SlideShare une entreprise Scribd logo
1  sur  16
Télécharger pour lire hors ligne
CERN: Big Science Meets Big Data

            Dr Bob Jones
                CERN
         Bob.Jones <at> CERN.ch
CERN was founded 1954: 12 European States
Today: 20 Member States

~ 2300 staff
~ 790 other paid personnel
> 10000 users
Budget ~1000 MCHF annual




                        20 Member States: Austria, Belgium, Bulgaria,
                        the Czech Republic, Denmark, Finland, France, Germany,
                        Greece, Hungary, Italy, Netherlands, Norway, Poland,
                        Portugal, Slovakia, Spain, Sweden, Switzerland and
                        the United Kingdom
                        Candidates for Accession: Romania, Israel
                        Observers to Council: India, Japan,
                        the Russian Federation, the United States of America,
                         Bob Jones - December 2012                            2 2
                        Turkey, the European Commission and UNESCO
Accelerating Science and Innovation
     Bob Jones - December 2012        3
Data flow to permanent storage: 4-6 GB/sec




200-400 MB/sec
                                       1-2 GB/sec


                                                         1.25 GB/sec


                             1-2 GB/sec
                 Bob Jones - December 2012                             4
WLCG – what and why?
•   A distributed computing 
    infrastructure to provide the 
    production and analysis 
    environments for the LHC 
    experiments

•   Managed and operated by a 
    worldwide collaboration between 
    the experiments and the 
    participating computer centres

•   The resources are distributed – for 
    funding and sociological reasons

•   Our task was to make use of the            Tier-0 (CERN):                   Tier-2 (~130 centres):
    resources available to us – no              • Data recording                • Simulation
    matter where they are located               • Initial data reconstruction   • End-user analysis
                                                • Data distribution

                                               Tier-1 (11 centres):
•   Secure access via X509 certificates        •Permanent storage
    issued by network of national              •Re-processing
    authorities ‐ International Grid           •Analysis
    Trust Federation (IGTF)
     –   http://www.igtf.net/              Bob Jones ‐ December  2012                                    5
WLCG: Data Taking
•   Castor service at Tier 0 well adapted to     HI: ALICE data into Castor  > 4 GB/s (red)
    the load:
     – Heavy Ions: more than 6 GB/s to tape 
       (tests show that Castor can easily 
       support >12 GB/s); Actual limit  now 
       is network from experiment to CC
     – Major improvements in tape 
       efficiencies – tape writing at ~native     HI: Overall rates to tape > 6 GB/s (r+b)
       drive speeds. Fewer drives needed
     – ALICE had x3 compression for raw 
       data in HI runs




                                                        Accumulated Data 2012
                                                           0.1 0.2 0.8
                                                            0.0                    ALICE
                                                                             0.8
                                                                      1.3          AMS
                                                       0.9     1.2
                                                                                   ATLAS
                                                                                   CMS

                                                                            5.8    COMPASS
                                                            4.6
                                                                                   LHCB
       23 PB data written in 2011                                                  NA48
0
                                                                                                                                                          10000000
                                                                                                                                                                     20000000
                                                                                                                                                                                30000000
                                                                                                                                                                                                    40000000
                                                                                                                                                                                                                               50000000
                                                                                                                                                                                                                                          60000000


                                                                                                                                                Jan‐09

                                                                                                                                                Feb‐09

                                                                                                                                                Mar‐09

                                                                                                                                                Apr‐09

                                                                                                                                                May‐09

                                                                                                                                                Jun‐09                                             CMS
                                                                                                                                                                                                               LHCb



                                                                                                                                                                                ALICE
                                                                                                                                                 Jul‐09                                    ATLAS
                                                                                                                                                Aug‐09

                                                                                                                                                Sep‐09

                                                                                                                                                Oct‐09

                                                                                                                                                Nov‐09

                                                                                                                                                Dec‐09

                                                                                                                                                Jan‐10

                                                                                                                                                Feb‐10

                                                                                                                                                Mar‐10
                                                                                                                                                                                                               1.5M jobs/day




                                                                                                                                                Apr‐10

                                                                                                                                                May‐10

                                                                                                                                                Jun‐10
Ja                                                                                                                                               Jul‐10




                  100000000
                              200000000
                                          300000000
                                                      400000000
                                                                  500000000
                                                                              600000000
                                                                                           700000000
                                                                                                              800000000
                                                                                                                            900000000




