Computational Science and Engineering Online

1. Computational Science and Engineering Online Computational Science and Engineering Online Thanh N. Truong University of Utah Julio Facelli University of Utah Tom Cheatham University of Utah James Lewis Brigham Young University Supported by:National Science Foundation - Information Technology Research

2. NSF Blue Ribbon Advisory Panel on Cyberinfrastructure “a new age has dawned in scientific and engineering research, pushed by continuing progress in computing, information, and communication technology, and pulled by the expanding complexity, scope, and scale of today’s challenges. The capacity of this technology has crossed thresholds that now make possible a comprehensive “cyberinfrastructure” on which to build new types of scientific and engineering knowledge environments and organizations and to pursue research in new ways and with increased efficiency.” • http://www.cise.nsf.gov/sci/reports/toc.cfm

4. Report to the President – June 2005 Computational science is now indispensable to the solution of complex problems in every sector, from traditional science and engineering domains to such key areas as national security, public health, and economic innovation…. Yet, despite the great opportunities and needs, universities and the Federal government have not effectively recognized the strategic significance of computational science in either their organizational structures or their research and educational planning. These inadequacies compromise U.S. scientific leadership, economic competitiveness, and national security. Respond: Creation of the Office of Cyber-Infrastructure in NSF

5. MISSION To provide an online extendable integrated Grid enabled cyber-infrastructure for research, collaboration, and education in computational science and engineering. --- A step in the right direction Computational Science and Engineering Online (CSE-Online): A Cyber-Infrastructure for Scientific Computing Truong, T. N.; Nayak, M.; Huynh, H. H.; Cook, T.; Mahajan, P.; Tran, L. T.; Bharath, J.; Jain, S.; Pham, H. B.; Boonyasiriwat, C.; Nguyen, N.; Andersen, E.; Kim, Y.; Choe, S.; Choi, J.; Cheatham, T. E., III; Facelli, J. C.J. Chem. Inf. Model;46 (2006) 971;

6. File Systems Storage Packaging Interconnect Adaptive Computing The Users CSE-Online Transparent Interface Applications Transparent Interface Adaptive System Software Operating System Optimized Performance Multiple Processor Technologies ScalableSystemInfrastructure Adapt the system to the users – not force the users to adapt to the system

7. GOALS • To create an extendable integrated, user-friendly, problem solving environment to empower individuals and groups to perform research more effectively and to facilitate multi-disciplinary research on multi-scale complex problems in computational science and engineering. • To provide secure and simple access to state-of-the-art application tools and to remote private data sources and shared data repositories or libraries. • To provide simple and secure access to both local and grid computing resources. • To enable reliable and real-time visualization, data analysis, and information extraction from remote data sources and libraries. • To enable communication between users; thus to facilitate collaborations and training. • To promote the participation of different domain disciplines by enforcing the inter-operability of the software architecture and to provide seamless interfaces between application domains. • To ensure broad acceptance and usage by different scientific communities.

8. Knowledge Management System Material Science Solid-State Physics Molecular Mechanics Quantum Chemistry Thermo- dynamics Bio- Molecular Modeling Computational Fluid Dynamics Reaction Engineering Bio- Informatics Kinetics Application Software Platform

9. ROADMAP

11. Component-based system • Software architecture: Desktop Environment of a Remote Unix System (DERUS) • Online, Integrated, and Secure • Multi-layer Knowledge Management System • Adaptable software architecture • Public databases – PDB, Combustion Mechanisms, • Prototype private DB layer • Visualization/Analysis Tools • Converted to Java Open GL for graphics to enable real-time visualization of remote data sources • BioViewer, PsiViewer, CrystalViewer • Pandora, Spreadsheet • Communication/Collaboration • Text/Audio chat – CSEO Messenger

12. CPU User B Desktop Environment of the Server System 1 Server OS User Accounts and Directories System 2 System 3 CPU User A Desktop Environment of the Server System 4 CPU Computers that are connected to the computing grid Comp. 1 Comp. 3 Comp. 2 Computers that are locally connected to the server Desktop Environment of Remote Unix/Linux Server (DERUS)

13. User CPU Public DB Grid User Desktop Environment Server HDD Database GUI Prog. 1 Prog. 2 File Manager Server DB Local HDD Resource Manager GUI Computer Cluster connected to the server Computing Grid Server OS Server CPU DERUS

15. Problems with DERUS • Extensibility -- difficult • Adaptability – very little • Difficult for 3rd-party developers to incorporate their tools into DERUS • No concurrent access to multiple remote servers • Collaboration – difficult

16. Technology Definition Java On-Demand Application Framework (JODAF) for the Software as a Service (SaaS) model

17. Current Pitfalls of SaaS technology • Availability • Performance issues • Security challenges • Hype due to over-expectation • Integration/Interoperability problems

18. JODAF Innovation • Availability • Applications from more than one provider (i.e. host server) can be delivered to the user virtual desktop environment. • Performance Issues • Balancing the load between the client and server to enhance performance and stability with respect to network interruptions. • Security Challenges • Independent of the Web Browser, using secure connections, and assuming any application could be malicious. • Hype due to over-expectation • Delivering a robust working SaaS model • Integration/Interoperability problems • JODAF is a hybrid model allowing integration of legacy applications with SaaS solutions.

19. New architecture The Users Online On Demand Application Framework SSH SOA Applications System Software Computing Infrastructure

20. Online On Demand Application Framework

22. Benefits of the new architecture • Scalable, Extendable, Secure, Platform independent • Online On-Demand Application Framework for distributed applications and data • Merging individual work and collaborative environments into the same cyber-space to create a new coopetitive research environment • Introducing an online software registry and repository • On-demand user customizable cyber workspace – virtual enterprise system • Simple adaptability for 3rd-party applications • One time user installation. No server installation is required. Making Network Computing Transparent

23. Which is an Optimal Research Environment? Coopetitive Cooperative Collaborative Environment Competitive Collective Farming Olympics Intel+Micron  IM Flash Technologies Example Variable Positive Sum Positive Definite Sum Rule Zero Sum “You have to compete and cooperate at the same time” ----‘Coopetition’ Ray Noorda, CEO Novell

24. http://cse-online.net

25. GUI Wendell Duncan Ha Pham Hoang Phung VISUALIZATION Seungkeol Choe Evan Andersen Shophia Han GRAPHIC DESIGN Phil Nguyen Framework Tom Cook GRID COMPUTING Ronald Price Wayne Bradford DATABASES Priya Mahajan Yong Kim Web Master Son Duong COMMUNICATION Jihoon Choi ADVISORY BOARD CHEMISTRY Jack Simons Jeff Nichols Ellen Stechel REACTION ENGINEERING Adel Sarofim Max Tirtowidjojo Phil Smith COMPUTATIONAL BIOLOGY Monte Pettitt COMPUTER SCIENCE Martin Berzins Gary Lindstrom Monte Pettitt DIRECTOR Thanh N. Truong COMPUTING INFRASTRUCTURE Julio Facelli EDUCATION/COLLABORATION Thanh N. Truong RESEARCH Thanh N. Truong CHEMISTRY Thanh N. Truong Hoa G. Nguyen MATERIAL SCIENCE James Lewis Hao Wang Brandon Keith COMPUTATIONAL BIOLOGY Tom Cheatham Jingfa Xao REACTION ENGINEERING Thanh N. Truong Lam K. Huynh PROJECT MANAGER Manohar Nayak

26. THANK YOU