The Grid approach for the HEP computing problem Massimo Sgaravatto INFN Padova massimo. sgaravatto@pd. infn. it
What is a Grid ? “Dependable, consistent, pervasive access to resources” n n Enable communities (“virtual organizations”) to share geographically distributed resources as they pursue common goals in the absence of central control, omniscience, trust relationships Make it easy to use diverse, geographically distributed, locally managed and controlled computing facilities as if they formed a coherent local cluster
What does the Grid do for you? n n You submit your work And the Grid n n n “Partitions” your work into convenient execution units based on the available resources, data distribution, … if there is scope for parallelism Finds convenient places for it to be run Organises efficient access to your data n n n n Caching, migration, replication Deals with authentication and authorization to the different sites that you will be using Interfaces to local site resource allocation mechanisms, policies Runs your jobs Monitors progress Recovers from problems Tells you when your work is complete
Grid approach in many sciences and disciplines …
Mathematicians Solve NUG 30 n n n Looking for the solution to the NUG 30 quadratic assignment problem An informal collaboration of mathematicians and computer scientists Condor-G delivered 3. 46 E 8 CPU seconds in 7 days (peak 1009 processors) in U. S. and Italy (8 sites) 14, 5, 28, 24, 1, 3, 16, 15, 10, 9, 21, 2, 4, 29, 25, 22, 13, 26, 17, 30, 6, 20, 19, 8, 18, 7, 27, 12, 11, 23 Meta. NEOS: Argonne, Iowa, Northwestern, Wisconsin
Network for Earthquake Engineering Simulation n n NEESgrid: national infrastructure to couple earthquake engineers with experimental facilities, databases, computers, & each other On-demand access to experiments, data streams, computing, archives, collaboration NEESgrid: Argonne, Michigan, NCSA, UIUC, USC
Grid approach to address the High Energy Physics (HEP) computing problem
HEP computing characteristics n n n n Large numbers of independent events to process Large data sets, mostly read-only Modest floating point requirement Batch processing for production & selection - interactive for analysis Commodity components are just fine for HEP Very large aggregate requirements – computation, data The LHC challenge n Jump in orders of magnitude wrt. previous experiments n n Geographical dispersion of people and of resources Scale n n n n Petabytes per year of data Thousands of processors Thousands of disks Terabits/second of I/O bandwidth … Complexity Lifetime (20 years) …
World Wide Collaboration distributed computing & storage capacity CMS: 1800 physicists 150 institutes 32 countries
Solution? n Regional Computing Centres n n Serve better the needs of the world-wide distributed community Data available nearby Reduce dependence on links to CERN Exploit established computing expertise & infrastructure in national labs, universities See http: //www. cern. ch/monarc
~PBytes/sec Online System ~100 MBytes/sec ~20 TIPS There are 100 “triggers” per second Each triggered event is ~1 MByte in size ~622 Mbits/sec or Air Freight (deprecated) France Regional Centre Spec. Int 95 equivalents Offline Processor Farm There is a “bunch crossing” every 25 nsecs. Tier 1 1 TIPS is approximately 25, 000 Tier 0 Germany Regional Centre Italy Regional Centre ~100 MBytes/sec CERN Computer Centre Fermi. Lab ~4 TIPS ~622 Mbits/sec Tier 2 ~622 Mbits/sec Institute ~0. 25 TIPS Physics data cache Institute ~1 MBytes/sec Tier 4 Physicist workstations Caltech ~1 TIPS Tier 2 Centre Tier 2 Centre ~1 TIPS Physicists work on analysis “channels”. Each institute will have ~10 physicists working on one or more channels; data for these channels should be cached by the institute server
Grid as a possible approach n Various technical issues to address n n Resource Discovery Resource Management n n Data Management n n n Petabyte-scale information volumes, high speed data moving and replica, replica synchronization, data caching, uniform interface to mass storage management systems, … Automated system mgmt techniques of large computing fabrics Monitoring Services Security n n Distributed scheduling, optimal co-allocation of CPU, data and network resources, uniform interface to different local resource managers, … Authentication, Authorization … Scalability, Robustness, Resilience Grid model to address such problems
State (HEP-centric view) circa 2. 5 years ago n Globus project n n Globus toolkit: core services for Grid tools and applications (Authentication, Information service, Resource management, etc…) Good basis to build on but: n n No higher level services Handling of lots of data not addressed No production quality implementations Not possible to do real work with Grids yet …
Data. Grid Project (EDG) n n Project started Jan 2001, duration 3 years Goals n n Specific project objectives n n To build a significant prototype of the LHC computing model To collaborate with and complement other European and US projects To develop a sustainable computing model applicable to other sciences and industry: biology, earth observation etc. Middleware for fabric & Grid management evaluation, test, and integration of existing M/W S/W and research and development of new S/W as appropriate Large scale testbed Production quality demonstrations Open source and technology transfer See http: //www. eu-datagrid. org
Main Partners n CERN n CNRS - France n ESA/ESRIN - Italy n INFN - Italy n NIKHEF – The Netherlands n PPARC - UK
