Computational Science and the School of Informatics at Indiana University IU/HBCU STEM Initiative IUPUI April 11 2007 Geoffrey Fox Computer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington.
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Computational Science and the School of Informatics at Indiana University IU/HBCU STEM Initiative IUPUI April 11 2007 Geoffrey Fox Computer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington IN 47401 [email protected] http://www.infomall.org What is Computational Science? Informatics is the integration of the art, science, and the human dimensions of information technology to provide solutions to discipline-specific problems Informatics is a response to the data/information/knowledge gaps (data deluge) caused by “billions and billions of bits” • Grids are technology supporting this in distributed research Computational Science could be the same as this or focus on the large scale simulation part Multicore chips will revitalize simulation! Bioinformatics Data Deluge Challenge and Opportunity 1985 2000 1 experiment 1 experiment 1 gene 10,000 genes 10 data 10,000,000 data e-moreorlessanything and the Grid ‘e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it.’ from its inventor John Taylor Director General of Research Councils UK, Office of Science and Technology e-Science is about developing tools and technologies that allow scientists to do ‘faster, better or different’ research Similarly e-Business captures an emerging view of corporations as dynamic virtual organizations linking employees, customers and stakeholders across the world. • The growing use of outsourcing is one example The Grid provides the information technology e-infrastructure for e-moreorlessanything. A deluge of data of unprecedented and inevitable size must be managed and understood. People, computers, data and instruments must be linked. On demand assignment of experts, computers, networks and storage resources must be supported Why Grids/ Cyberinfrastructure Useful Supports distributed science – data, people, computers Exploits Internet technology (Web2.0) adding management, security, supercomputers etc. It has two aspects: parallel – low latency (microseconds) between nodes and distributed – highish latency (microseconds) between nodes Parallel needed to get high performance on individual 3D simulations, data analysis etc.; must decompose problem Distributed aspect integrates already distinct components Cyberinfrastructure is in general a distributed collection of parallel systems Grids are made of services that are “just” programs or data sources packaged for distributed access Web 2.0 can be used “instead of” Grids TeraGrid: Integrating NSF Cyberinfrastructure Buffalo Wisc UC/ANL Utah Cornell Iowa PU NCAR IU NCSA Caltech PSC ORNL USC-ISI UNC-RENCI SDSC TACC TeraGrid is a facility that integrates computational, information, and analysis resources at the San Diego Supercomputer Center, the Texas Advanced Computing Center, the University of Chicago / Argonne National Laboratory, the National Center for Supercomputing Applications, Purdue University, Indiana University, Oak Ridge National Laboratory, the Pittsburgh Supercomputing Center, and the National Center for Atmospheric Research. Today 100 Teraflop; tomorrow a petaflop; Indiana 20 teraflop today and doubling APEC Cooperation for Earthquake Simulation ACES is a seven year-long collaboration among scientists interested in earthquake and tsunami predication • iSERVO is Infrastructure to support work of ACES • SERVOGrid is (completed) US Grid that is a prototype of iSERVO • http://www.quakes.uq.edu.au/ACES/ Chartered under APEC – the Asia Pacific Economic Cooperation of 21 economies Repositories Federated Databases Database Sensors Streaming Data Field Trip Data Database Sensor Grid Database Grid Research SERVOGrid Education Compute Grid Data Filter Services Research Simulations ? GIS Discovery Grid Services Customization Services From Research to Education Analysis and Visualization Portal Grid of Grids: Research Grid and Education Grid Education Grid Computer Farm SERVOGrid and Cyberinfrastructure Grids are the technology based on Web services that implement Cyberinfrastructure i.e. support eScience or science as a team sport • Internet scale managed services that link computers data repositories sensors instruments and people There is a portal and services in SERVOGrid for • Applications such as GeoFEST, RDAHMM, Pattern Informatics, Virtual California (VC), Simplex, mesh generating programs ….. • Job management and monitoring web services for running the above codes. • File management web services for moving files between various machines. • Geographical Information System services • Quaketables earthquake specific database • Sensors as well as databases • Context (dynamic metadata) and UDDI system long term metadata services • Services support streaming real-time data LEAD Gateway Portal NSF Large ITR and Teragrid Gateway - Adaptive Response to Mesoscale weather events - Supports Data exploration,Grid Workflow Grid Workflow Datamining in Earth Science NASA GPS Work with Scripps Institute Grid services controlled by workflow process real time data from ~70 GPS Sensors in Southern California Earthquake Streaming Data Support Transformations Data Checking Hidden Markov Datamining (JPL) Display (GIS) Some Organizations I work with • MSI CI2 Minority-Serving Institutions (MSI) Cyberinfrastructure Institute led by the • Alliance for Equity in Higher Education. Working with the Alliance will have systemic impact on at least 335 Minority Serving Institutions covered by the • AIHEC American Indian Higher Education Consortium) • HACU Hispanic Association of Colleges and Universities • NAFEO National Association for Equal Opportunity in Higher Education • MSI-CIEC Minority-Serving Institution Cyberinfrastructure (CI) Empowerment Coalition led by • UHD University of Houston Downtown as a major Hispanic Serving Institution • I am Senior Research Associate in the Center for Computational Science and Advanced Distributed Simulation at UHD and Visiting Scholar for Cyberinfrastructure Development at the Alliance for Equity in Higher Education Basic Ideas • Cyberinfrastructure is