              0
                                                                                                                                        1E+09
   n‐
      10
Fe                                                                                                                                              Aug‐10
   b‐
      10                                                                                                                                        Sep‐10
M
 ar
    ‐1                                                                                                                                          Oct‐10
       0
Ap                                                                                                                                              Nov‐10
   r‐1
      0                                                                                                                                         Dec‐10
M
 ay
    ‐1                                                                                                                                          Jan‐11
      0
 Ju                                                                                                                                             Feb‐11
                                                                                          CMS
                                                                                                       LHCb
      n‐



                                                                      ALICE
         10                                                                                                                                     Mar‐11
 Ju
    l‐1
                                                                              ATLAS                                                             Apr‐11
       0
Au                                                                                                                                              May‐11
   g‐
      10                                                                                                                                        Jun‐11
Se
      p‐                                                                                                                                         Jul‐11
         10
Oc                                                                                                                                              Aug‐11
   t‐ 1
       0                                                                                                                                        Sep‐11
No
   v‐
      10                                                                                                                                        Oct‐11

De                                                                                                                                              Nov‐11
   c‐
      10
                                                                                                                                                Dec‐11
Ja
   n‐
      11                                                                                                                                        Jan‐12

Fe
   b‐
      11
M
  ar
    ‐1
       1
Ap
   r‐1
       1
                                                                                                                                                                                                                                                     Overall use of WLCG




M
 ay
    ‐1
       1
Ju
     n‐
                                                                                                          109 HEPSPEC‐hours/month




        11
                                                                                                          (~150 k CPU continuous use)




 Ju
    l ‐1
        1
Au
   g‐
       11
                                                                                                                                                                                       ‐ # jobs/day




Se
                                                                                                                                                                                       ‐ CPU usage




      p‐
         11
Oc
   t‐ 1
       1
No
                                                                                                                                                                                       year technical stop




   v‐
      11
                                                                                                                                                                                       Usage continues to 




De
  c‐
     11
                                                                                                                                                                                       grow even over end of 
Broader Impact of the LHC 
     Computing Grid
• WLCG has been leveraged on both sides of 
  the Atlantic, to benefit the wider scientific 
  community
   – Europe (EC FP7):
       • Enabling Grids for E‐sciencE        Archeology
         (EGEE) 2004‐2010                    Astronomy
                                             Astrophysics
       • European Grid Infrastructure 
                                             Civil Protection
         (EGI)  2010‐‐                       Comp. Chemistry
   – USA (NSF):                              Earth Sciences
       • Open Science Grid (OSG)             Finance
                                             Fusion
         2006‐2012  (+ extension?)
                                             Geophysics
                                             High Energy
                                             Physics
• Many scientific applications              Life Sciences
                                             Multimedia
                                             Material Sciences
                Bob Jones ‐ December  2012                8
                                             …
How to evolve LHC data processing

Making what we have today more sustainable is a challenge
• Big Data issues
   – Data management and access
   – How to make reliable and fault tolerant systems
   – Data preservation and open access
• Need to adapt to changing technologies
   – Use of many‐core CPUs
   – Global filesystem‐like facilities
   – Virtualisation at all levels (including cloud computing services) 
• Network infrastructure
   – Has proved to be very reliable so invest in networks and make full 
      use of the distributed system

                             Bob Jones ‐ December  2012             9
CERN openlab in a nutshell


• A science – industry partnership to drive R&D
   and innovation with over a decade of success

• Evaluate state-of-the-art technologies in a
   challenging environment and improve them

• Test in a research environment today what will
   be used in many business sectors tomorrow

• Train next generation of engineers/employees
                                                       CONTRIBUTOR (2012)


• Disseminate results and outreach to new
   audiences

                          Bob Jones - December 2012                10
Virtuous Cycle
                                     CERN
                                  requirements
                                  push the limit

             Produce                                        Apply new
            advanced                                       techniques
          products and                                        and
             services                                     technologies




                       Test                            Joint
                  prototypes in                    development
                      CERN                           in rapid
                  environment                         cycles



A public-private partnership between the research community and industry
                          http://openlab.cern.ch
                         Bob Jones - December 2012                         11
Bob Jones - December 2012   12
A European Cloud Computing Partnership: 
big science teams up with big business




