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Transcript of 14.09.2006. 2 GridKA School 2006, H. Enke, AIP 14.09.2006 Overview AstroGrid-D History Project ...
14.09.2006
2GridKA School 2006, H. Enke, AIP14.09.2006
OverviewOverview
AstroGrid-D AstroGrid-D HistoryHistory Project StructureProject Structure GoalsGoals
Current statusCurrent status ArchitectureArchitecture Resource IntegrationResource Integration Services:Services:
• Information Service (MetaData Management)Information Service (MetaData Management)• Database and DataStreams ManagementDatabase and DataStreams Management
Selected UseCasesSelected UseCases• DynamoDynamo• NBody6++NBody6++
GATGAT ChallengesChallenges
• LOFAR / GlowGridLOFAR / GlowGrid• Robotic Telescopes GridRobotic Telescopes Grid
AstroGrid-D and GAVOAstroGrid-D and GAVO
3GridKA School 2006, H. Enke, AIP14.09.2006
History: About Cactus
Cactus and its ancestor codes have been using Grid infrastructure since 1993
Support for Grid computing was part of the design requirements for Cactus 4.0 (experiences with Cactus 3)
Cactus compiles “out-of-the-box” with
Globus
[using globus device of MPICH-G(2)] Design of Cactus means that applications are
unaware of the underlying machine/s that the simulation is running on … applications become trivially Grid-enabled
Infrastructure thorns (I/O, driver layers) can
be enhanced to make most effective use of the underlying Grid architecture T.RadkeT.Radke
4GridKA School 2006, H. Enke, AIP14.09.2006
History : Simulation
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benötigt.
Numerical relativity: AEItangential collision of two black holes
Numerical relativity: AEItangential collision of two black holes
SC99 Colliding Black Holes
using Garching, ZIB T3E’s, with remote collaborative interaction and visualisation at ANL and NCSA booths
2000 Single simulation
LANL, NCSA, NERSC, SDSC, ZIB, Garching, …
SC99 Colliding Black Holes
using Garching, ZIB T3E’s, with remote collaborative interaction and visualisation at ANL and NCSA booths
2000 Single simulation
LANL, NCSA, NERSC, SDSC, ZIB, Garching, …
5GridKA School 2006, H. Enke, AIP14.09.2006
Galaxy Merger
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benötigt.
6GridKA School 2006, H. Enke, AIP14.09.2006
Consortium AIP (Lead) AEI ZIB
ZAH
MPA MPE TUM
AstroGrid-D Consortium
Heidelberg
Potsdam/Berlin
Garching
Associated Partners
UP
MPIAMPIfR
LRZRZGUSM
FZK
7GridKA School 2006, H. Enke, AIP14.09.2006
AstroGrid-D Work packages
Integration of compute and data resources
Managing and providing metadata Distributed management of data (files) Distributed query of data bases and
management of data streams Supervision and interactive management
of grid jobs User and application programmer
interfaces
8GridKA School 2006, H. Enke, AIP14.09.2006
Resource Integration
Building Grid Infrastructure: Unified configurations based on GTK 4.x Compiled, no binary installation required for MPI
(mpichG2) Each resource acknowledges GermanGrid and
GridGerman Root CA (D-Grid StA recommendation) VOMRS, registration of access to resources Each institute has a Registration Authority Development of translation from MDS information to
AstroGrid-D Information Service for Job-Submisson, Brokering, VO Management
Globus MDS is enhanced by Ganglia Firewall configuration according to D-Grid-StA
recommendation
9GridKA School 2006, H. Enke, AIP14.09.2006
Certification / RA / Usermanagement
Certification / RA RA:
• MPA/MPE: RA via RZG (DFN)• TUM: -> (DFN)• AIP : RA established (GridKA)• AEI : RA established (GridKA)• ZIB : RA established (DFN)• ZAH: RA established (GridKA)
Usermanagement• Adopted the gridpool approach (gLite)
Grid-users are created in pools, allowing of an easy mapping for VO to (unix) groups, for accounting and tuning of local resource access policies
10GridKA School 2006, H. Enke, AIP14.09.2006
VO Management
Virtual Organisations D-Grid management tool (VOMS) is only available with a nearly
fully fledged gLite-Installation• Most Communites base their Grid environment on Globus
VOMRS is derived from VOMS, but is easily compatible with GTK
Benefits of VORMS: • Frontend: Java-webapp with https, uses certificates• Enhanced facilities for VO-Group and User-Management, extensible
to registering resources and their policies• SOAP clients builtin• Backend for customized queries of the database
AstroGrid-D has a grid-map merge procedure allowing to fine tune the grid-maps for local resource providers
11GridKA School 2006, H. Enke, AIP14.09.2006
Architecture: Overview
12GridKA School 2006, H. Enke, AIP14.09.2006
AstroGrid-D Metadata
Resources (computational, storage, robotic telescopes, instruments, network, software) Well-defined schemes
GLUE schema (computational, storage, software)
RTML (robotic telescopes) State of grid services
(jobs, files, data stream, ...)
