/ 1W. Sudholt, K. Baldridge Swiss Grid Day, Geneva Grid Computing for Computational Chemistry and Beyond Wibke Sudholt 1 and Kim Baldridge 1,2 1 Institute of Organic Chemistry, University of Zurich, Switzerland 2 San Diego Supercomputer Center, University of California, San Diego, USA

/ 2W. Sudholt, K. Baldridge Overview Why do we use Grid Computing to answer scientific questions? How are we involved in Grid Computing? What can we do to support users to apply Grid Computing? How does Grid Computing help us to solve real- world problems?

/ 3W. Sudholt, K. Baldridge Towards a Global Cyberinfrastructure Workstations and PCs Supercomputers and clusters Internet and grids Computing Storage Instruments Networking Collaboration Information

/ 4W. Sudholt, K. Baldridge Interdisciplinary Research Mathematics Physics Chemistry Biology Computer Science Computational Chemistry

/ 5W. Sudholt, K. Baldridge Bridging Scientific Gaps Atoms Molecules Proteins Cells Organs Organisms Nuclei m m m m m 10 0 m m Accuracy Complexity Quantum mechanics Classical mechanics

/ 6W. Sudholt, K. Baldridge Grid Computing “A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.” Foster/Kesselman, 1999 Grid types: -Computational Grids -Desktop Grids -Data Grids -Knowledge Grids Grid opportunities: -Performance -Throughput -Scalability -Fairness -Collaboration -Knowledge exchange and dissemination Grid challenges: -Heterogeneity -Network speed -Fault tolerance -Distribution algorithms -Job scheduling -Legacy codes -Policy issues

/ 7W. Sudholt, K. Baldridge Grid Infrastructure Layers Applications Upper-level middleware Resources User interfaces Web portals Resource brokers Workflow systems Lower-level middleware Security infrastructure Resource management Information services Data management Scientific or business software Scientific or business data Visualization Network Job managers Operating systems Hardware

/ 8W. Sudholt, K. Baldridge Baldridge Group Hardware Chempossible cluster at SDSC Individual resources Grid resources Y. Potier, M. Packard, W. Sudholt, UniZH, et al. Mac laptops Matterhorn cluster at UniZH

/ 9W. Sudholt, K. Baldridge Grid Middleware Experience Cluster management: -Rocks -SGE Open source or freeware: -Globus -Nimrod -ProActive -UNICORE -Condor -BOINC -GridPort -SRB -Web services Commercial products: -DataSynapse -United Devices Workflow infrastructures: -Kepler -Informnet Security: -CA -GAMA

/ 10W. Sudholt, K. Baldridge Virtual Organizations Swiss Grid Initiative: Swiss Bio Grid (SBG): Southern European Partnership for Advanced Computing (SEPAC): Pacific Rim Applications and Grid Middleware Assembly (PRAGMA): Chemomentum: I2CAM:

/ 11W. Sudholt, K. Baldridge Computational Chemistry Grid User Interfaces Molecular visualization and remote execution (K. Baldridge, J. Greenberg, SDSC): -QMView GridPort web portals (J. Greenberg, SDSC, et al.): -GAMESS -APBS -Euler -AMBER -CE Workflow and integrated infrastructure projects (UniZH/SDSC): -Resurgence -Gemstone

/ 12W. Sudholt, K. Baldridge The Resurgence Project RESearch sURGe ENabled by CyberinfrastructurE Description: -Workflow tool for computational chemistry -Allow researchers to easily combine existing computational chemistry tools in innovative ways -Exploit the possibilities of the growing web and grid infrastructure -Focus on high-throughput calculations -Based on and included in the collaborative Kepler scientific workflow system Interfaced programs: -GAMESS (quantum chemistry), Babel, Open Babel (file format conversion), QMView (molecular visualization) -In preparation: Nimrod/G (grid distribution) -Planned: APBS (biomolecular continuum electrostatics) Participants: -UniZH/ETHZ: W. Sudholt et al. -SDSC: I. Altintas et al. Status: -Project has ended -Many ideas to be taken over into the Gemstone framework

