Distributed e-infrastructures for data intensive science
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1 Distributed e-infrastructures for data intensive science Bob Jones CERN Bob.Jones <at> CERN.ch
2 Overview What is CERN The LHC accelerator and experiments The Computing needs of the LHC The World wide LHC Computing Grid Relevance for other scientific disciplines Data Infrastructures evolution This talk presents the work of many people at CERN and the LHC and grid computing communities Bob Jones June
3 CERN was founded 1954: 12 European States Today: 20 Member States ~ 2300 staff ~ 790 other paid personnel > users Budget (2011) ~1000 MCHF 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 1 Candidate for Accession: Romania 8 Observers to Council: India, Israel, Japan, the Russian Federation, the United States of America, Turkey, the European Commission and UNESCO 3
4 The Mission of CERN Push back the frontiers of knowledge E.g. the secrets of the Big Bang what was the matter like within the first moments of the Universe s existence? Develop new technologies for accelerators and detectors Information technology - the Web and the GRID Medicine - diagnosis and therapy Train scientists and engineers of tomorrow Unite people from different countries and cultures CERN / January 2011
5 Enter a New Era in Fundamental Science Start-up of the Large Hadron Collider (LHC), one of the largest and truly global scientific projects ever, is the most exciting turning point in particle physics. CMS LHCb Exploration of a new energy frontier Proton-proton collisions at E CM = 14 TeV ALICE LHC ring: 27 km circumference ATLAS
6 The ATLAS experiment CERN IT Department CH-1211 Genève 23 Switzerland tons, 150 million sensors generating data 40 millions times per second i.e. a petabyte/s Bob Jones The LHC Computing Grid - February
7 7 A LHC
8 8 The Data Acquisition
9 RAID controllers 3,518 Data acquisition and storage for CERN Tape Drives 160 Tape Cartridges Tape slots Tape Capacity (TB) High Speed Routers (640 Mbps 2.4 Tbps) 24 Ethernet Switches Gbps ports 2000 Switching Capacity 4.8 Tbps Servers 8,076 Processors 13,802 Cores 50,855 HEPSpec06 359,431 Disks 53,728 Raw disk capacity (TB) 45,331 Memory modules 48,794
10 The LHC Data Challenge CERN IT Department CH-1211 Genève 23 Switzerland The accelerator will run for 20 years Experiments will produce about 15 Million Gigabytes of data each year (about 20 million CDs!) LHC data analysis requires a computing power equivalent to ~100,000 of today's fastest PC processors Requires many cooperating computer centres, as CERN can only provide ~20% of the capacity Bob Jones 10
11 World-wide LHC Computing Grid 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 is to make use of the resources available to us no matter where they are located 11
12 WLCG data processing model Tier-0 (CERN): Data recording Initial data reconstruction Data distribution Tier-1 (11 centres): Permanent storage Re-processing Analysis Tier-2 (~130 centres): Simulation End-user analysis 12
13 CERN Ca- TRIUMF US-BNL Amsterdam/NIKHEF-SARA WLCG Collaboration Status Tier 0; 11 Tier 1s; 64 Tier 2 federations Taipei/ASGC Today we have 49 MoU signatories, representing 34 countries: Australia, Austria, Belgium, Brazil, Canada, China, Czech Rep, Denmark, Estonia, Finland, France, Germany, Hungary, Italy, India, Israel, Japan, Rep. Korea, Netherlands, Norway, Pakistan, Poland, Portugal, Romania, Russia, Slovenia, Spain, Sweden, Switzerland, Taipei, Turkey, UK, Ukraine, USA. Bologna/CNAF NDGF US-FNAL De-FZK Barcelona/PIC Lyon/CCIN2P3 UK-RAL
14 Large Hadron Collider Optical Private Network Bob Jones June
15 Worldwide resources >140 sites ~250k CPU cores ~100 PB disk 15
16 2010 Data Taking Stored ~ 15 PB in 2010 with peaks at 220 TB/day during Pb+Pb Tier-0 Bandwidth Average in: 2 GB/s with peaks at 11.5 GB/s Average out: 6 GB/s with peaks at 25 GB/s 16
17 European Grid Infrastructure European Data Grid (EDG) Explore concepts in a testbed Enabling Grid for E-sciencE (EGEE) Moving from prototype to production European Grid Infrastructure (EGI) Routine usage of a sustainable e- infrastructure EGI-InSPIRE RI
18 European Grid Infrastructure (Status April 2011 yearly increase) end-users (+9%) 186 VOs (+6%) ~30 active VOs: constant Logical CPUs (cores) 207,200 EGI (+8%) 308,500 All 90 MPI sites 101 PB disk 80 PB tape 25.7 million jobs/month 933,000 jobs/day (+91%) 320 sites (1.4%) 58 countries (+11.5%) Archeology Astronomy Astrophysics Civil Protection Comp. Chemistry Earth Sciences Finance Fusion Geophysics High Energy Physics Life Sciences Multimedia Material Sciences EGI-InSPIRE RI
19 Eric Yen Bob Jones June
20 Eric Yen Bob Jones June
21 Bob Jones June 2011 Andrea Donnellan 21
22 Andrea Donnellan Bob Jones June
23 EPOS infrastructure Satellite observation infrastructure GMES, GEOSS,... Users, science, education, public User Interface Permanent Networks Temporary deployments In-situ Observatories European Plate Observing System Volcano Observatories Experimental Laboratories Data mining archiving Analytical Laboratories Computational Facilities (HPC, GRID) Ocean observation infrastructures, EMSO, ESONET, See poster T5-P21...
24 Grids, clouds, supercomputers, etc. Grids Collaborative environment Distributed resources (political/sociological) Commodity hardware (HEP) data management Complex interfaces (bug not feature) Communities expected to contribute resources Supercomputers Scarce Low latency interconnects Applications peer reviewed Parallel/coupled applications Also SC grids (DEISA/PRACE, Teragrid/XD) Clouds Proprietary (implementation) Economies of scale in management Commodity hardware Pay-as-you-go usage model Details of physical resources hidden Simple interfaces Volunteer computing Simple mechanism to access millions CPUs Difficult if (much) data involved Control of environment check Community building people involved in Science Potential for huge amounts of real work Bob Jones June
25 A collaborative Data Infrastructure a framework for the future Trust Data Curation Data generators Users Community Support Services Common Data Services User functionalities, data capture & transfer, virtual research environments Data discovery & navigation Workflow generation Annotation, interpretability Persistent storage Identification, Authenticity, workflow execution, mining
26 vision 2030 high-level experts group on Scientific Data Our vision is a scientific e-infrastructure that supports seamless access, use, re-use and trust of data. In a sense, the physical and technical infrastructure becomes invisible and the data themselves become the infrastructure a valuable asset, on which science, technology, the economy and society can advance. High-Level Group on Scientific Data Riding the Wave: how Europe can gain from the raising tide of scientific data
27 Thank you for your attention Accelerating Science and Innovation
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