egee a large-scale production grid infrastructure

EGEE – A large-scale production Grid infrastructureErwin Laure
EGEE-II INFSO-RI-031688
Distributed parallel computing
Increased storage provision
Interconnection of arbitrary resources
Corresponding security
CoreGrid Definition
GGF Definition
Defining the Grid
A Grid is the combination of networked resources and the corresponding middleware, which provides services for the user.
This interconnection of users, resources, and services for jointly addressing dedicated tasks is called a virtual organization.
Comparison between Grids and Networks:
Networks realize message exchange between endpoints
Grids realize services for the users higher level of abstraction
EGEE - A Large-scale Production Grid Infrastructure
Unter einem Grid versteht man die Gesamtheit von vernetzten Ressourcen (z.B. Rechner, Instrumente, Sensoren, ...) sowie die darauf bereitgestellte Vermittlungsschicht (Grid Middleware), die für Anwender als Grid Dienste zur Verfügung stehen. Dieser Zusammenschluss von Benutzern, Ressourcen und Diensten zur gemeinsamen Bewältigung einer Aufgabe wird als virtuelle Organisation bezeichnet. Im Unterschied zum Internet, wo prinzipiell Nachrichten zwischen zwei Punkten ausgetauscht werden, realisiert ein Grid somit eine höhere Abstraktionsstufe, durch die der Benutzer Dienstleistungen (in Form von Grid Services) in Anspruch nehmen kann. Die Dienstleistungen werden von der Vermittlungsschicht weitgehend automatisch durchgeführt, wobei zwischen der Basis-Grid-Middleware - mit möglichst allgemein gültigen Diensten - und höheren Grid Diensten - mit entsprechender Spezialisierung auf bestimmte Dienstleistungen - unterschieden wird.
of networked resources and the corresponding middleware, which provides services for the user.
The EGEE Project
Aim of EGEE:
“to establish a seamless European Grid infrastructure for the support of the European Research Area (ERA)”
EGEE
71 partners in 27 countries, federated in regional Grids
EGEE-II
Expanded consortium
91 partners
Challenge: large consortium needs clearly defined management structure and reporting lines
tested in EGEE, expanded in EGEE-II
maintain expertise from EGEE partners
EGEE-II
focus on providing a service to users and less on building up the infrastructure
increased work with industry: now also direct input in technical management on same level as scientific applications
Involvement of industry also in the technical work – as EGEE business associates or through collaboration with the CERN openlab project (www.cern.ch/openlab)
SA = Service Activities: operation and management of the Grid as well as provision of network resources working, sustainable infrastructure: EGEE-II as core service provider
new sites/countries joining the infrastructure
new activity (SA3) responsible for software integration and testing
NA = Networking Activities: management and coordination of all the communication aspects of the project, application support Growth of infrastructure user base + international collaboration
increased support for applications
reinforced dissemination and training: closer links to industry; extend coverage to all regions
JRA = Joint Research Activities: Re-engineering and integration of Grid middleware components Middleware becoming more mature, needs less development
also includes quality assurance for the whole project and security
New coordination bodies:
Technical Coordination Group
User Information Group
EGEE-II website: www.eu-egee.org
EGEE Infrastructure
~ 25 000 CPUs
> 10 PB storage
> 60 Virtual Organizations
At Feb review:
6 domains and
Scaling up the infrastructure with resource centres around the globe
Stable, well-supported infrastructure, running only well-tested and reliable middleware
Pre-production service
Run in parallel with the production service (restricted nr of sites)
First deployment of new versions of the gLite middleware
Test-bed for applications and other external functionality
T-Infrastructure (Training&Education)
and application (Testbed, CA,
Regional Operation Centers
Tools are developed/hosted at different sites:
GOC DB (RAL), SFT (CERN), GStat (Taipei), CIC Portal (Lyon)
Grid operator on duty
CERN, IN2P3, INFN, UK/I, Ru,Taipei
Crucial in improving site stability and management
Expanding to all ROCs in EGEE-II
Operations coordination
Nov 04, May 05, Sep 05, June 06
Procedures described in Operations Manual
Introducing new sites
Site downtime scheduling
Suspending a site
Escalation procedures; etc.
