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WSISRO Openinghbn110702

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Information about WSISRO Openinghbn110702
Travel-Nature

Published on March 30, 2008

Author: Miguel

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Slide1:  Creating a Sustainable Cycle of Innovation Harvey B Newman, Caltech WSIS Pan European Regional Ministerial Conference Bucharest, November 7-9 2002 Global Virtual Organizations for Data Intensive Science Challenges of Data Intensive Science and Global VOs:  Challenges of Data Intensive Science and Global VOs Geographical dispersion: of people and resources Scale: Tens of Petabytes per year of data Complexity: Scientic Instruments and information 5000+ Physicists 250+ Institutes 60+ Countries Major challenges associated with: Communication and collaboration at a distance Managing globally distributed computing & data resources Cooperative software development and physics analysis New Forms of Distributed Systems: Data Grids Emerging Data Grid User Communities:  Emerging Data Grid User Communities Grid Physics Projects (GriPhyN/iVDGL/EDG) ATLAS, CMS, LIGO, SDSS; BaBar/D0/CDF NSF Network for Earthquake Engineering Simulation (NEES) Integrated instrumentation, collaboration, simulation Access Grid; VRVS: supporting new modes of group-based collaboration And Genomics, Proteomics, ... The Earth System Grid and EOSDIS Federating Brain Data Computed MicroTomography … Virtual Observatories Grids are Having a Global Impact on Research in Science & Engineering Global Networks for HENP and Data Intensive Science :  Global Networks for HENP and Data Intensive Science National and International Networks with sufficient capacity and capability, are essential today for The daily conduct of collaborative work in both experiment and theory Data analysis by physicists from all world regions The conception, design and implementation of next generation facilities, as “global (Grid) networks” “Collaborations on this scale would never have been attempted, if they could not rely on excellent networks” – L. Price, ANL Grids Require Seamless Network Systems with Known, High Performance High Speed Bulk Throughput BaBar Example [and LHC]:  Data volume Moore’s law High Speed Bulk Throughput BaBar Example [and LHC] Driven by: HENP data rates, e.g. BaBar ~500TB/year, Data rate from experiment >20 MBytes/s; [5-75 Times More at LHC] Grid of Multiple regional computer centers (e.g. Lyon-FR, RAL-UK, INFN-IT, CA: LBNL, LLNL, Caltech) need copies of data Need high-speed networks and the ability to utilize them fully High speed Today = 1 TB/day (~100 Mbps Full Time) Develop 10-100 TB/day Capability (Several Gbps Full Time) within the next 1-2 years Data Volumes More than Doubling Each Yr; Driving Grid, Network Needs HENP Major Links: Bandwidth Roadmap (Scenario) in Gbps:  HENP Major Links: Bandwidth Roadmap (Scenario) in Gbps Continuing the Trend: ~1000 Times Bandwidth Growth Per Decade; We are Rapidly Learning to Use and Share Multi-Gbps Networks AMS-IX Internet Exchange Thruput Accelerating Growth in Europe (NL):  AMS-IX Internet Exchange Thruput Accelerating Growth in Europe (NL) Monthly Traffic 4X Growth In 14 Months 8/01 – 10/02 ↓ 2 Gbps 8 Gbps 6 Gbps 4 Gbps HENP & World BW Growth: 3-4 Times Per Year; 2 to 3 Times Moore’s Law National Light Rail Footprint:  National Light Rail Footprint NLR Buildout Starts November 2002 Initially 4 10 Gb Wavelengths To 40 10Gb Waves in Future NREN Backbones reached 2.5-10 Gbps in 2002 in Europe, Japan and US; US: Transition now to optical, dark fiber, multi-wavelength R&E network Distributed System Services Architecture (DSSA): CIT/Romania/Pakistan:  Distributed System Services Architecture (DSSA): CIT/Romania/Pakistan Agents: Autonomous, Auto-discovering, self-organizing, collaborative “Station Servers” (static) host mobile “Dynamic Services” Servers interconnect dynamically; form a robust fabric in which mobile agents travel, with a payload of (analysis) tasks Adaptable to Web services: OGSA; and many platforms Adaptable to