13GridKA School 2006, H. Enke, AIP14.09.2006
Metadata (cont.)
Scientific metadata (domain-specific description of data sets, provenance)
Application-specific metadata (job history, job progress, ...)
Schemes will be decided later by the community
14GridKA School 2006, H. Enke, AIP14.09.2006
Requirements
Extensible/flexible schemes Easy to extract and export metadata Protect from unauthorized access Support exact match and range queries Handle different metadata characteristics
15GridKA School 2006, H. Enke, AIP14.09.2006
Approach
Metadata representation with RDF An RDF entry is a (subject, predicate, object)-
tuple A set of triples/statements form a graph
Metadata access via SPARQL Query language for RDF Graph pattern matching
Simple interface including add, update, remove and query
16GridKA School 2006, H. Enke, AIP14.09.2006
RDF Example
“Maria”
Photographer“A picture of the Eiffel tower has a photographer with value Maria”
17GridKA School 2006, H. Enke, AIP14.09.2006
RDF Example
“Maria has a phone number with value 555-444”
“Maria”
555-444
“Maria”
Photographer“A picture of the Eiffel tower has a photographer named Maria”“A picture of the Eiffel tower has a photographer with value Maria”
Phone number
18GridKA School 2006, H. Enke, AIP14.09.2006
RDF Example
“Maria has a phone number withvalue 555-444”
“Maria”
555-444
“A picture of the Eiffel tower hascreation-date with value 2003.06.05”
Photographer
“Maria”
555-4442003.06.05
Creation-date
“Maria”
Photographer“A picture of the Eiffel tower has a photographer named Maria”
Phone number
“A picture of the Eiffel tower has a photographer with value Maria”
Phone number
19GridKA School 2006, H. Enke, AIP14.09.2006
SPARQL Example
Photographer
“Maria”
555-444
“Get the name and phone number of the photographer who took the picture of the Eiffel tower” Phone number
SELECT ?name, ?number WHERE{“Picture of Eiffel tower” “Photographer” ?name . ?name “Phone number” ?number }
Number Name
555-444 Maria
2003.06.05
Creation-date
Input graph
Output results
20GridKA School 2006, H. Enke, AIP14.09.2006
Information Service (Architecture overview)
21GridKA School 2006, H. Enke, AIP14.09.2006
Storage interface
Add(String RDF, String context) Update(String RDF, String context)
Overwrite matching statements Remove([statements], String context)
Delete existing metadata part of the information service storage
Query(String sparql_query) Extract metadata from the information service or
RDF information producers
22GridKA School 2006, H. Enke, AIP14.09.2006
Demo: Overview
Idea: use Google's map API to present grid resources using RDF metadata provided by the information services
Tools MDS4 WebMDS produces an XML representation
of resource information Template language or XSLT for translating to RDF RDF store Web service interface to add and query the RDF
store
23GridKA School 2006, H. Enke, AIP14.09.2006
Demo: Component interaction
24GridKA School 2006, H. Enke, AIP14.09.2006
Demo: SPARQL queries
SELECT ?site, ?lat, ?long WHERE{?site rdf:type “Site” . OPTIONAL {?site geo:lat ?lat . ?site geo:long ?long }}
“Get all sites and their longitude and latitudeif available”
“Get all computing elements from site S”
SELECT ?ce WHERE {S “ComputeElement” ?ce}
25GridKA School 2006, H. Enke, AIP14.09.2006
Demo: RDF graph (example)
10.25
<SiteID>
<ClusterID>
<ComputeElementID>
51.30
default 2
48
#Running jobs
#FreeCPUsName#CPUs
Cluster Long
Lat
ComputeElement
26GridKA School 2006, H. Enke, AIP14.09.2006
DataStream Management
27GridKA School 2006, H. Enke, AIP14.09.2006
DataStream Management
28GridKA School 2006, H. Enke, AIP14.09.2006
Job Management (Architecture)
29GridKA School 2006, H. Enke, AIP14.09.2006
UseCase Dynamo
Modelling the turbulent dynamo in planets, stars and galaxies
(solving the induction equation with turbulent electromotive force)
Moderate Requirements:• some MB to few GB main memory and <= 10 GB of local disk space• Runtime: hours to days, Fortran90 code / compilers• Handling of plain files only• Concurrent start of multiple simulations with different input parameters
30GridKA School 2006, H. Enke, AIP14.09.2006
Preparation of Taskfarming
• One directory for each model (parameter sets) containing input parameter files and the executable or code and Makefile
• Job Description (Globus XML file for multijobs) • data location (input)• FQDN names of compute resources• data location (output)
31GridKA School 2006, H. Enke, AIP14.09.2006
Multi-Job XML
..........