Evolving and maturing procedures
Procedures being in introduced into and shared with the related infrastructure projects
Strict software process
Software configuration management, version control, defect tracking, automatic build system, …
Conservative approach in what software to use
Avoid “cutting-edge” software
Deployment on over 100 sites cannot assume a homogenous environment – middleware needs to work with many underlying software flavors
Avoid evolving standards
Evolving standards change quickly (and sometime significantly cf. OGSI vs. WSRF) – impossible to keep pace on > 100 sites
Long (and tedious) path
from prototypes to production
EGEE generic middleware
March 4, 2006:
After gLite 3.0:
As needed by users and as made available by developers
Major releases provide a “check-point”
In general in coincidence with major application challenges
Continuing development to
Improve functionality
Increase robustness
Increase usability
Grid Interoperability
Incubator for new Grid
Strengthening contacts with industry
Platform
Infrastructure
Unix
Windows
JVM
TCP/IP
MPI
Platform
Infrastructure
Unix
Windows
JVM
TCP/IP
MPI
Middleware structure
Higher-Level Grid Services may or may not be used by the applications
should help them but not be mandatory
Foundation Grid Middleware is deployed on the infrastructure
should not assume the use of Higher-Level Grid Services
must be complete and robust
should allow interoperation with other major grid infrastructures
Job submission
Information System
SA1 Pre-Production
Scalability Tests
Pre-Production Deployment
EGEE Applications
>20 applications
Applications now moving from testing to routine and daily usage
At Feb review:
6 domains and
2185
2796
7617
10312
11151
9096.5
8629.7419354839
10924.6774193548
10717.4
18084.8709677419
23259.5333333333
22880.8709677419
29417.4516129032
32331.6428571429
30691.8064516129
26448.3
Sheet1
Normalised CPU time [units 1K.SI2K.Hours] by VO and DATE (Excluded dteam VO)
VO
Jun-05
Jul-05
Aug-05
Sep-05
Oct-05
Nov-05
Dec-05
Jan-06
Feb-06
Mar-06
Apr-06
May-06
Total
Jobs / day
CSV Dump from Grid Operations Centre accounting portal for the period 06/2005 to 05/2006
Values shown are Total number of jobs run
(Units are Number of physical jobs per site per VO per month)
Jun-05
Jul-05
Aug-05
Sep-05
Oct-05
Nov-05
Dec-05
Jan-06
Feb-06
Mar-06
Apr-06
May-06
20053
2
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1527
1774
517
alice
9999
2577
169
2226
18339
19716
9227
24557
12113
2086
40856
3982
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0
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7147
1974
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4301
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atlas
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136118
119347
91664
200932
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209226
378028
436221
518646
357668
48836
atlasgrid
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1852
679
2584
2269
5204
1654
4956
696
155
202
3
atlaslcl
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0
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1
1
13
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5
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atlassgm
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59
22
12
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536
1991
176
auvergrid
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23
44
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9540
856
92
biomath
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253
1809
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biomed
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22509
42154
15169
32592
24331
6556
biomedsgm
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0
0
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0
9
11
0
bmed
2308
2932
1711
571
530
330
733
889
576
1349
1379
170
calice
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11
2
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cdf
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714
1028
698
1633
2637
1693
5566
1840
232
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18
4
27
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37
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241
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437
473
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cms
68614
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31827
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152142
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121852
144785
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148459
135239
11056
cmsgrid
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1071
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534
960
1830
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31
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cosmo
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11034
2048
d0
7
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3584
2250
775
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dcms
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909
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enea
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13
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esr
918
305
355
2541
1451
1810
567
1001
563
532
283
128
eumed
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fusion
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gamess
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geant
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3
2852
229
1041
4
362
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geant4
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401
2570
1169
1041
5
6
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geantsgm
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776
3041
358
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gear
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4
33
338
gearsgm
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gene
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131
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gridtest
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2252
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gvmuam
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h1
388
1236
1322
702
307
411
295
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11
154
5
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hera1
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herab
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hgdemo
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hone
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816
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336
2514
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1973
1297
751
39
28
hungrid
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32
2
1
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icecube
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1554
559
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443
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7
59
174
368
410
191
ilc
20
140
5637
2116
1089
676
1097
348
1833
2571
1884
165
ilcgrid
10
24
233
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62
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35
41
2
ildg
2
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4
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25
103
55
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inaf
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2
80
2
705
37
1
1
146
1
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infngrid
18
209
574
2178
2156
1446
677
521
3301
5121
1741
3
inforet
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2
3
5
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ingv
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1212
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instruments ever built to
Mont Blanc
(4810 m)
Downtown Geneva
The accelerator generates 40 million particle collisions (events) every second at the centre of each of the four experiments’ detectors
The LHC Accelerator
LHC DATA
This is reduced by online computers that filter out a few hundred “good” events per sec.
Which are recorded on disk and magnetic tape
at 100-1,000 MegaBytes/sec ~15 PetaBytes per year
for all four experiments
event filter
grid infrastructures ….
Example: HEP
Preparing for LHC start-up
Emphasis on providing a service
Computing needs of experiments
E.g. LHCb: ~700 CPU years in 2005 on the EGEE infrastructure
E.g. ATLAS: over 10,000 jobs per day
ATLAS
LHCb
ATLAS
LHC = Large Hadron Collider http://lhc.web.cern.ch/lhc/
The Large Hadron Collider (LHC) is being built in a circular tunnel 27 km in circumference, 50 to 175 m underground, at CERN near Geneva, Switzerland.
It is designed to collide two counter rotating beams of protons or heavy ions. Proton-proton collisions are foreseen at an energy of 7 TeV per beam with a planned start-up in 2007.