                                                                                      To create an Earth 
                                     To support the           Setting up a new 
  Strategic Plan                   computing capacity        service to simplify 
                                                                                     Observation platform, 
                                                                                          focusing on 
                                   needs for the ATLAS        analysis of large 
   Establish multi‐tenant,           experiment          genomes, for a deeper 
                                                                                        earthquake and 
    multi‐provider cloud                                                               volcano research
                                                           insight into evolution 
    infrastructure                                            and biodiversity
   Identify and adopt policies 
    for trust, security and 
    privacy

   Create governance 
    structure

   Define funding schemes




        Email:contact@helix-nebula.eu Twitter: HelixNebulaSC Web: www.helix-nebula.eu                     13
Initial flagship use cases
  ATLAS High Energy            Genomic Assembly           SuperSites Exploitation
  Physics Cloud Use               in the Cloud                  Platform




To support the computing     A new service to simplify    To create an Earth
capacity needs for the       large scale genome           Observation platform,
ATLAS experiment             analysis; for a deeper       focusing on earthquake
                             insight into evolution and   and volcano research
                             biodiversity


                 Scientific challenges with societal impact
                 Sponsored by user organisations
                 Stretch what is possible with the cloud today
                                                                                   14
                           Bob Jones - December 2012
Conclusions

• Big Data Management and Analytics require a solid organisational
  structure at all levels 

• Corporate culture: our community started preparing more than a 
  decade before real physics data arrived

• Now, the LHC data processing is under control but data rates will 
  continue to increase (dramatically) for years to come: Big Data at the 
  Exabyte scale 

• CERN is working with other science organisations and leading IT 
  companies to address our growing big‐data needs


                             Bob Jones ‐ December  2012              15
Accelerating Science and Innovation
                                      16

Contenu connexe

Tendances (7)

Amsa annual national leadership development seminar 30 aug 2010
Amsa annual national leadership development seminar   30 aug 2010Amsa annual national leadership development seminar   30 aug 2010
Amsa annual national leadership development seminar 30 aug 2010
 
Clinical Trials in Australia
Clinical Trials in AustraliaClinical Trials in Australia
Clinical Trials in Australia
 
Australia's Future Health
Australia's Future HealthAustralia's Future Health
Australia's Future Health
 
Small Business Energy Efficiency: Roadmap to Program Design
Small Business Energy Efficiency: Roadmap to Program DesignSmall Business Energy Efficiency: Roadmap to Program Design
Small Business Energy Efficiency: Roadmap to Program Design
 
Poster presentation
Poster presentationPoster presentation
Poster presentation
 
Delivering value with online resources
Delivering value with online resourcesDelivering value with online resources
Delivering value with online resources
 
Update on US Rail Transportation
Update on US Rail TransportationUpdate on US Rail Transportation
Update on US Rail Transportation
 

Similaire à CERN: Big Science Meets Big Data

IBM Storwize V7000 Ultimate Performance Eng
IBM Storwize V7000 Ultimate Performance EngIBM Storwize V7000 Ultimate Performance Eng
IBM Storwize V7000 Ultimate Performance Eng
Oleg Korol
 
Solutions for the Texas Energy Shortage
Solutions for the Texas Energy Shortage Solutions for the Texas Energy Shortage
Solutions for the Texas Energy Shortage
Rick Borry
 
Kevin Ms Web Platform
Kevin Ms Web PlatformKevin Ms Web Platform
Kevin Ms Web Platform
rsnarayanan
 
Wim De Waele - IBBT Strategy
Wim De Waele - IBBT StrategyWim De Waele - IBBT Strategy
Wim De Waele - IBBT Strategy
imec.archive
 
Spreaker - Live Podcasting on AWS - AWS Case Study
Spreaker - Live Podcasting on AWS - AWS Case StudySpreaker - Live Podcasting on AWS - AWS Case Study
Spreaker - Live Podcasting on AWS - AWS Case Study
Amazon Web Services
 
Png 492 pec final-presentation[1][1]
Png 492  pec final-presentation[1][1]Png 492  pec final-presentation[1][1]
Png 492 pec final-presentation[1][1]
nas-psu
 
Png 492 pec final-presentation
Png 492  pec final-presentationPng 492  pec final-presentation
Png 492 pec final-presentation
nas-psu
 
Paper and pencil_cosmological_calculator
Paper and pencil_cosmological_calculatorPaper and pencil_cosmological_calculator
Paper and pencil_cosmological_calculator
Sérgio Sacani
 

Similaire à CERN: Big Science Meets Big Data (20)

Dimensioning and Cost Structure Analysis of Wide Area Data Service Network - ...
Dimensioning and Cost Structure Analysis of Wide Area Data Service Network - ...Dimensioning and Cost Structure Analysis of Wide Area Data Service Network - ...
Dimensioning and Cost Structure Analysis of Wide Area Data Service Network - ...
 
