University of Virginia Alliance for Computational Science & Engineering

1. University of Virginia Alliance for Computational Science & Engineering January 2008

2. thoughts • Goals • Success metrics • Non-goals • Strategy • Tactics • Management • Operations • Faculty advisor BOD • Resources • Equipment • People • Support

3. Goals • Support sponsored computational science research in Virginia • Change the culture of computation • Education/outreach/curriculum • Be the place in Virginia for HPC – be a statewide resource • Foster a multi-disciplinary ethos • Assist ITC/UVA/the schools in planning, managing, and acquiring computational resources • Rationalize high-end computing

4. Success Metrics • Codes ported • Number of users of HPC • Science done – papers that result • Increase in research budgets associated with computational science

5. Non-goals • Build or manage a big machine for massive macho flops

6. Strategy • Engage university management • we need resources and policy backing • Engage the departments and schools • SOM, SEAS, CLAS, ED, all have a role, e.g., SOM bioinformatics core, ACHS, • Both in research support and in curriculum • in particular computer science • Be proactive: go to the researchers, don’t wait for them to show up. • Integrate and partner with the NSF and DOE centers

7. Tactics • Tiger teams • Send experts to work with research groups to both parallelize their codes – and to help them plan and structure their codes • Understand our community • Gather usage statistics on clusters throughout uva • Interview users: type of problem, scope of required resources, impact if successful • Leverage national resources • Assist our users in paperwork associated with national centers, and porting their codes/scripts • Education/outreach • Bootcamps • Faculty outreach • Curriculum development and integration • Leverage local resources

8. Management • Faculty should have major role – they are the customers • Current HPC group may be good start • Policy issues (for the queues) should be driven by faculty, not by staff • Faculty should set policy, direction, and approve initiatives • Grimshaw/Hawley lead effort

9. Resources • Short-term • Ed and Katherine • I could provide one or two graduate students for tiger team work if they are funded • I know some very good ugrads we could try and capture • ACHS? • SOM bio-informatics core • Long term (see ITRTF document) • Full time professional staff FTE • Department faculty slots in CSE

10. Immediate steps • Redirect Katherine and Ed to going out to the departments, interested research groups, and bootcamp participants to find tiger team projects of 3-6 month duration. Recent economics project a good model. Write up each. • Meet with them at least weekly until the projects are settled, then bi-weekly. • Ed ramps up curriculum synchronization efforts • OPPORTUNITY – CS is restructuring CS 101 • Audit/catalog clusters on grounds • Attempt to integrate under PBS? • Assess current usage patterns • Make public PC’s available for high-throughput computing via Genesis II.

11. Computational Science in Computer Science • ----- Full --------- • Jack Davidson – optimizing compilers • Andrew Grimshaw – HPC and Grid • Anita Jones – former DDR&E, importance of computational science • Paul Reynolds – simulation & HPC • Mary Lou Soffa – optimizing and parallelizing compilers • Bill Wulf – former NAE President, importance of computational science • ---- Associate ---- • Kevin Skadron – multicore architecture • --- Assistant ------- • Sudhavna Gurumuthri – parallel IO • Kim Hazelwood – optimizing and parallelizing compilers • Marty Humphrey – Grid • Greg Humphries – parallel graphics • Wes Weimer – program annotations (including parallelism)