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

2. 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. 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. 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. 5 Institute for Computational Research and Education for 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. 6 Organize to broaden and support use of applied mathematics and computation to deal with problems of increasing scale and complexity Modernize and optimize research facilities, computational clusters, and high performance Networks (the Campus Cyber-infrastructure) Leverage existing disciplinary research strengths and organize around multidisciplinary challenges (NIH - Center for Computational Biology being the most recent example) Organize to broaden and support use of applied mathematics and computation to deal with problems of increasing scale and complexity Leverage existing domain research strengths and organize around multidisciplinary challenges Institute for Computational Research and Education in Science, Engineering and the Arts Multidisciplinary Institutes DOE Lab of Structural Biology, PSTI, LONI, IGPP, CMISE, CNSI … Academic Departments Disciplinary Interests and Education Computer Science and Applied Math Campus Cyberinfrastructure Resources and Services through Academic Technology Services Institute for Pure and Applied Mathematics 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

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

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

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

10. 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. 11 Building on Existing Investment in Computational Infrastructure through ATS

12. 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. 13 Technical Support Faculty Researchers Industry Computational Resources Technology Sandbox Testing Prototyping Experimentation Benchmarking Trials Outcomes Published Outcomes Published A Sketch of the Organizational Landscape for Computational Research and Education at UCLA A starting point to encourage discussion and input! Dean’s Steering Council HSSEAS, LS, PS, SAA, SOM, TFT Computational Research Executive Committee (faculty from all disciplines across campus) VCR (Peccei) AVC (Davis) Director (CIRE) Director (OIT) Campus Computational Research Infrastructure New Technology for Research, Instruction and Productivity Chancellor’s Office CNSI - Data Center