Personalised Graph-Based Selection of Web APIs
Personalised Graph-Based Selection of Web APIsPersonalised Graph-Based Selection of Web APIs
Personalised Graph-Based Selection of Web APIs
 
IBM Storwize V7000 Ultimate Performance Eng
IBM Storwize V7000 Ultimate Performance EngIBM Storwize V7000 Ultimate Performance Eng
IBM Storwize V7000 Ultimate Performance Eng
 
Solutions for the Texas Energy Shortage
Solutions for the Texas Energy Shortage Solutions for the Texas Energy Shortage
Solutions for the Texas Energy Shortage
 
Kevin Ms Web Platform
Kevin Ms Web PlatformKevin Ms Web Platform
Kevin Ms Web Platform
 
Use Distributed Filesystem as a Storage Tier
Use Distributed Filesystem as a Storage TierUse Distributed Filesystem as a Storage Tier
Use Distributed Filesystem as a Storage Tier
 
(ATS3-PLAT01) Recent developments in Pipeline Pilot
(ATS3-PLAT01) Recent developments in Pipeline Pilot(ATS3-PLAT01) Recent developments in Pipeline Pilot
(ATS3-PLAT01) Recent developments in Pipeline Pilot
 
American Pharmaceutical Review Barnes Et Al
American Pharmaceutical Review Barnes Et AlAmerican Pharmaceutical Review Barnes Et Al
American Pharmaceutical Review Barnes Et Al
 
Lattes and other Brazilian ST&I platforms
Lattes and other Brazilian ST&I platformsLattes and other Brazilian ST&I platforms
Lattes and other Brazilian ST&I platforms
 
Ape 2013 23012013
Ape 2013 23012013Ape 2013 23012013
Ape 2013 23012013
 
Lte asia 2011 s niri
Lte asia 2011 s niriLte asia 2011 s niri
Lte asia 2011 s niri
 
Business review templates
Business review templatesBusiness review templates
Business review templates
 
Wim De Waele - IBBT Strategy
Wim De Waele - IBBT StrategyWim De Waele - IBBT Strategy
Wim De Waele - IBBT Strategy
 
Energy smart grid-analytics and insights of Intelen patented Technology
Energy smart grid-analytics and insights of Intelen patented TechnologyEnergy smart grid-analytics and insights of Intelen patented Technology
Energy smart grid-analytics and insights of Intelen patented Technology
 
Spreaker - Live Podcasting on AWS - AWS Case Study
Spreaker - Live Podcasting on AWS - AWS Case StudySpreaker - Live Podcasting on AWS - AWS Case Study
Spreaker - Live Podcasting on AWS - AWS Case Study
 
Bratislava Airport City
Bratislava Airport CityBratislava Airport City
Bratislava Airport City
 
Png 492 pec final-presentation[1][1]
Png 492  pec final-presentation[1][1]Png 492  pec final-presentation[1][1]
Png 492 pec final-presentation[1][1]
 
Png 492 pec final-presentation
Png 492  pec final-presentationPng 492  pec final-presentation
Png 492 pec final-presentation
 
What I did in My Internship @ WSO2
What I did in My Internship @ WSO2What I did in My Internship @ WSO2
What I did in My Internship @ WSO2
 
Paper and pencil_cosmological_calculator
Paper and pencil_cosmological_calculatorPaper and pencil_cosmological_calculator
Paper and pencil_cosmological_calculator
 

Dernier

Spellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseSpellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please Practise
AnaAcapella
 

Dernier (20)

How to setup Pycharm environment for Odoo 17.pptx
How to setup Pycharm environment for Odoo 17.pptxHow to setup Pycharm environment for Odoo 17.pptx
How to setup Pycharm environment for Odoo 17.pptx
 
How to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POSHow to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POS
 
Google Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptxGoogle Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptx
 
Sociology 101 Demonstration of Learning Exhibit
Sociology 101 Demonstration of Learning ExhibitSociology 101 Demonstration of Learning Exhibit
Sociology 101 Demonstration of Learning Exhibit
 
Fostering Friendships - Enhancing Social Bonds in the Classroom
Fostering Friendships - Enhancing Social Bonds  in the ClassroomFostering Friendships - Enhancing Social Bonds  in the Classroom
Fostering Friendships - Enhancing Social Bonds in the Classroom
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptx
 
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
 
Spellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseSpellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please Practise
 
Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...
 