32GridKA School 2006, H. Enke, AIP14.09.2006
Start Taskfarming
Single sign-on to grid$>grid-proxy-init
Submit Multi-Job$>globusrun-ws –submit -b –f job.xml \
–J –S –o epr.xml
Status requests & monitoring:$>globusrun-ws –status –j epr.xml
globusrun-ws –monitor –s –j epr.xml
33GridKA School 2006, H. Enke, AIP14.09.2006
Multi-Job Flowchart
Use
rG
rid
Res
ou
rce
Gri
d R
eso
urc
eG
rid
Res
ou
rce
Gri
d R
eso
urc
e
grid-proxy-
init
SubmitMulti-Job
XML
Multi-Job Description
Accept Multi-Job
Multi-Job Description
Dele-gate 1. Job
Dele-gate
N. Job
Accept singleJob
Accept singleJob
FileStage-In
Single-Job Descriptions
ExecuteTask
FileStage-
Out
InputData
1
Task
DeliverData &Task
Re
que
st F
iles
InputData
1 Task
Sen
d F
iles
OutputData
1
CleanUp
SaveOutputData
Sen
d O
utp
ut F
iles
OutputData
1
FileStage-In
ExecuteTask
FileStage-
Out
InputData
N
Task
OutputData
N
CleanUp
DeliverData &Task
SaveOutputData
OutputData
N
InputData
N
XML
HandleStatus
Info
ProvideMonitoring
Data
Job EPR
Job EPR
RequestJob
Status
RequestJob
Monitoring
34GridKA School 2006, H. Enke, AIP14.09.2006
JDSL and RSL
Why consider another Job Description Language ? Globus RSL, which is processed by GRAM,
lacks some features, which are required for a detailed description of many jobs
Simulations require often the compilation before the actual job is run
Datamining, where the first stage of the job has to acquire the actual data to operate on from remote archives/databases
Defining workflows is next to impossible
35GridKA School 2006, H. Enke, AIP14.09.2006
JDSL and RSL
JDSL is developped by a GGF working group AstroGrid-D started to develop a JSDL to RSL
translator to meet the requirements of our usecases
Commandline Interface
takes XML-file as inputproduces RSL-file for globus-run command
$>jsdlproc jsdl-examples/nbody6.jsdl > temp.rsl &&\globusrun-ws -submit -staging-delegate -job-description-file temp.rsl -F < globushost >
36GridKA School 2006, H. Enke, AIP14.09.2006
JDSL and RSL
37GridKA School 2006, H. Enke, AIP14.09.2006
JDSL and RSL
38GridKA School 2006, H. Enke, AIP14.09.2006
GAT (Grid Application Toolkit)
•GAT is not a new grid middleware
GAT enables an easy access to different grid infrastructures
• GRAM• Condor• Unicore• GridFTP• ...
