EGEE, Grid infrastructure for Earth Science

bunkietameΤεχνίτη Νοημοσύνη και Ρομποτική

20 Οκτ 2013 (πριν από 4 χρόνια και 8 μήνες)

137 εμφανίσεις

EGEE,Grid infrastructure for Earth Science
August 2007
M.Petitdidier (IPSL,FR),E.Clévédé (IPGP,FR),L.Fusco (ESA),S.Godin-Beekmann (IPSL,FR),L.Hluchy (UISAV,SK),G.Lecca (CRS4,IT),P.Renard (Unine,CH),
H.Schwichtenberg (FhG/SCAI,DE),W.Somde Cerff (KNMI,NL),D.Thomas &G.Vetois (CGGVeritas,FR),J.-P.Vilotte (IPGP,FR),G.Moguilny (IPGP,FR),
D.Weissenbach (IPSL,FR),M.Zhizhin (GCRAS,RU)
Grid:Revolution or Evolution
The web has spawned a true revolution!
What about Grid?
Historically,the Grid can be viewed as the latest step toward
distributed computing solutions;the signicance of the Gri d comes from its ambi-
tion to extend distributed computing and storage to a global scale.In fact,every
technological revolution conceals a great deal of evolution!
What is Grid
The Grid is a service for sharing computer power and data storage capacity in a
geographically distributed way.Like the web,the Grid is a service which runs on
Internet.Unlike the web,there is no uniform standard or protocol for the Grid
today:there are many Grids for applications with different kinds of computing
Some Grids link resources at a local or national scale.Some Scientic Grids link
together dozens of major computing centers on several countries,even continents.
Projects such as the EU co-funded
(Enabling Grids for E-sciencE) and
(Distributed European Infrastructure for Supercomputing Applications)
are establishing general-purpose Grid infrastructure for science and industrial re-
search applications.DEISA links super-computers while EGEE is devoted to ac-
cess and analyze large amount of data by thousands of scientists for the larger part
fromthe High Energy Physics eld.
How to access the EGEE Grid?
• A
personal certicate
asked to the certicate authority of your country is
needed to become an EGEE member.

Registration in a Virtual Organization
(VO) i.e.belonging to an identi-
ed community,recognized by EGEE.
For Earth Science,two VOs:

(Earth Science Research):50 members on average from aca-
demic communities and organizations of 10 countries (monique.

(Expanding GEOscience On DEmand):30 members (∼12
fromthe academy).Mainly dedicated to the use of the Geocluster soft-
ware,developed by the Compagnie Générale de Géophysique (CGG-
Veritas,France) (
• An account on an EGEE
User Interface
Data in EGEE
• Data les:stored on Storage Elements on EGEE.Listed on the EGEE
catalogs to locate them when required,or attached to the job in the input
• (Meta)Databases:accessed through Amga if inside the Grid infrastruc-
ture,accessed with OGSA-DAI authentication if outside.
• Volume:millions of les,only limited by availability of storage spac e and
network rates.
• Formats:all accepted.
• Data sharing and exchange:a given set of data belonging to a VO is
accessible only to the members of this VO(or a subset of it).The data can
be encrypted,if needed.
DEGREE:Dissemination and Exploitation of GRids in Earth sciencE
SSA IST 2005-034619
Strategic objectives
• Disseminate and promote uptake of Grid in wider ES community.
• Bridge the ES and Grid communities throughout Europe
 to ensure that ES requirements are satised in next Grid gene ration,
 to ensure the integration of emerging technologies for manag ing
ES knowledge.
How does the grid work?
The essential component is the middleware,which is a software that allows the
user to access remote data and processing power in a simple,reliable and efcient
way.The physical infrastructure consists of clusters of PCs,supercomputers,
tapes and disk storage systems,as well as the network that links themtogether.
Some Earth Science
August 2007
Gome/ERS2:Ozone-7 years
Production of ozone proles through the
means of a a Neural Network algorithm
(2 versions) and a physical inversion al-
Validation with ground-based lidar.
Grid characteristics:
• large number of les ( ∼80000),
• metadata base with geospatial
queries for collocation satellite-
• OGSA-DAI server for the database,
• complex algorithms,
• sharing raw and elaborated data.
Two publications in Journal of Quan-
titative Spectroscopy and Radiative
Data:seismograms fromGeoscope net-
Computation:Green function for each
3D-Grid point around the approximate
earthquake location and for different
Results:Location of the space-time
barycenter of the rupture,the seismic
energy released,the source duration,
and the global mechanismof the source.
Grid characteristics:
• many simultaneous independent
jobs (50-100),
• greatly improved response time (<6
hours vs 1 week).
2006:21/24 earthquakes analyzed,
results published on Geoscope web
site http://geoscope.ipgp.
CGG-Veritas (FR)
Seismic platform software (∼400
modules) developed by CGG for
Academy and Industry.
Available in EGEE for Academic
More resources available:possibility to
use it on a larger scale.
Last version of the software,no need to
implement it.
Grid characteristics:
• license server,
• large storage space,
• large network bandwidth (between
sites and internal network),
• processing intensive:batch,MPI,
• fault tolerance system for central
server (LFC,GGS,VOMS),
• interactive access.
Codesa - 3D
CRS4 (IT),Unine (CH),INAT (TU)
Intrusion of seawater into coastal
Results:probabilistic maps of sea-
water intrusion in coastal aquifers of
the Mediterranean basin,using Monte
Carlo simulations,and according to dif-
ferent scenarios for sustainable water re-
sources management.
Grid characteristics:
• large dataset volume,
• MPI,
• long running jobs,
• virtual data model,
• monitoring needs,
• collaborative environment,
• use of licensed software (not yet on
the grid),