critical to all involved in Research and Education • Cyberinfrastructure is intrinsically democratic supporting broad participation • MSI’s should lead MSI integration with Cyberinfrastructure • One should guide the projects with experts • One should aim at scalable (systemic) approaches • Goal is peer collaborations involving all institutions of higher education Teaching Jackson State Fall 97 to Spring 2005 Syracuse JSU Example: Setting up a Polar CI/Grid • NSF CI-Team project with HBCU ECSU in North Carolina and Kansas University will design and set up a Polar Grid – CI Enable MSIs (ECSU Haskell) and a community (Polar Science) • The North and South poles are melting with potential huge environmental impact – We have changed the 100,000 year Glacier cycle into a ~50 year cycle; the field has increased dramatically in importance and interest • Polar Grid is a network of computers, sensors (on robots and satellites), data and people aimed at understanding science of ice-sheets and impact of global warming • We are planning Polar Grid relevant CI Education Infrastructure and initial projects with Undergraduate students (ECSU) and Graduate students (Kansas) – Polar weather stations as Grid resources – Use distance education to cover all CReSIS sites CReSIS PolarGrid • Important CReSIS-specific Cyberinfrastructure components include – Managed data from sensors and satellites – Data analysis such as SAR processing – possibly with parallel algorithms – Electromagnetic simulations (currently commercial codes) to design instrument antennas – 3D simulations of ice-sheets (glaciers) with non-uniform meshes – GIS Geographical Information Systems • Also need capabilities present in many Grids – Portal i.e. Science Gateway – Submitting multiple sequential or parallel jobs • TeraGrid etc. (the National Cyberinfrastructure) is having Cyberinfrastructure days at various places around country to popularize and identify how institutions can participate – ECSU will be later this year Indiana University Cheminformatics Center Summary Indiana University is focusing on two major areas: • Creating a comprehensive, easily accessible infrastructure for chemoinformatics tools and data sources, linked with PubChem and made available as web services, and partnering with screening centers and other users to demonstrate how this infrastructure can be usefully applied – Infrastructure can include any tools, not just ours (commercial/open source, chemoinformatics, bioinformatics, and so on) – New, custom applications can be built quickly using existing services in a similar way to Google Maps and other “web 2.0” resources • Being a central hub of chemoinformatics education, including offering distance courses on chemoinformatics theory and techniques, practical workshops on using chemoinformatics resources, and freely available webbased educational resources – We currently offer a Ph.D, M.S. and graduate certificate (distance) in chemical informatics – Distance education program allows you to “pick and choose” courses to meet educational needs: certificate is awarded on completion of four courses CICC Chemical Informatics and Cyberinfrastucture Collaboratory Funded by the National Institutes of Health www.chembiogrid.org CICC CICC Combines Grid Computing with Chemical Informatics Large Scale Computing Challenges Chemical Informatics is non-traditional area of high performance computing, but many new, challenging problems may be investigated. NIH PubMed DataBase Chemical informatics text analysis programs can process 100,000’s of abstracts of online journal articles to extract chemical signatures of potential drugs. OSCAR Text Analysis Initial 3D Structure Calculation Molecular Mechanics Calculations Cluster Grouping Toxicity Filtering Science and Cyberinfrastructure CICC is an NIH funded project to support chemical informatics needs of High Throughput Cancer Screening Centers. The NIH is creating a data deluge of publicly available data on potential new drugs. . Docking OSCAR-mined molecular signatures can be clustered, filtered for toxicity, and docked onto larger proteins. These are classic “pleasingly parallel” tasks. Topranking docked molecules can be further examined for drug potential. Quantum Mechanics Calculations NIH PubChem DataBase POVRay Parallel Rendering IU’s Varuna DataBase Big Red (and the TeraGrid) will also enable us to perform time consuming, multi-stepped Quantum Chemistry calculations on all of PubMed. Results go back to public databases that are freely accessible by the scientific community. CICC supports the NIH mission by combining state of the art chemical informatics techniques with • World class high performance computing • National-scale computing resources (TeraGrid) • Internet-standard web services • International activities for service orchestration • Open distributed computing infrastructure for scientists world wide Indiana University Department of Chemistry, School of Informatics, and Pervasive Technology Laboratories CICC Web Service Infrastructure Cheminformatics Services Statistics Services Database Services Core functionality Fingerprints Similarity Descriptors 2D diagrams File format conversion Computation functionality Regression Classification Clustering Sampling distributions 3D structures by CID SMARTS 3D Similarity Docking scores/poses by CID SMARTS Protein Docking scores Applications Applications Docking Predictive models Filtering Feature selection Druglikeness 2D plots Toxicity predictions Arbitrary R code (PkCell) Mutagenecity predictions PubChem related data by Anti-cancer activity predictions Pharmacokinetic parameters CID, SMARTS OSCAR Document Analysis InChI Generation/Search Computational Chemistry (Gamess, Jaguar etc.) Grid Services Varuna.net Quantum Chemistry Portal Services Service Registry Job Submission and Management Local Clusters IU Big Red TeraGrid, Open Science Grid RSS Feeds User Profiles Collaboration as in Sakai Varuna environment for molecular modeling (Baik, IU) Researcher Chemical Concepts Papers etc. ChemBioGrid Experiments Reaction DB QM Database PubChem, PDB, NCI, etc. DB Service Queries, Clustering, Curation, etc. QM/MM Database Simulation Service FORTRAN Code, Scripts Condor TeraGrid Supercomputers “Flocks”