GAT is an OpenSource project
•GAT is a framework to enable an uniform access to different grid middleware
39GridKA School 2006, H. Enke, AIP14.09.2006
GAT (Grid Application Toolkit)
• Applications call the GAT-API for grid operations Applications have to be linked against the GAT
• Applications are independend of the underlying grid infrastructure
GAT Engine loads available adaptors at runtime During a calls of the GAT-API the GAT engine decides, which adaptor performs the grid operation In error case during a „grid operation“, another adaptor will be accessed
• default adaptors offer local operations grid applications can be compiled, linked and tested without available grid services The same application can run in a „complete grid environment“: without a new build
40GridKA School 2006, H. Enke, AIP14.09.2006
•The GAT-API doesn‘t change. Changes e.g. in Globus job submit are included in the GAT Globus adaptor
•GAT offers reliability. If one grid service is not available, another grid service is used
•GAT is much eaysier to install than Globus
•GAT has now a Java-API, allowing for pure client-installations in combination with JAVA-COG (AstroGrid-D development)
•GAT offers grid with a minimum effort for the end user
GAT (Grid Application Toolkit)
41GridKA School 2006, H. Enke, AIP14.09.2006
•GAT doesn‘t replace any function of a grid middleware
•Without an adaptor for a grid middleware GAT is useless for this middleware
•GAT has no resource broker
GAT (Grid Application Toolkit)
42GridKA School 2006, H. Enke, AIP14.09.2006
GAT Adapter
SGE
PBSGTK4
Globus 2/3.xUnicore
DRMAA
Application
Application layer
GAT API GAT Engine
GAT layer
User S
pace
„Grid
“ Sp
aceGAT (Grid Application Toolkit)
43GridKA School 2006, H. Enke, AIP14.09.2006
Robotic Telescope GridRobotic Telescope Grid
24h-observation, no reaction delay.
Independent of local weather.
Use GRID-technology in an uplifted abstraction layer for robotic telescopes
IVOA (VOEvent) and HTN (Heterogeneous Telescopes Network)
AIP Liverpool JMU U GöttingenT. GranzerT. Granzer
Hawaii
Australia
Texas
La Palma Tenerife
South Africa
PotsdamArizona
44GridKA School 2006, H. Enke, AIP14.09.2006
Robotic Telescopes
45GridKA School 2006, H. Enke, AIP14.09.2006
LOFAR / GlowGrid
GLOW: German LOng Wavelength Consortium represents the interests of the german
astronomy community in the LOFAR project AIP, MPA and MPIfR are members of GLOW Goals of GlowGrid:
Grid methods and infrastructure for radioastronomy community
Developing grid based methods for “real time” processing of antennae signals
Long term storage for LOFAR/GLOW data
46GridKA School 2006, H. Enke, AIP14.09.2006
LOFAR / GlowGrid
Partners: AIP, MPA, MPIfR, ZIB, FZJ, KIP TLS, RUB, ZAH, TUM
Volume 5 FTE x 3 years + hardware Project is placed as community project, but
AstroGrid-D will be managing the project and the workpackages are added to our current structure
47GridKA School 2006, H. Enke, AIP14.09.2006
LOFAR
25 50 75
BremenBremen
48GridKA School 2006, H. Enke, AIP14.09.2006
FrequencyCoverage
Sensitivity Improve-ment
Resolu-tionImprove-ment
Polarization Purity
Flexibility+ New features
LOFAR(2006-2015)
20-200 MHz ~100-1000 100-1000 > 30 dB Digital pointingfrequency agilityall-sky FOVtime buffering
SKA
(>2015)
0.1-20 GHz ~100 ~1 40 dB digital + mechanical pointingfrequency agilitylarge FOV
submm-VLBI 40-600 GHz ~10 ~10 > 20 dB
ALMA(2008-2020)
40-1000 GHz
~10-100 ~10 > 30 dB Fast mechanical pointing
frequency agility
LOFAR
49GridKA School 2006, H. Enke, AIP14.09.2006
LOFAR: Wide Area Sensor Network
50GridKA School 2006, H. Enke, AIP14.09.2006
LOFAR: Grid-Environment
51GridKA School 2006, H. Enke, AIP14.09.2006
LOFAR: Grid-Environment
Data Storage: Distributed storage of data-product in SDC Access of data from distributed collaborations
Post Processing: Central Processing Facility Distributed Computing Facilities (SDC,
collaborations)
Access to LOFAR User-Interface Access to scheduling & monitoring information Event registering & triggering
52GridKA School 2006, H. Enke, AIP14.09.2006
LOFAR: Science Operating / Data Centers
Data Product of LOFAR:e.g. 6 TB of raw visibility data for an 8 beam, 4 hour synthesis
observation, after integration for 1 sec and over 10kHz.
