Published on October 15, 2007
The SwissGrid Initiative: The SwissGrid Initiative Peter Kunszt Manager Swiss Grid Initiative EGEE Summer School Budapest, July, 2006 Peter Kunszt: Manager Swiss Grid Initiative, Swiss National Supercomputing Centre CSCS Manno EU Grid Projects, leading data management middleware development CERN, Geneva Doctorate in Theoretical Physics from the University of Bern Peter Kunszt Building the Science Database of the Sloan Digital Sky Survey, Johns Hopkins University Baltimore CSCS: CSCS Content : Content Swiss Grid Initiative Swiss Involvements in Grid Projects – challenges EGEE Swiss Bio Grid SEPAC Intelligent Scheduling System ISS Importance of Grids in General Beyond the Hype Strategies for Successful Grids Importance of National Grids Why is it necessary to have a national Grid Advantages and Disadvantages of participating in large projects Grid Computing in Switzerland – High Level Goals: Grid Computing in Switzerland – High Level Goals Resource Sharing: Pooling of Available Resources Excellent national network provided by national research network provider SWITCH Optimal usage of national resources Pooling of available resources at research institutions Harvesting cycles on as of yet unused resources (e.g. classroom PCs, cluster backfill queues) Grid Computing in Switzerland – High Level Goals: Grid Computing in Switzerland – High Level Goals Coordination: Building an Infrastructure Agreements on the usage of the available resources Coordinated support of the resources Sharing of tools and middleware Grid Computing in Switzerland – High Level Goals: Grid Computing in Switzerland – High Level Goals Collaboration: Enabling Scientific Discovery Coordinated application usage, thematic Grids Building a community Establishing a joint knowledge base Swiss Grid Initiative: Swiss Grid Initiative Taking care of coordinating and supporting national Grid projects. Point of contact for all Grid Projects Point of support for all Grid users and administrators Representation of Swiss Academic Research Interests In Europe Globally Towards the Industry The Swiss Grid Initiative: The Swiss Grid Initiative The Swiss Grid Initiative has been created to Provide support and expertise for the Swiss research community Promote connectivity and collaboration between disciplines and users, especially CS and ‘high-need’ applications Represent the interests of the national research community towards other national and EU Grid projects Get involved in joint multinational projects, help Swiss partners to get funding Interact with the industry in joint projects Continuously initiate thematic projects, including e-Science pilot studies Research and develop middleware components to fill gaps and to improve the services to the community and with the community Swiss Grid Initiative Focus: Swiss Grid Initiative Focus Support the End-User Enabling Relevant Scientific Discovery from Day 1 (no testbeds) Consulting about Gridification – not every project is suitable for the High Throughput Paradigm Seek new opportunities and initiate new projects Content : Content Swiss Grid Initiative Swiss Involvements in Grid Projects – challenges EGEE Swiss Bio Grid SEPAC Intelligent Scheduling System ISS Importance of Grids in General Beyond the Hype Strategies for Successful Grids Importance of National Grids Why is it necessary to have a national Grid Advantages and Disadvantages of participating in large projects EGEE and LCG: EGEE and LCG SEE PREVIOUS PRESENTATION FOR DETAILS European Grid Infrastructure for Enabling E-science Teaming up with the D-Grid in the DECH Federation Tier-ed model: Tier-ed model Swiss Partners: Swiss Partners CSCS – Swiss Supercomputing Centre SWITCH – Swiss Research & Edu Network CSCS SA1, NA2, NA3, NA4 Is an LCG Tier2 Site Support for Region and all of EGEE Analysis of Physics Data Biomed, Comp.Chemistry, EO applications Training, Education, Public Relations SWITCH: JRA1 Security Middleware: Next generation of Grid Certificates by integrating Shibboleth and PKI Challenges in EGEE: View of CSCS: Challenges in EGEE: View of CSCS Nontrivial Administration Steep learning curve to become ‘EGEE member’ Reporting, Deliverables, etc Substantial Communication Overhead Finding the right partner to communicate with Many bodies, forums, sometimes contradictory information It helps to be vocal – just trotting along silently will not help to improve the project Infrastructure: substantial effort To keep the site running To respond to updates Many things are not well automated Mean Time Between Failure very low (in Grid middleware) Complex System: Many things break in many ways Swiss Bio Grid: Swiss Bio Grid Swiss Bio Grid Applications: Swiss Bio Grid Applications Usage Patterns of different Applications Identified three classes of applications Short CPU jobs (Docking) Medium CPU + data exchange (Proteomics Pipelining) Data intensive (Mass Spectrometry MS; Systems Biology) Strategy: Address them in sequence, find commonalities Dengue docking project (see next slides) swissPIT (Protein Identification Toolbox) Project starting now Orphan Diseases: Dengue: Orphan Diseases: Dengue What does it take to make a drug?: 12 years of development, 802 mio US$ (DiMasi, J.A. et al. (2003) J Health Econ, 22, 151-185). 