Formation and evolution of landscapes
using a discrete model of transport.
Model:a 3D cellular automaton (CA)
in which different sets of next-neighbor
interactions allow to distinguish between
different types of physical processes (e.g.
erosion,deposition,transport).Such an
innovation is necessary to implement
retroaction mechanisms between a topog-
raphy and a ow.
Grid characteristics:
• parametrical studies,
• CPU and memory intensive.
This numerical tool uses the spectral ele-
ment method to model 3D seismic waves
propagation in complex geological media,
on a local scale (sedimentary basin,to-
pography).Its ability to handle unstruc-
tured meshes allows to take into account
complicated geometries (surfaces topog-
raphy,interfaces) and to adapt wave-
lengths resolution in heterogeneous me-
dia conditions.
Used to study the Caracas basin.
Grid characteristics:
• intensive processing with MPI/f90,
• to be ported on EELA.
Physical models of uid dynamics,struc-
tural mechanics,electromagnetics,heat
transfer and acoustics,for example.
These are described by partial differential
equations which Elmer solves with the Fi-
nite Element Method (FEM).
Grid characteristics:
• MPI,
• CPU and memory intensive.
Other Applications

Mars Atmosphere simulation
(F.Cipriani;CETP,FR):very intensive Monte-Carlo procedures on density vs altitude pro-
• The
Climate applications
(DKRZ,MPI,DE):Climate model output analysis on EGEE.For this purpose a metadata and
data management structure has been developed and deployed to make existing data searchable,accessible and processable
on EGEE.(

Stratospheric polar ozone
(IPSL,FR):10-years worth of climatologic data processed through meteorological and chemical
models (

Large-scale air pollution model
(BAS,BG;NERI,DK):Implementation on EGEE of the sequential version of the Danish
Eulerian Model (DEM) with mediumgrid spatial discretization.(Tzvetan

Interface with the Geoscope server
(IPGP,FR):re-analysis of 25 years worth of seismological data (stutz@ipgp.

(Geophysical Lab.,Univ.Thessaloniki,GR):numerical simulations in the broader area of Thessaloniki,Greece.

(GCRAS,RU):data mining on large sets of meteorological outputs (Mikhail
Flood Forecasting
of a Danube river
Data:Meteorological boundary con-
ditions,river network,numerical eld
Meteorology:ALADIN (MPI-parallel),
MM5 (MPI-parallel).
Hydrology:HSPF (sequential-para-
metric),NLC (sequential-parametric).
Hydraulic:DaveF (MPI-parallel),
FESWMS (MPI-parallel).
Output:weather forecasting,precip-
itation forecasting,hydrograph,water
level and velocity of ooding area.
Grid characteristics:
• complex workow,
• MPI,
• knowledge management.
Application to be adapted to French
and Ukrainian rivers.
Monique Petitdidier
David Weissenbach