Ubiquitous, mobile working environments Managing Global Systems of Increasing Scope and Complexity, In the Service of Science and Society, Requires A New Generation of Scalable, Autonomous, Artificially Intelligent Software Systems Slide10:  By I. Legrand (Caltech) Deployed on US CMS Grid Agent-based Dynamic information / resource discovery mechanism Implemented in Java/Jini; SNMP WDSL / SOAP with UDDI Part of a Global “Grid Control Room” Service http://cil.cern.ch:8080/MONALISA/ MonaLisa: A Globally Scalable Grid Monitoring System History - Throughput Quality Improvements from US to World :  History - Throughput Quality Improvements from US to World Bandwidth of TCP < MSS/(RTT*Sqrt(Loss)) (1) 80% annual improvement Factor ~100/8 yr Progress, but the Digital Divide is Maintained: Action is Required NREN Core Network Size (Mbps-km): http://www.terena.nl/compendium/2002:  NREN Core Network Size (Mbps-km): http://www.terena.nl/compendium/2002 Perspectives on the Digital Divide: Int’l, Local, Regional, Political Building Petascale Global Grids: Implications for Society:  Building Petascale Global Grids: Implications for Society Meeting the challenges of Petabyte-to-Exabyte Grids, and Gigabit-to-Terabit Networks, will transform research in science and engineering These developments could create the first truly global virtual organizations (GVO) If these developments are successful, and deployed widely as standards, this could lead to profound advances in industry, commerce and society at large By changing the relationship between people and “persistent” information in their daily lives Within the next five to ten years Realizing the benefits of these developments for society, and creating a sustainable cycle of innovation compels us TO CLOSE the DIGITAL DIVIDE Recommendations:  Recommendations To realize the Vision of Global Grids, governments, international institutions and funding agencies should: Define IT international policies (for instance AAA) Support establishment of international standards Provide adequate funding to continue R&D in Grid and Network technologies Deploy international production Grid and Advanced Network testbeds on a global scale Support education and training in Grid & Network technologies for new communities of users Create open policies, and encourage joint development programs, to help Close the Digital Divide The WSIS RO meeting, starting today, is an important step in the right direction Some Extra Slides Follow:  Some Extra Slides Follow Slide16:  IEEAF: Internet Educational Equal Access Foundation; Bandwidth Donations for Research and Education Next Generation Requirements for Physics Experiments:  Next Generation Requirements for Physics Experiments Rapid access to event samples and analyzed results drawn from massive data stores From Petabytes in 2002, ~100 Petabytes by 2007, to ~1 Exabyte by ~2012. Coordinating and managing the large but LIMITED computing, data and network resources effectively Persistent access to physicists throughout the world, for collaborative work Grid Reliance on Networks Advanced applications such as Data Grids rely on seamless operation of Local and Wide Area Networks With reliable, quantifiable high performance Networks, Grids and HENP:  Networks, Grids and HENP Grids are changing the way we do science and engineering Next generation 10 Gbps network backbones are here: in the US, Europe and Japan; across oceans Optical Nets with many 10 Gbps wavelengths will follow Removing regional, last mile bottlenecks and compromises in network quality are now All on the critical path Network improvements are especially needed in SE Europe, So. America; and many other regions: Romania; India, Pakistan, China; Brazil, Chile; Africa Realizing the promise of Network & Grid technologies means Building a new generation of high performance network tools; artificially intelligent scalable software systems Strong regional and inter-regional funding initiatives to support these ground breaking developments Closing the Digital Divide:  Closing the Digital Divide What HENP and the World Community