1 in 10‘000 NCE becomes a product (Heilman, R.D. (1995) Qual Assur 4(1) 75-9.) ‚Only‘ 20 years of Patent – 8 years to make money What does it take to make a drug? “In Silico” Drug Development: “In Silico” Drug Development Bioinformatics, data mining, visualization, simulations, modeling, and many algorithms, databases Screening of compounds: Screening of compounds Computational screening of small compounds to identify early drug candidates Dengue Docking project: Dengue Docking project Proof of concept for successful private-public partnership Biozentrum: in silico docking Novartis Institute for Tropical Deseases: In vitro/in vivo follow-up Novartis: drug development at cost Dengue Docking project: Dengue Docking project DOCK 5.1 Autodock 3.05 FlexX (SCAI/BioSolvIT) GLIDE(Schrödinger) NCI Diversity (2k) NCI DTP (200k) ZINC (2700k) 3D structure of targets NS5 Methyltransferase NS3 Protease GPE Envelope Glycoprotein NS3 Helicase Dengue NS5 Methyltransferase: Dengue NS5 Methyltransferase PDB 1R6A: Structure solved in complex with Ribavirin and AdoHCys 2' O-methylation of viral RNA (2nd capping step of type 1 RNA cap) Cofactor: SAM Deletion of SAM domain aborts viral replication in Kunjin (Koonin, 1993) Current Achievements of GRID-enabled Dengue Docking: Current Achievements of GRID-enabled Dengue Docking Completed Phase I SwissBioGrid Completed large-scale parameterization test using Autodock 3.0.5: >500‘000 docking runs, >38‘000h CPU time In vitro testing of predicted binders is underway at NITD Some initial candidates already in next phase Some challengs in grid adoption: Some challengs in grid adoption Compute resources are busy already Agree on dedicated compute time for grid projects PC Desktop grids: untapped resource Buy new clusters for your grid (not the idea) Non-intrusiveness Firewall exceptions Non-intrusiveness on PC Desktop grids: application level Application clearing: Security issues Numerical stability in heterogeneous environments Data model in bioinformatics different from HEP Applications need access to large databases or data sets Challenge: Heterogeneity: Challenge: Heterogeneity Very different resources at participating institutes Use ‘standard’ schedulers for clusters (Sun Grid Engine, LSF, PBS) Agree on a higher-level Grid scheduler Provide good documentation and bindings of the Grid scheduler to the predominant cluster schedulers Work on new bindings Here we are already quite advanced, can make good use of results of other projects – but still a long way to go! Challenge: Numerical stability : Challenge: Numerical stability Before: After: PDB: 3dfr Challenge: Security: Challenge: Security Sensitive data, data safety Rely on standards for Authentication and Authorization Network data channel encryption Encryption of distributed data on storage Distributed keys and algorithms for retrieval (n of m schemes) Not at all addressed yet; a lot of room for improvement Challenge: Legacy: Challenge: Legacy Licensed, proprietary, legacy code Solve the problem together with the software provider New licensing models for distributed computing (e.g. license servers don’t scale) Legacy support Recompilation if possible Emulators Virtual machines Virtual Machines may be the way forward for many of these applications – but not production quality yet, lot of research to be done; also a lot of room for improvement Challenge: User Interface: Challenge: User Interface Users don’t want to deal with Grid specifics Set up a Grid Portal Many portals exist, however almost none have a good application-specific interface for the users Proteomics Project addresses this: dedicated proteomics pipelining portal based on existing Grid portal technologies – work started now together with the Swiss Institute of Bioinformatics and SZTAKI using P-GRADE P-GRADE also addresses Legacy issues to some extent Data model for bioinformatics: Data model for bioinformatics Bioinformatics often requires operations on large amounts of data (100s of GB) Transparent versioning and provisioning of the correct data for the computation necessary Local caching of large datasets reduces network traffic DataProxy (ProtoGRID) Each job description requests data files. Identified by message digest and size Associated with a data-providing resource Data proxy transparently handles data reuirements Prior to execution, request or re-use from cache unique interface to data for application. Cached data is purged when necessary SEPAC: SEPAC SEPAC stands for South European Partnership for Advanced Computing SPACI consortium - University of Lecce - University of Calabria - Hewlett-Packard CILEA CSCS ETHZ UNIZH SEPAC Project Scope: SEPAC Project Scope Infrastructure and Technology oriented collaboration Exploration of technology and interoperability Application portfolio being built