Towards a code of practice for AI in AT.pptx
Towards a code of practice for AI in AT.pptxTowards a code of practice for AI in AT.pptx
Towards a code of practice for AI in AT.pptx
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 
Understanding Accommodations and Modifications
Understanding  Accommodations and ModificationsUnderstanding  Accommodations and Modifications
Understanding Accommodations and Modifications
 
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
 
REMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptxREMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptx
 
Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdf
 
Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.ppt
 
General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual  Proper...General Principles of Intellectual Property: Concepts of Intellectual  Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...
 
Interdisciplinary_Insights_Data_Collection_Methods.pptx
Interdisciplinary_Insights_Data_Collection_Methods.pptxInterdisciplinary_Insights_Data_Collection_Methods.pptx
Interdisciplinary_Insights_Data_Collection_Methods.pptx
 
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
 

CERN: Big Science Meets Big Data

  • 1. CERN: Big Science Meets Big Data Dr Bob Jones CERN Bob.Jones <at> CERN.ch
  • 2. CERN was founded 1954: 12 European States Today: 20 Member States ~ 2300 staff ~ 790 other paid personnel > 10000 users Budget ~1000 MCHF annual 20 Member States: Austria, Belgium, Bulgaria, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Italy, Netherlands, Norway, Poland, Portugal, Slovakia, Spain, Sweden, Switzerland and the United Kingdom Candidates for Accession: Romania, Israel Observers to Council: India, Japan, the Russian Federation, the United States of America, Bob Jones - December 2012 2 2 Turkey, the European Commission and UNESCO
  • 3. Accelerating Science and Innovation Bob Jones - December 2012 3
  • 4. Data flow to permanent storage: 4-6 GB/sec 200-400 MB/sec 1-2 GB/sec 1.25 GB/sec 1-2 GB/sec Bob Jones - December 2012 4
  • 5. WLCG – what and why? • A distributed computing  infrastructure to provide the  production and analysis  environments for the LHC  experiments • Managed and operated by a  worldwide collaboration between  the experiments and the  participating computer centres • The resources are distributed – for  funding and sociological reasons • Our task was to make use of the  Tier-0 (CERN): Tier-2 (~130 centres): resources available to us – no  • Data recording • Simulation matter where they are located • Initial data reconstruction • End-user analysis • Data distribution Tier-1 (11 centres): • Secure access via X509 certificates  •Permanent storage issued by network of national  •Re-processing authorities ‐ International Grid  •Analysis Trust Federation (IGTF) – http://www.igtf.net/  Bob Jones ‐ December  2012 5
  • 6. WLCG: Data Taking • Castor service at Tier 0 well adapted to  HI: ALICE data into Castor  > 4 GB/s (red) the load: – Heavy Ions: more than 6 GB/s to tape  (tests show that Castor can easily  support >12 GB/s); Actual limit  now  is network from experiment to CC – Major improvements in tape  efficiencies – tape writing at ~native  HI: Overall rates to tape > 6 GB/s (r+b) drive speeds. Fewer drives needed – ALICE had x3 compression for raw  data in HI runs Accumulated Data 2012 0.1 0.2 0.8 0.0 ALICE 0.8 1.3 AMS 0.9 1.2 ATLAS CMS 5.8 COMPASS 4.6 LHCB 23 PB data written in 2011 NA48
  • 7. 0 10000000 20000000 30000000 40000000 50000000 60000000 Jan‐09 Feb‐09 Mar‐09 Apr‐09 May‐09 Jun‐09 CMS LHCb ALICE Jul‐09 ATLAS Aug‐09 Sep‐09 Oct‐09 Nov‐09 Dec‐09 Jan‐10 Feb‐10 Mar‐10 1.5M jobs/day Apr‐10 May‐10 Jun‐10 Ja Jul‐10 100000000 200000000 300000000 400000000 500000000 600000000 700000000 800000000 900000000 0 1E+09 n‐ 10 Fe Aug‐10 b‐ 10 Sep‐10 M ar ‐1 Oct‐10 0 Ap Nov‐10 r‐1 0 Dec‐10 M ay ‐1 Jan‐11 0 Ju Feb‐11 CMS LHCb n‐ ALICE 10 Mar‐11 Ju l‐1 ATLAS Apr‐11 0 Au May‐11 g‐ 10 Jun‐11 Se p‐ Jul‐11 10 Oc Aug‐11 t‐ 1 0 Sep‐11 No v‐ 10 Oct‐11 De Nov‐11 c‐ 10 Dec‐11 Ja n‐ 11 Jan‐12 Fe b‐ 11 M ar ‐1 1 Ap r‐1 1 Overall use of WLCG M ay ‐1 1 Ju n‐ 109 HEPSPEC‐hours/month 11 (~150 k CPU continuous use) Ju l ‐1 1 Au g‐ 11 ‐ # jobs/day Se ‐ CPU usage p‐ 11 Oc t‐ 1 1 No year technical stop v‐ 11 Usage continues to  De c‐ 11 grow even over end of 
