.
Data replication built-in
Assume vast amounts of cheap diskspace
Simplex refines fault
models from GPS
UCSB’s Queue Prediction Service (QBETS)
Forecasts time you will
wait in the queue on
various TG super
from OGCE project.
Some Design Choices
Build portals out of portlets (Java Standard)
Reuse capabilities from our Open Grid Computing Environments (OGCE) project, the
REASoN GPS Explorer project, and many TeraGrid Science Gateways.
Decorate with Google Maps, Yahoo UI gadgets, etc.
Use Java Server Faces to build individual component portlets.
Build standalone tools, then convert to portlets at the very end.
Use simple Web Services for accessing codes and data.
Keep It Stateless …
Use Condor-G and Globus job and file management services for interacting
with high performance computers.
Favor Google Maps and Google Earth for their simplicity, interactivity and
Generate KML and GeoRSS
Use Apache Maven based build and compile system, SVN on SourceForge
QuakeSim, Version 1
Reason to Revise
QuakeSim, Version 2
Application Web Service for
wrapping a.out executables.
service built with Apache
Services too coupled to
portal; no simple WSDL
programming interface; could
not be used in workflow
engines; not self contained
Give each code a proper
service interface. Retain
Apache Ant core but extend.
Keep WSDL message
structure simple (Strings,
ints, doubles, URLs), wrapped
as Java Beans
File Management Service
Unnecessary, too coupled to
Apache Axis 1.0
HTTP GET, URLs
Service manages persistent
portal sessions using
recursive XML structure.
Too slow (file system); didn’t Using DB40; all services
scale; XML databases didn’t
communicate with easily
XML serializable JavaBeans.
Mappings (ORM) not efficient
OGC-compatible map and
Too complicated; ORM is a
Google Maps, KML
Serial job submission
NSF TeraGrid and Open
Science Grid run full time
production Grids for HPC.
job management extensions
to GeoFEST service.
Grid Job Submission
Globus provides a universal queuing system interface.
PBS, LoadLeveler, Sun Grid Engine, LSF
We chose Condor-G as our job management software for
submitting jobs to HPC queuing systems.
University of Wisconsin
Works with Globus, Matlab DCE, Unicore, etc.
We co-locate Condor-G with our GeoFEST Web Service.
Communication is through Birdbath, Condor’s Web Service interface.
So GeoFEST service API is more or less the same, just now Grid enabled.
We also plan to release a general version of this service.
Condor command line and Birdbath have different names for job
Big Easter Egg hunt to find this, but now we know.
Set up and run RDAHMM, query Scripps
GRWS GPS Service, maintain persistent user
Similar to RDAHMM portlet; ST_Filter has
much more input.
Shows GPS stations on a Google Map,
displays last 10 minutes of data.
Real Time RDAHMM
Displays RDAHMM results of last 10 minutes
of GPS data in a Google map.
Calculates, updates RDAHMM event
classifications with daily updated GPS data
from SOPAC’s GRWS service (14 day delay,
but uses all the data).
Create input geometries, generate FE meshes,
run parallel FEM solvers.
Calculate service displacements from fault
They’ll see the Big Board!
QuakeSimDistributed Environment for Modeling Observations
Managing Real Time GPS Data
Slides from Galip Aydin
California Real Time Network
Continuous GPS Stations (CGPS) are depicted as
triangles while the Real-Time stations are
represented as circles. Image is obtained from
SOPAC GPS Explorer at
Network Data Rates
How does one manage all the data generated by the
85 stations? How can you get just the data you want?
Note this is fundamentally different from traditional
request/response style Web Services.
Processing Real-Time GPS Streams
A Complete Sensor Message Processing Path, including a data analysis application.
Application Integration with Real-Time
for 10 minutes
representation of the
2 – Multiple Publishers Test
Multiple Publishers Test
Time Of The Day
We add more GPS networks by running more publishers.
The results show that 1000 publishers can be supported
with no performance loss. This is an operating system
4 – Multiple Brokers Test
creation of Broker networks.
We create a two-broker
Messages published to first
broker can be received from
the second broker.
We take timings on each
We connect 750 clients to
each broker and run for 24
hours. We chose 750 clients to
stay well below the saturation