/ 13W. Sudholt, K. Baldridge The Gemstone Project Grid Enabled Molecular Science Through Online Networked Environments Goals: -Integrated framework for accessing grid resources -Support scientific exploration, workflow capture and replay, and a dynamic services oriented architecture -Provide researchers in the molecular sciences with a tool to discover and compose remote grid application services Components: -Dynamic rich-client desktop interface (Firefox extension, XUL, registry lookup) -Strongly typed data schemas (XML Schema, CML, GamessXML) -Molecular visualization tools (Flash, Garnet, interface to QMView) -Optional: Authenticated interaction (GAMA) -Planned: Workflow integration (Informnet) Application web services: -APBS, GAMESS, Autodock, SIESTA codes -MolPrep, Babel, PDB2PQR, Psize utilities Related and interfaced projects: -Opal: Web services wrapping toolkit -Topaz: GridFTP Firefox extension Status: -Ongoing NSF and NBCR-supported project -Version 1.0 released on Participants: -UniZH: K. Baldridge, C. Amoreira, A. Bowen, Y. Potier et al. -SDSC: K. Bhatia, J. Greenberg, S. Krishnan, S. Mock, B. Stearn et al.

/ 14W. Sudholt, K. Baldridge Example Computational Chemistry Grid Projects and Collaborations Parameterization of a Group Difference Pseudopotential for QM/MM calculations using GAMESS and the Nimrod distributed parametric modeling tool (W. Sudholt, UCSD/UniZH/ETHZ, D. Abramson, Monash, et al.) Coupling of the GAMESS quantum chemical code with the BOINC desktop grid platform (M. Taufer, UCSD/UTEP, et al.) Investigation of protein-ligand interactions based on a GAMESS and APBS pipeline using Nimrod and Gemstone on the PRAGMA testbed (C. Amoreira, UniZH, et al.) Implementation of the material science application SIESTA into the Gemstone framework (A. Garcia, UPV/ICMAB, Spain)

/ 15W. Sudholt, K. Baldridge Parameterization of a Group Difference Pseudopotential Challenge: -Parameterization of a pseudopotential for QM/MM calculations -Embarrassingly parallel parameter sweeps and optimizations Setup: -GAMESS quantum chemistry code (pre- deployed) -Globus and Nimrod grid middleware -PRAGMA testbed resources (mainly at the PRAGMA 4 and Supercomputing 2003 conferences) Results: -Up to about 60’000 jobs -More than 200 days of computing time in less than 48 hours real time -Parameterized group difference potential - personal/pubs.htmlhttp:// personal/pubs.html Participants: -UCSD/UniZH/ETHZ: W. Sudholt -Monash University, Australia: D. Abramson, C. Enticott, S. Garic

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/ 17W. Sudholt, K. Baldridge Collaborative Research Project with Swiss Re NatCat application: -Probabilistic modeling of losses for insurance portfolios from natural catastrophes (earthquakes, tropical cyclones etc.) based on pre-simulated events at specific locations -Java sources, Oracle database, test cases Goals: -Distribution of main Rate process over a computational grid -Improvement of performance, scalability, stability, and fairness -Testing of the DataSynapse GridServer and INRIA ProActive grid middleware tools Results: -Distribution over a number of Linux machines by an event set-based algorithm -Performance considerably improved -Database access represents bottleneck -Some results already in production version -Currently working on improving the distribution algorithm Participants: -Swiss Re: M. Spühler, P. Pfister et al. -UniZH: W. Sudholt, M. Packard, H. Mahmood, M. Dänzer, M. Monroe, K. Baldridge

/ 18W. Sudholt, K. Baldridge Summary Conclusions: -Grid computing is important for our domain-specific as well as our computer science research and has helped us to establish new local and international collaborations. -Our group and coworkers now have a lot of experience in grid computing including project participation and organization, infrastructure setup, software development, and application to scientific problems. -By developing grid user interfaces, we try to make grids easier accessible for the domain scientists. -We are building a record of grid projects in computational chemistry and also reach out to new fields, concepts, and collaborations. -Grid computing still requires a lot of effort, but the future is bright if we learn from the successes and failures, are aware of the limits, have clearly defined needs and goals, and do not reinvent the wheel. Thanks for funding: -UniZH, UCSD, SDSC, NSF, DAAD, ETHZ, EU, Swiss Re and others Swiss Grid Initiative: -This is an important initiative, and we are interested in participating. -We could provide our open source software and expertise. -We would contribute personnel and hardware resources only for well-defined, collaborative, and financed projects. -We expect knowledge exchange and dissemination, new collaborations, access to resources and funding, and not much organizational overhead. -This has to be a win-win situation with mutual trust, clear goals, and freedom for research.