Can Do Spread the message: ICFA SCIC, IEEAF et al. can help Help identify and highlight specific needs (to Work On) Policy problems; Last Mile problems; etc. Encourage Joint programs [Virtual Silk Road project; Japanese links to SE Asia and China; AMPATH to So. America] NSF & LIS Proposals: US and EU to South America Make direct contacts, arrange discussions with gov’t officials ICFA SCIC is prepared to participate where appropriate Help Start, Get Support for Workshops on Networks & Grids Encourage, help form funded programs Help form Regional support & training groups [Requires Funding] LHC Data Grid Hierarchy:  LHC Data Grid Hierarchy Tier 1 Online System CERN 700k SI95 ~1 PB Disk; Tape Robot FNAL: 200k SI95; 600 TB IN2P3 Center INFN Center RAL Center Institute Institute Institute Institute ~0.25TIPS Workstations ~100-400 MBytes/sec 2.5-10 Gbps 0.1–10 Gbps Physicists work on analysis “channels” Each institute has ~10 physicists working on one or more channels Physics data cache ~PByte/sec ~2.5-10 Gbps ~2.5 Gbps Tier 0 +1 Tier 3 Tier 4 Tier 2 Experiment CERN/Outside Resource Ratio ~1:2 Tier0/( Tier1)/( Tier2) ~1:1:1 Slide21:  Two centers are trying to work as one: -Data not duplicated -Internationalization -transparent access, etc Tier A "Physicists have indeed foreseen to test the GRID principles starting first from the Computing Centres in Lyon and Stanford (California). A first step towards the ubiquity of the GRID." Le Monde 12 april 2001 CERN-US Line + Abilene Renater + ESnet 3/2002 LHC Grid Wkshop 3/02; 2003: to 1 Gbps range 0.5 PB and UP; LHC 10 to 100 Times Greater Why Grids?:  Why Grids? 1,000 physicists worldwide pool resources for petaop analyses of petabytes of data A biochemist exploits 10,000 computers to screen 100,000 compounds in an hour Civil engineers collaborate to design, execute, & analyze shake table experiments Climate scientists visualize, annotate, & analyze terabyte simulation datasets An emergency response team couples real time data, weather model, population data Why Grids? (contd):  Why Grids? (contd) Scientists at a multinational company collaborate on the design of a new product A multidisciplinary analysis in aerospace couples code and data in four companies An HMO mines data from its member hospitals for fraud detection An application service provider offloads excess load to a compute cycle provider An enterprise configures internal & external resources to support e-business workload Grids: Why Now?:  Grids: Why Now? Moore’s law improvements in computing produce highly functional endsystems The Internet and burgeoning wired and wireless provide universal connectivity Changing modes of working and problem solving emphasize teamwork, computation Network exponentials produce dramatic changes in geometry and geography 9-month doubling: double Moore’s law! 1986-2001: x340,000; 2001-2010: x4000? A Short List: Revolutions in Information Technology (2002-7) :  A Short List: Revolutions in Information Technology (2002-7) Scalable Data-Intensive Metro and Long Haul Network Technologies DWDM: 10 Gbps then 40 Gbps per ; 1 to 10 Terabits/sec per fiber 10 Gigabit Ethernet (See www.10gea.org) 10GbE / 10 Gbps LAN/WAN integration Metro Buildout and Optical Cross Connects Dynamic Provisioning  Dynamic Path Building “Lambda Grids” Defeating the “Last Mile” Problem (Wireless; or Ethernet in the First Mile) 3G and 4G Wireless Broadband (from ca. 2003); and/or Fixed Wireless “Hotspots” Fiber to the Home Community-Owned Networks Grid Architecture:  Grid Architecture Connectivity Resource Collective Application Fabric Internet Transport Appli- cation Link Internet Protocol Architecture More info: www.globus.org/research/papers/anatomy.pdf Slide27:  Grid projects have been a step forward for HEP and LHC: a path to meet the “LHC Computing” challenges But: the differences between HENP Grids and classical Grids are not yet fully appreciated The original Computational and Data Grid concepts are largely stateless, open systems: known to be scalable Analogous to the Web The classical Grid architecture has a number