Building on another Grid Portal: the Grid Resource Broker from the Univ. of Lecce Intelligent Scheduling System ISS: Intelligent Scheduling System ISS Partners: CSCS, EPFL, EIA-FR Provide a middleware service allowing optimal placement and scheduling of applications on the Grid – submit to the most suited computer architecture based on resource and application monitoring Research-oriented project, exploiting new ideas for a scheduling approach (2 PhDs) ISS Details: Switch I S S First Testbed : EPFL Mechanics departement machines (clusters & single CPU machines) Second Testbed : Whole EPFL Third Testbed : EPFL + CSCS + EIA-Fr + ETHZ machines ISS Details Cost function includes monitoring data on machine status and application behaviour. Usage of Γ model. See http://pleiades1.epfl.ch/~rgruber/projects/iss.pdf Monitoring Data on machines and applications delivered by application monitoring and the service itself Actual job submission through existing Grid middleware Exemple : Integration of ISS into VIOLA/MSS/UniCORE Environment : Exemple : Integration of ISS into VIOLA/MSS/UniCORE Environment Team : CSCS, EPFL, EIA-Fr, FhG, JFZ And There Are More…: And There Are More… … Swiss Involvements in Grids CoreGrid: EPFL, CSCS, EIA-FR KnowARC project: University of Geneva DILIGENT: University of Basel EMBRACE: University of Lausanne, SIB Computational Chemistry Grid: University of Zurich … Content : Content Swiss Grid Initiative Swiss Involvements in Grid Projects – challenges EGEE Swiss Bio Grid SEPAC Intelligent Scheduling System ISS Importance of Grids in General Beyond the Hype Strategies for Successful Grids Importance of National Grids Why is it necessary to have a national Grid Advantages and Disadvantages of participating in large projects Are Grids Just a Hype?: Are Grids Just a Hype? Grids respond to a Paradigm Shift in Scientific Discovery Paradigm Shift from Individual Researchers to Collaborations Project driven research – joint work preferred over one-man shows Collaborations do achieve the most relevant results these days Need for Collaborative Computing Platforms Need for temporary Virtual Organizations to do work, share data and results and publish results Grids are here to stay All Grids?: All Grids? Successful Grids are measured by the success of their users Ease of use Ease of configuration Non-intrusiveness at participating sites Security Robustness Some Grids will Disappear Measure of Success: Measure of Success Users are producing scientific results Harnessing increased computing capacity Easy integration of applications – users can focus on their field instead of computing Number of Publications Complexity of applications We are not here yet New Projects WANT to use your Grid instead of building their own If people knock on your door that they want to work with you, you know you are successful Your Repository of Middleware is used by others You need robust, professionally documented, re-usable software Using Grid Service standards, interoperable Mandatory collaboration with other Grid projects and Universities Content : Content Swiss Grid Initiative Swiss Involvements in Grid Projects – challenges EGEE Swiss Bio Grid SEPAC Intelligent Scheduling System ISS Importance of Grids in General Beyond the Hype Strategies for Successful Grids Importance of National Grids Why is it necessary to have a national Grid Advantages and Disadvantages of participating in large projects National Grids: National Grids Scaling large multinational projects can only be done through a well-managed hierarchy Strategy of long-term infrastructures will follow the NREN model EU drives in this direction: building on national infrastructures Visible results of National Financing build the basis for EU funding Participating in Large Multinational Projects: ADVANTAGES: Participating in Large Multinational Projects: ADVANTAGES Being part of the game, enabling national users to play on the large international playground Access to a much larger infrastructure Ability to voice local interests to the large community Ability to focus on strengths, taking components from others Building expertise in large Grids Profiting from international funding Visibility of the national efforts on an international scale, raising the attractivity of the country Participating in Large Multinational Projects: DISADVANTAGES: In large multinational projects the large nations will dominate Many technological decisions are political and not baswed on quality Choice of middleware components Assigning development tasks to concurring teams Inefficiency of large projects Communication Overhead Meetings, conferences, telephones, emails... Internal arguments Need for Compromise – Slow Decision making Positioning inside a project very important Expertise Choice of partners inside the project Participating in Large Multinational Projects: DISADVANTAGES Links: Links SwissGrid Initiative: http://www.swiss-grid.org/ or http://www.gridinitiative.ch/ CSCS: http://cscs.ch/
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