The beams will be stored at high energy for hours. During this time collisions take place inside the four main LHC experiments.
LHC Experiments:
ALICE http://aliceinfo.cern.ch/
Dedicated heavy-ion detector to exploit the unique physics potential of nucleus-nucleus interactions at LHC energies. ALICE will study the physics of strongly interacting matter at extreme energy densities, where the formation of a new phase of matter, the quark-gluon plasma, is expected.
ATLAS http://atlas.web.cern.ch/Atlas/index.html
ATLAS will explore the fundamental nature of matter and the basic forces that shape the universe in the particle collisions of the LHC. The debris of the collisions reveal fundamental particle processes. The energy density in these high energy collisions is similar to the particle collision energy in the early universe less than a billionth of a second after the Big Bang.
CMS http://cmsinfo.cern.ch/outreach/
The CMS magnet will be the largest solenoid ever built, providing a magnetic field of 4 Tesla, to detect muons (elementary particles). CMS will explore physics at the TeV scale, try do discover the Higgs boson, look for evidence of supersymmetry, and be able to study aspects of heavy ion collisions.
LHCb http://lhcb-public.web.cern.ch/lhcb-public/
LHCb will obtain precise measurements of CP violation – to understand why there is more matter than antimatter in the universe.
LHC Service Challenges: http://lcg.web.cern.ch/LCG/PEB/Planning/deployment/Grid%20Deployment%20Schedule.htm
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Sheet1
Emerging diseases know no frontiers. Time is a critical factor
Avian influenza:
human casualties
Early detection
Epidemiological watch
WISDOM focuses on drug discovery for neglected and emerging diseases.
Summer 2005: World-wide In Silico Docking On Malaria
46 million ligands docked in 6 weeks
~1 million virtual ligands selected
1TB of data produced
Spring 2006: drug design against H5N1 neuraminidase involved in virus propagation
impact of selected point mutations on the efficiency of existing drugs
identification of new potential drugs acting on mutated N1
N1
H5
300,000 Chemical compounds:
Data challenge on EGEE,
In vitro
Example: Pharmacokinetis
A lesion is detected in an MRI study of a patient
– start with virtual biopsy
The process requires obtaining
breath-holds.
Before analyzing the variation of each voxel, images must be co-registered to minimize deformation due to different breath holds.
The total computational cost of a clinical trial of 20 patients is around 100 CPU days.
Example: Determining
earthquake mechanisms
magnitude, mechanism
10 times faster on the Grid than on local computers
Results
Different location (different part of fault line further south)
Different mechanism
Peru, June 23, 2001
Permanent or
periodically updated
ITU-BR developed a system for RRC 2006
Run compatibility and
Provide more CPU power
Gain experience on how to access
large and reliable computing resources
‘on demand’
EGEE used a subset of its Grid for RRC 2006
Over 400 PCs
Compatibility analysis < 1h
Dissemination and outreach
Training and education
Increasing the number of applications by improving application support and middleware functionality
Improved usability through high level grid middleware extensions
Increasing the grid infrastructure
summer schools across many countries
>3000 people trained
Material archive online with ~250 presentations
Public and technical websites
4 conferences organized (~ 460 @ Pisa)
Next conference: September 2006 in Geneva ~600 participants
Links related industry projects (NESSI, BEinGRID, …)
Works with EGEE’s Technical Coordination Group
Collaboration with CERN openlab project
IT industry partnerships for hardware and software
development
Industry Forum
Organises industry events and disseminates grid information
e.g. this Wednesday here at the school
Platform
Infrastructure
Unix
Windows
JVM
TCP/IP
MPI
Example: Biomedicine
Parallel simulation
Scientific Visualization
Sony PSP – PlayStation Portable
Not only portals
Portals are a good way to bring computing power to end-users
In most cases domain specific
Application programmers (and portal programmers) need more powerful interfaces
Workflow engines
Programming environments (gEclipse)
Related Infrastructures
Maintain Europe’s leading position in global science Grids
Ensure a reliable and adaptive support for all sciences
Independent of project funding cycles
Modelled on success of GÉANT
Infrastructure managed centrally in collaboration
with national bodies (in EGEE-II: JRUs)
Expand the idea and problems of the JRU
Sample of National Grid projects:
Austrian Grid Initiative
OMII; GridPP
Average of 180 M€ per year since 2002 (national + EC)
Grids represent a powerful new tool for science
Today we have a window of opportunity to move grids from research prototypes to permanent production systems (as networks did a few years ago)
EGEE offers …
… a mechanism for linking together people, resources and data of many scientific community
… a basic set of middleware for gridfying applications with documentation, training and support
… regular forums for linking with grid experts, other communities and industry
Summary
Success will lead to the adoption of grids as the main computing infrastructure for science
If we succeed then the potential return to international scientific communities will be enormous and open the path for commercial and industrial applications
Demos
25-29 September 2006
Data sources
Hydrological simulation
Hydraulic simulation

egee a large-scale production grid infrastructure

Documents