Intellectual Architecture

1. A Proposed Framework forComputational Research and Education at UCLA Intellectual Architecture Leverage existing domain research strengths and organize around multidisciplinary challenges Institute for Computational Research and Education in Science, Engineering and the Arts Opportunity for integration, growth, knowledge transfer, and new funding

2. Background • ASCI failed proposal ( ~ 7 years ago) • Continued to build strengths across campus in high-end computation and visualization • Growing interest in the campus to cooperate across disciplines through multidisciplinary centers and support of IT side of University with research enterprise • Growing interest in the campus to cooperate across disciplines through multidisciplinary centers • Increased interaction and support of IT side of University with research enterprise • Campus Faculty, Computational Research Advisory Board (CRAB), and the ITPB through its vision statement of “Research Leadership” got behind the effort

3. Significant momentum achieved by Spring 2004 Clear decision by HSSEAS and Physical Science Deans to commit significant resources Full willingness by Jim Davis and Marsha Smith to realign ATS to support the Institute Full buy-in for moving along this path by Life Science and School of Medicine Deans Enthusiastic support of SAA and TFT Deans- Seen as further enabling the Experiential Technology Center (ETC) and Media, Performance and Engineering Research Center (MPERC) Identification of Alan Laub as potential leader for initiative Clear indications of Federal Government willingness to invest in this area Background (cont.)

4. By December 2004, agreement from the Chancellor to proceed: Seed funding for 5 years Recruitment of the Director Begin the process of transition - the Institute, ATS and OIT CNSI space for the Institute Background (cont.)

5. Institute for Computational Research and Educationfor Science, Engineering and the Arts (working title) • A more detailed look at the Institute: • Elements of computational research and education which make UCLA a national leader • The Institute is responsive to: • new funding potential • UCLA trends in computational growth • Opportunity for integration, growth, knowledge transfer, and new funding

6. Elements of Computational Research and Education which make UCLA a National Leader • Build Upon Partnerships • S. Campus Deans - Eng., Phy. Sci., Med., Life Sci. • N. Campus Deans - A&A, TFT • VC Research and AVC of IT • CNSI - Data Center • ATS and OIT Multidisciplinary Institutes DOE Lab of Structural Biology, PSTI, LONI, IGPP, CMISE, CNSI… Academic Departments Disciplinary Interests and Education Leverage existing domain research strengths and organize around multidisciplinary challenges Leverage existing disciplinary research strengths and organize around multidisciplinary challenges (NIH - Center for Computational Biology being the most recent example) Institute for Computational Research and Education in Science, Engineering and the Arts Organize to broaden and support use of applied mathematics and computation to deal with problems of increasing scale and complexity Institute for Pure and Applied Mathematics Computer Science and Applied Math Organize to broaden and support use of applied mathematics and computation to deal with problems of increasing scale and complexity Campus Cyberinfrastructure Resources and Services through Academic Technology Services Modernize and optimize research facilities, computational clusters, and high performance Networks (the Campus Cyber-infrastructure)

7. Responsive to External and Internal Trends National priorities for most challenging problems UCLA IT Repositioning Initiative High-End Computing Revitalization Report (HECRTF - 5/10/04) Intellectual Architecture Multidisciplinary Institutes DOE Lab of Structural Biology, PSTI, LONI, IGPP, CMISE, CNSI… Academic Departments Disciplinary Interests and Education Leverage existing domain research strengths and organize around multidisciplinary challenges Institute Retention and transfer of software development knowledge A Science-Based Case for Large Scale Simulations (Office of Science, DOE 6/30/04) Institute for Pure and Applied Mathematics Computer Science and Applied Math Campus Cyberinfrastructure Resources and Services through Academic Technology Services Revolutionizing Science and Engineering through CyberInfrastructure (NSF Blue Ribbon Panel - 5/1/2002) Increasing demand for computation on campus (cycles and software tools)

8. Responsive to UCLA Trends in Computational Growth Computational Growth (GFLOPS)Past, Current and Projected Campus - 150% ATS - 940%

9. Offers Opportunity for Integration, Growth, Knowledge Transfer, and New Funding Multidisciplinary Vision Cross-campus Research Centers Academic Disciplines Education & Training Computational Research Algorithmic Development And Application New Technology Integration Data Structure and Access Parallel Code Optimization Core Infrastructure UCLA Research Enterprise Institute for Computational Research and Education for science, engineering, and the arts Academic Deans ATS Infrastructure

10. Aligning ATS with the Institute • Incorporates the philosophy of a campus wide resource: • Enable ATS to deliver computational resources and services to the campus not restrict them • Build on existing investments in computational infrastructure • Create a sustainable funding model

11. Building on Existing Investment in Computational Infrastructure through ATS VISUALIZATION PORTAL 160 X 40 degree Immersive Virtual Reality Theater WINDOWS NETWORK Campus Backbone, Internet, and Super Computer Centers SGI ONYX2 SGI Origin 3400 MODELING LAB Research Scholar Lab ATS GIGABIT ETHERNET BACKBONE Rendering Cluster HIGH PERFORMANCE STORAGE TECHNOLOGY SANDBOX SHARED STORAGE 3584L32 Tape Backup System 80 TB ArcGIS Oracle Server STATS LAB TSM Server GRID TEST Cluster 14 Nodes HOFFMAN Cluster 40 Nodes VIDEO SERVING Cluster Tivoli Identity Management System ISSR Storage HOSTED CLUSTERS: CMISE Cell Mimetic Space Exploration Cluster 14 Nodes CNSI Nano- Technology Cluster 24 Nodes MILES Functional MRI Cluster 8 Nodes MOLSIM Molecular Simulation Cluster 13 Nodes MIRTH SIMULATOR Earth Sciences Cluster 71 Nodes DALTON Chem Eng Cluster 8 Nodes NEUTRINO Theoretical Elementary Physics & Astronomy Cluster 24 Nodes DAWSON Plasma Physics Cluster 259 Nodes

12. What should the organizational structure be? • At local level, the governance of the Institute is relatively straightforward • Institute will be run by a Director • Institute will have an Executive Committee with broad representation across UCLA • Institute will also have an External Advisory Board, with members from the National Labs, industry, and other universities • Much more challenging is what to do at University level • must be partnership based (VCR, OIT, ATS, Institute) • must start with a transition period that allows for thoughtful input to make organizational changes that fully enable the Institute but also make sense for the campus

13. Outcomes Published Benchmarking Trials Faculty Researchers Computational Resources Technology Sandbox Testing Prototyping Experimentation Technical Support Industry A Sketch of the Organizational Landscape for Computational Research and Education at UCLAA starting point to encourage discussion and input! Chancellor’s Office VCR (Peccei) AVC (Davis) Dean’s Steering Council HSSEAS, LS, PS, SAA, SOM, TFT Computational Research Executive Committee (faculty from all disciplines across campus) Director (CIRE) Director (OIT) CNSI - Data Center Campus Computational Research Infrastructure New Technology for Research, Instruction and Productivity