Associated Partners Research and Academic Institutes • CESNET (Czech Republic) • Commissariat à l'énergie atomique (CEA) – France • Computer and Automation Research Institute, Hungarian Academy of Sciences (MTA SZTAKI) • Consiglio Nazionale delle Ricerche (Italy) • Helsinki Institute of Physics – Finland • Institut de Fisica d'Altes Energies (IFAE) - Spain • Istituto Trentino di Cultura (IRST) – Italy • Konrad-Zuse-Zentrum für Informationstechnik Berlin - Germany • Royal Netherlands Meteorological Institute (KNMI) • Ruprecht-Karls-Universität Heidelberg - Germany • Stichting Academisch Rekencentrum Amsterdam (SARA) – Netherlands • Swedish Natural Science Research Council (NFR) - Sweden Industry Partners • Datamat (Italy) • IBM (UK) • Compagnie des Signaux (France)
Testbed Applications Middleware Testbed Infrastructure Applications Middleware Infrastructure Management The Management Working Group has in charge the coordination of the entire project on a day-to-day basis and the dissemination of the results among industries and research institutes. Infrastructure Management n The Applications Working Group exploits the project developments to process large amounts of data produced by experiments in the fields of High Energy Physics (HEP), Earth Observations (EO) and Biology. Middleware Management n The Infrastructure Working Group is focused on the integration of middleware software with systems and networks to provide testbeds to demonstrate the effectiveness of Data. Grid in production quality operations over high performance networks. Applications Management n The Middleware Working Group coordinates the development of the software modules leveraging, existing and long tested open standard solutions. Five parallel development teams implement the software: job scheduling, data management, grid monitoring, fabric management and mass storage management. Testbed n
Data. Grid Architecture Local Computing Grid Local Application Local Database Grid Application Layer Data Management Job Management Metadata Management Object to File Mapping Collective Services Information & Monitoring Replica Manager Grid Scheduler Underlying Grid Services SQL Database Services Computing Element Services Storage Element Services Replica Catalog Authorization Authentication and Accounting Service Index Grid Fabric services Resource Management Configuration Management Monitoring and Fault Tolerance Node Installation & Management Fabric Storage Management
Data. Grid achievements n Testbed 1: first release of EDG middleware n First workload management system n n n “Super scheduling" component using application data and computing elements requirements File Replication Tools (GDMP), Replica Catalog, SQL Grid Database Service, … Tools for farm installation and configuration … Used for real productions Towards testbed 2: new functionalities and increased reliability
dg-job-submit myjob. jdl Job submission scenario Myjob. jdl Executable = "$(CMS)/exe/sum. exe"; Input. Data = "LF: testbed 0 -00019"; Replica. Catalog = "ldap: //sunlab 2 g. cnaf. infn. it: 2010/rc=WP 2 INFN Test Replica Catalog, dc=sunlab 2 g, dc=cnaf, dc=infn, dc=it"; Data. Access. Protocol = "gridftp"; Input. Sandbox = {"/home/user/WP 1 test. C", "/home/file*”, "/home/user/DATA/*"}; Output. Sandbox = {“sim. err”, “test. out”, “sim. log"}; Requirements = other. Architecture == "INTEL" && other. Op. Sys== "LINUX Red Hat 6. 2"; Rank = other. Free. CPUs;
Other HEP Grid initiatives n n n PPDG (US) Gri. Phy. N (US) Data. Tag & i. VDGL n n Transatlantic testbeds (to address interoperability) LCG (LHC Computing Grid Project)
The Grid World: current status n n Dozens of major Grid projects in scientific & technical computing/research & education Considerable consensus on key concepts and technologies n n n Open source Globus Toolkit™ a de facto standard for major protocols & services Industrial interest emerging rapidly Opportunity: convergence of e. Science and e. Business requirements & technologies
Problems n n n Almost all projects have developed specialized services which have been layered on top of standard services (security, remote job execution, etc. ) Patchwork of protocols and noninteroperable “standards” and difficult to re-use “implementations” Exploit Web Services
Web Services n Increasingly popular standards-based framework for accessing network applications n n WSDL: Web Services Description Language n n XML-based RPC protocol; common WSDL target WS-Inspection n n Interface Definition Language for Web services SOAP: Simple Object Access Protocol n n W 3 C standardization; Microsoft, IBM, Sun, others Conventions for locating service descriptions UDDI: Universal Desc. , Discovery, & Integration n Directory for Web services
Open Grid Service Architecture (OGSA) n Service orientation n Computational resources, storage resources, networks, programs, databases, etc. all represented as services Allows standard interface definition mechanisms: multiple protocol bindings, multiple implementations, local/remote transparency Grid service: web service with semantic for service interactions n Management of transient instances (& state)
Global Grid Forum n Mission n To focus on the promotion and development of Grid technologies and applications via the development and documentation of "best practices, " implementation guidelines, and standards with an emphasis on "rough consensus and running code" An Open Process for Development of Standards n A Forum for Information Exchange n A Regular Gathering to Encourage Shared Effort n See http: //www. globalgridforum. org
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