The City University of New York

1. The City University of New York Campus of The City College of New York of The City University of New York

2. CUNY-Background • 19th Century • City College of New York • Established in 1847 as the “Free Academy”to provide tuition-free college education to all, based solely on merit, including the economically disadvantaged and those precluded from attending the leading universities of the day because of ethnicity or gender. • Hunter College • Established in 1870 as a tuition-free teacher-training school, based solely on merit, for young women. • Incorporated an elementary and high school for gifted children. • Twentieth Century • Expansion • “City University of New York” • Established in 1961 and incorporates the pre-existing City public colleges. • 23 Institutions. • End of free tuition as a result of NYC’s 1975 financial crisis (currently $4,000 per year at the senior colleges, $2,800 at the community colleges). • Tuition increases to $4,600 per year in 2009

3. CUNY-Background • Largest urban university in the United States. • Third largest university system in the United States. • 231,000 degree credit students. • 230,000 adult, continuing and professional education students. • Baruch College - largest School of Business in the U.S. • College Now • Academic enrichment program for 32,500 high school students. • Offered at CUNY campuses and more than 300 high schools. • University Teacher Academy • Free tuition for highly motivated mathematics and science majors who commit to teach in New York City. • Extensive Science, Technology, Engineering, and Mathematics and Louis Stokes Alliances for Minority Participation Programs.

4. Bernard Baruch, Financier Senator Barbara Boxer Sidney 'Paddy' Chayefsky, Author Alan M. Dershowitz, Lawyer Felix Frankfurter, US Supreme Court Justice Andy Grove, co-founder and former CEO, Intel Corp. Irving Howe, Literature Robert Kahn, Co-developer of TCP/IP General Colin Powell, former Commander, Joint Chiefs of Staff and Secretary of State Dr. Jonas Salk, Polio Vaccine Bernard L. Schwartz, former CEO, Loran Upton Sinclair, Author More CEOs and top executives in America graduated with first degrees from CUNY than any other degree-granting institution in the nation (Standard & Poors). 12 Nobel prize winners Many Pulitzer Prize Winners CUNY-Demographics

5. Decade of Science • Initiated in 2005 • Enhance CUNY’s position as a research university. • Hire 1,200 new faculty. • Upgrade research facilities. • Cyber Infrastructure/High Performance Computing Initiative.

6. CUNY HPC Center • College of Staten Island - 204 acre park-like campus • Free cruise on a 24x7 basis to Wall Street • 4,500 sq. ft computer room • $3 million allocated for facility renovation • 2.25 MW • Chilled water • Raised floor • $6.5 million allocated for design of a 90,000 square foot Computational Science Facility • 2014-15 planned completion • Expected to cost > $75 million Campus of the College of Staten island

7. Why GPUs? • Processor clock speed/computational performance CFP2006 year clock cfp2006 base • Woodcrest 2006 2.83 GHz 13 • Clovertown 2006 2.66 GHz 14 • Barcelona 2008 2.30 Ghz 17 • Harpertown 2008 3.16 GHz 24 • Nehalem 2009 2.93 GHz 36

8. Why GPUs-CUNY Perspective? • User Interest • “Older faculty” in physics and mathematics remember vectors • “I did that 20 years ago, I can do that” • Newer faculty have used CUDA and GP/GPUs on laptops and desktops • “Let me at it” • Faculty in the social sciences and biology need more computational power, but are not interested in complex programming exercises • Matlab (parallel Matlab and Parallel Matlab with CUDA extensions) • Mathematica (ditto) • R

9. Why GPUs? • Comparison of X86-64 and NVidia S1070 (preliminary) • X86-64 = Harpertown running at 3.16 GHz • One Tesla processors (240 cores) out of the four on the Nvidia S1070 1U board • CFD calculation - full Navier-Stokes • Used one X86-64 core and one Tesla processor • 5.8 times speed-up • Not fully optimized • Goal is a minimum of 10X over a single core

10. Why GPUs-User Perspective? • Scaling, for most applications, is not forever • CUDA is easier than MPI • Of course, we want to do both • Scaling with dense computation adds complexity, but for the right applications provides significant performance advantages

11. Why GPUs-System Management Perspective? • Scaling out • Adds dramatically to system management and interconnect network complexity • GPUs • Does not add to cluster OS adminstration/management complexity • Does not add to interconnect complexity • Plug-in and play • But, scheduling cores and Teslas adds complexity

12. HPC Infrastructure (Proposed Addition) • Configuration • 100 teraflops peak performance • 48 Intel X86-64 (Nehalem Core i7-960) nodes • 24 NVidia S1070 general purpose GPUs • Heterogeneous nodes • 96 sockets of Nehalem • 96 Tesla boards • PCIex-16 interconnect • Efficient support for scalable dense computational algorithms • Monte Carlo • Supported 3rd party applications • Parallel Matlab • Star-P • Parallel Mathematica • Others

13. Economics • Proposed Configuration • One Tesla per X86-64 socket • CFD application was not fully optimized • Have not worked on using all the cores on the X86 socket in this example • Given the above caveats, for this application, at its current state and extrapolating: • Adding one Tesla equates to adding 1.5 to 2.5 X86 sockets • Adding 96 Teslas to a 96 socket cluster only adds 25% to the cost of the cluster • No interconnect impact • No OS impact

14. Futures • Tighter integration between vectors/GPU and X86 architectures • More 64-bit floating point support in the GPU • Higher speed interconnects • Better, unified software support • Simplified computational capability