One month of observing in this mode results in ~1 PetaByte
Normally final data-products are exported (from CPF) Archiving and scientific use is the responsibility of the
SO/DC for routine observation Intermediate data products can be exported to SO/DC,
provided sufficient bandwidth (1 Gbit-Connection; a 1 Beam, 4h integration takes ~100min)
53GridKA School 2006, H. Enke, AIP14.09.2006
LOFAR / GlowGrid
54GridKA School 2006, H. Enke, AIP14.09.2006
GAVO: Context IVOA
GAVO (German Astrophysical Virtual Observatory)
is part of international efforts of the Astronomical und
Astrophysical Community, to
Achieve interoperability of observational data and simulation
data archives
Development of software and tools for Astronomy towards a
„multi-wave-length“ view of the Universe
Defining standards and protocols for enabling unified access to
VO-compliant data archives
55GridKA School 2006, H. Enke, AIP14.09.2006
GAVO/AstroGrid-D: Clusterfinder
Simultaneous search for X-Ray clusters of galaxies X-Ray photon maps (RASS) Optical galaxy maps (SDSS)
(P. Schuecker et al. MPE)
Clusterfinder: VO-ConeSearch Distributed Computing on AstroGrid-D Integration of Results
(H. Enke/P.Schuecker/A.Carlson)
(see link: Clusterfinder)
56GridKA School 2006, H. Enke, AIP14.09.2006
AstroGrid / GAVO: Clusterfinder
Web
serv
ice
GridQueue
GridJob-Runner
VO-Archive access
ClusterFinder.exe-1processor-100 MB memory-10 GB dataspace- resources (maps, psf)
14.09.2006
Current Simulation: MareNostrum
Current Simulation: MareNostrum
Zur Anzeige wird der QuickTime™ Dekompressor „“
benötigt.
A.KahlatlayanA.Kahlatlayan
58GridKA School 2006, H. Enke, AIP14.09.2006
AstroGrid-D and GAVO
GAVO developped a VO-compliant data base and
query interface for useful cosmological
information (Halos and other substructures)(SOAP and HTTP-interface)
(see link: Millennium)
AstroGrid-D will support the grid-based storage of astronomical archives Databases simulation archives
and access based on both grid and VO protocols
59GridKA School 2006, H. Enke, AIP14.09.2006
AstroGrid-D and GAVO
AstroGrid-D: Infrastructure Network Computing Resources Grid-Technologie
GAVO: Interoperability of astronomical archives Virtual Observatoy compatible
Software Tools Database-Interfaces User-Interfaces
60GridKA School 2006, H. Enke, AIP14.09.2006
Thanks for your attention
Visit our website
www.gac-grid.org
Thanks to all the contributors from AstroGrid-DThanks to all the contributors from AstroGrid-D
61GridKA School 2006, H. Enke, AIP14.09.2006
Links to AstroGrid-D and IVOA
AstroGrid-D: http://www.gac-grid.org (Project website) http://www.gac-grid.org/project-products.html (Help, WebMDS, Software) http://cashmere.aip.de:8080/gridsphere/gridsphere (Portal) http://cashmere.aip.de:8080/gridsphere/gridsphere?cid=astrogridmap
(Demo) https://vomrs.gac-grid.org (VOMRS only with a valid D-Grid-Certificate) http://jean-luc.aei.mpg.de/Press/BH1999/ (Simulations) http://www.aip.de/People/msteinmetz/Movies.html (Simulations) http://www.aip.de/~arm2arm/ (Simulations) http://www.mpa-garching.mpg.de/mpa/research/current_research/hl2004-
8/hl2004-8-en.html (Simulations)
GAVO: http://www.ivoa.org/ (IVOA, International Virtual Observatory Alliance) http://www.g-vo.org (GAVO website) http://www.g-vo.org/clusterfinder/ (Clusterfinder) http://www.g-vo.org/portal/tile/products/services/mpasims/index.jsp
(Millennium Simulation Database)