  • 8. Broader Impact of the LHC  Computing Grid • WLCG has been leveraged on both sides of  the Atlantic, to benefit the wider scientific  community – Europe (EC FP7): • Enabling Grids for E‐sciencE Archeology (EGEE) 2004‐2010 Astronomy Astrophysics • European Grid Infrastructure  Civil Protection (EGI)  2010‐‐ Comp. Chemistry – USA (NSF): Earth Sciences • Open Science Grid (OSG)  Finance Fusion 2006‐2012  (+ extension?) Geophysics High Energy Physics • Many scientific applications  Life Sciences Multimedia Material Sciences Bob Jones ‐ December  2012 8 …
  • 9. How to evolve LHC data processing Making what we have today more sustainable is a challenge • Big Data issues – Data management and access – How to make reliable and fault tolerant systems – Data preservation and open access • Need to adapt to changing technologies – Use of many‐core CPUs – Global filesystem‐like facilities – Virtualisation at all levels (including cloud computing services)  • Network infrastructure – Has proved to be very reliable so invest in networks and make full  use of the distributed system Bob Jones ‐ December  2012 9
  • 10. CERN openlab in a nutshell • A science – industry partnership to drive R&D and innovation with over a decade of success • Evaluate state-of-the-art technologies in a challenging environment and improve them • Test in a research environment today what will be used in many business sectors tomorrow • Train next generation of engineers/employees CONTRIBUTOR (2012) • Disseminate results and outreach to new audiences Bob Jones - December 2012 10
  • 11. Virtuous Cycle CERN requirements push the limit Produce Apply new advanced techniques products and and services technologies Test Joint prototypes in development CERN in rapid environment cycles A public-private partnership between the research community and industry http://openlab.cern.ch Bob Jones - December 2012 11
  • 12. Bob Jones - December 2012 12
  • 13. A European Cloud Computing Partnership:  big science teams up with big business To create an Earth  To support the  Setting up a new  Strategic Plan computing capacity  service to simplify  Observation platform,  focusing on  needs for the ATLAS  analysis of large   Establish multi‐tenant,  experiment genomes, for a deeper  earthquake and  multi‐provider cloud  volcano research insight into evolution  infrastructure and biodiversity  Identify and adopt policies  for trust, security and  privacy  Create governance  structure  Define funding schemes Email:contact@helix-nebula.eu Twitter: HelixNebulaSC Web: www.helix-nebula.eu 13
  • 14. Initial flagship use cases ATLAS High Energy Genomic Assembly SuperSites Exploitation Physics Cloud Use in the Cloud Platform To support the computing A new service to simplify To create an Earth capacity needs for the large scale genome Observation platform, ATLAS experiment analysis; for a deeper focusing on earthquake insight into evolution and and volcano research biodiversity  Scientific challenges with societal impact  Sponsored by user organisations  Stretch what is possible with the cloud today 14 Bob Jones - December 2012
  • 15. Conclusions • Big Data Management and Analytics require a solid organisational structure at all levels  • Corporate culture: our community started preparing more than a  decade before real physics data arrived • Now, the LHC data processing is under control but data rates will  continue to increase (dramatically) for years to come: Big Data at the  Exabyte scale  • CERN is working with other science organisations and leading IT  companies to address our growing big‐data needs Bob Jones ‐ December  2012 15
  • 16. Accelerating Science and Innovation 16