of implicit assumptions The ability to locate and schedule suitable resources, within a tolerably short time (i.e. resource richness) Short transactions; Relatively simple failure modes HEP Grids are data-intensive and resource constrained Long transactions; some long queues Schedule conflicts; [policy decisions]; task redirection A Lot of global system state to be monitored+tracked LHC Distributed CM: HENP Data Grids Versus Classical Grids Upcoming Grid Challenges: Building a Globally Managed Distributed System:  Upcoming Grid Challenges: Building a Globally Managed Distributed System Maintaining a Global View of Resources and System State End-to-end System Monitoring Adaptive Learning: new paradigms for execution optimization (eventually automated) Workflow Management, Balancing Policy Versus Moment-to-moment Capability to Complete Tasks Balance High Levels of Usage of Limited Resources Against Better Turnaround Times for Priority Jobs Goal-Oriented; Steering Requests According to (Yet to be Developed) Metrics Robust Grid Transactions In a Multi-User Environment Realtime Error Detection, Recovery Handling User-Grid Interactions: Guidelines; Agents Building Higher Level Services, and an Integrated User Environment for the Above Slide29:  (Physicists’) Application Codes Experiments’ Software Framework Layer Needs to be Modular and Grid-aware: Architecture able to interact effectively with the Grid layers Grid Applications Layer (Parameters and algorithms that govern system operations) Policy and priority metrics Workflow evaluation metrics Task-Site Coupling proximity metrics Global End-to-End System Services Layer Monitoring and Tracking Component performance Workflow monitoring and evaluation mechanisms Error recovery and redirection mechanisms System self-monitoring, evaluation and optimization mechanisms Interfacing to the Grid: Above the Collective Layer Slide30:  GENEVA ABILENE ESNET CALREN NewYork STAR-TAP STARLIGHT DataTAG Project EU-Solicited Project. CERN, PPARC (UK), Amsterdam (NL), and INFN (IT); and US (DOE/NSF: UIC, NWU and Caltech) partners Main Aims: Ensure maximum interoperability between US and EU Grid Projects Transatlantic Testbed for advanced network research 2.5 Gbps Wavelength Triangle 7/02 (10 Gbps Triangle in 2003) Wave Triangle TeraGrid (www.teragrid.org) NCSA, ANL, SDSC, Caltech:  TeraGrid (www.teragrid.org) NCSA, ANL, SDSC, Caltech NCSA/UIUC ANL UIC Multiple Carrier Hubs Starlight / NW Univ Ill Inst of Tech Univ of Chicago Indianapolis (Abilene NOC) I-WIRE Caltech San Diego DTF Backplane: 4 X 10 Gbps Abilene Chicago Indianapolis Urbana OC-48 (2.5 Gb/s, Abilene) Multiple 10 GbE (Qwest) Multiple 10 GbE (I-WIRE Dark Fiber) Source: Charlie Catlett, Argonne A Preview of the Grid Hierarchy and Networks of the LHC Era Baseline BW for the US-CERN Link: HENP Transatlantic WG (DOE+NSF):  Baseline BW for the US-CERN Link: HENP Transatlantic WG (DOE+NSF) DataTAG 2.5 Gbps Research Link in Summer 2002 10 Gbps Research Link by Approx. Mid-2003 Transoceanic Networking Integrated with the Abilene, TeraGrid, Regional Nets and Continental Network Infrastructures in US, Europe, Asia, South America Baseline evolution typical of major HENP links 2001-2006 HENP As a Driver of Networks: Petascale Grids with TB Transactions:  HENP As a Driver of Networks: Petascale Grids with TB Transactions Problem: Extract “Small” Data Subsets of 1 to 100 Terabytes from 1 to 1000 Petabyte Data Stores Survivability of the HENP Global Grid System, with hundreds of such transactions per day (circa 2007) requires that each transaction be completed in a relatively short time. Example: Take 800 secs to complete the transaction. Then Transaction Size (TB) Net Throughput (Gbps) 1 10 10 100 100 1000 (Capacity of Fiber Today) Summary: Providing Switching of 10 Gbps wavelengths within ~3 years; and Terabit Switching within 5-8 years would enable “Petascale Grids with Terabyte transactions”, as required to fully realize the discovery potential of major HENP programs, as well as other data-intensive fields. National Research Networks in Japan:  