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The City University of New York
11/19/2018 Campus of The City College of New York of The City University of New York November 19, 2018
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CUNY-Background 19th Century City College of New York Hunter College
11/19/2018 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 November 19, 2018
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CUNY-Background Largest urban university in the United States.
11/19/2018 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. November 19, 2018
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11/19/2018 CUNY-Demographics 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 November 19, 2018
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Decade of Science Initiated in 2005
11/19/2018 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. November 19, 2018
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Campus of the College of Staten island
11/19/2018 CUNY HPC Center College of Staten Island 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 planned completion Expected to cost > $75 million Campus of the College of Staten island November 19, 2018
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Why GPUs? Processor clock speed/computational performance
11/19/2018 Why GPUs? Processor clock speed/computational performance CFP2006 year clock cfp2006 base Woodcrest GHz 13 Clovertown GHz 14 Barcelona Ghz Harpertown GHz 24 Nehalem GHz November 19, 2018
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Why GPUs-CUNY Perspective?
11/19/2018 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 November 19, 2018
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Why GPUs? Comparison of X86-64 and NVidia S1070 (preliminary)
11/19/2018 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 November 19, 2018
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Why GPUs-User Perspective?
11/19/2018 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 November 19, 2018
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Why GPUs-System Management Perspective?
11/19/2018 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 November 19, 2018
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HPC Infrastructure (Proposed Addition)
11/19/2018 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 November 19, 2018
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Economics Proposed Configuration One Tesla per X86-64 socket
11/19/2018 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 November 19, 2018
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Futures Tighter integration between vectors/GPU and X86 architectures
11/19/2018 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 November 19, 2018
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