National Research Networks in Japan SuperSINET Started operation January 4, 2002 Support for 5 important areas: HEP, Genetics, Nano-Technology, Space/Astronomy, GRIDs Provides 10 ’s: 10 Gbps IP connection 7 Direct intersite GbE links Some connections to 10 GbE in JFY2002 HEPnet-J Will be re-constructed with MPLS-VPN in SuperSINET Proposal: Two TransPacific 2.5 Gbps Wavelengths, and Japan-CERN Grid Testbed by ~2003 Tokyo Osaka Nagoya Internet Osaka U Kyoto U ICR Kyoto-U Nagoya U NIFS NIG IMS U-Tokyo NAO U Tokyo NII Hitot. IP WDM path IP router ISAS Slide35:  National R&E Network Example Germany: DFN TransAtlantic Connectivity Q1 2002 2 X 2.5G Now: NY-Hamburg and NY-Frankfurt ESNet peering at 34 Mbps Direct Peering to Abilene and Canarie expected UCAID will add another 2 OC48’s; Proposing a Global Terabit Research Network (GTRN) FSU Connections via satellite: Yerevan, Minsk, Almaty, Baikal Speeds of 32 - 512 kbps SILK Project (2002): NATO funding Links to Caucasus and Central Asia (8 Countries) Currently 64-512 kbps Propose VSAT for 10-50 X BW: NATO + State Funding Slide36:  RNP Brazil (to 20 Mbps) FIU Miami/So. America (to 80 Mbps) Slide37:  The simulation program developed within MONARC (Models Of Networked Analysis At Regional Centers) uses a process- oriented approach for discrete event simulation, and provides a realistic modelling tool for large scale distributed systems. Modeling and Simulation: MONARC System SIMULATION of Complex Distributed Systems for LHC Globally Scalable Monitoring Service:  Farm Monitor Client (other service) Lookup Service Lookup Service Farm Monitor Discovery Proxy Component Factory GUI marshaling Code Transport RMI data access Push & Pull rsh & ssh scripts; snmp Globally Scalable Monitoring Service I. Legrand RC Monitor Service Registration MONARC SONN: 3 Regional Centres Learning to Export Jobs:  MONARC SONN: 3 Regional Centres Learning to Export Jobs NUST 20 CPUs CERN 30 CPUs CALTECH 25 CPUs 1MB/s ; 150 ms RTT 1.2 MB/s 150 ms RTT 0.8 MB/s 200 ms RTT Day = 9 <E> = 0.73 <E> = 0.66 <E> = 0.83 By I. Legrand COJAC: CMS ORCA Java Analysis Component: Java3D Objectivity JNI Web Services:  COJAC: CMS ORCA Java Analysis Component: Java3D Objectivity JNI Web Services Internet2 HENP WG [*] :  Internet2 HENP WG [*] Mission: To help ensure that the required National and international network infrastructures (end-to-end) Standardized tools and facilities for high performance and end-to-end monitoring and tracking [Gridftp; bbcp…] Collaborative systems are developed and deployed in a timely manner, and used effectively to meet the needs of the US LHC and other major HENP Programs, as well as the at-large scientific community. To carry out these developments in a way that is broadly applicable across many fields Formed an Internet2 WG as a suitable framework: October 2001 [*] Co-Chairs: S. McKee (Michigan), H. Newman (Caltech); Sec’y J. Williams (Indiana) Website: http://www.internet2.edu/henp; also see the Internet2 End-to-end Initiative: http://www.internet2.edu/e2e A Short List: Coming Revolutions in Information Technology :  A Short List: Coming Revolutions in Information Technology Storage “Virtualization” [ A Single Logical Resource] Grid-enabled Storage Resource Middleware (SRM) iSCSI (Internet Small Computer Storage Interface); Integrated with 10 GbE  Global File Systems Internet Information Software Technologies Global Information “Broadcast” Architecture E.g the Multipoint Information Distribution Protocol (Tie.Liao@inria.fr) Programmable Coordinated Agent Architectures E.g. Mobile Agent Reactive Spaces (MARS) by Cabri et al., University of Modena The “Data Grid” - Human Interface Interactive monitoring and control of Grid resources By authorized groups and individuals By Autonomous Agents Slide43:  Palat Telefoane 1G link 1G backup link Romana Victoriei Gara de Nord Eroilor Izvor Universitate Unirii NOC Cat3550-24-L3 C7206 w Gigabit C7513 w Gigabit Cat4000 L3 Sw Bucharest MAN for Ro-Grid ICI IFIN 100Mbps 10/100/1000Mbps Slide44:  RoEdu Network

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