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Supercomputing and Sciences Rong Ge Marquette University
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Supercomputing in plain English Personal computers and limited capability Supercomputers for solving scientific problems Supercomputing and speed Supercomputing for high school students Why should HS students care Supercomputing for HS in the country Roadmap
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Personal Computer Output device Input device Network cable
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Opening the Box
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Processor: control and ALU Memory Input Output Like human organs Five Classic Components
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Processor: number cruncher Speed: 2GHz-4GHz? Duo core or quad core? Memory: data storage 8GB? These hardware parameters largely determine how fast a computer is. Typical PC Configurations
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Are Long to compute Need large quantity of memory large quantity of runs Are Time Critical Not All Programs can Run on PC
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Slide 8 Example 2: Fluid dynamics calculations (1000 1000 1000 lattice) 10 9 lattice points 1000 FLOP/point 10 000 time steps = 10 16 FLOP Example 3: Monte Carlo simulation of nuclear reactor 10 11 particles to track (for 1000 escapes) 10 4 FLOP/particle = 10 15 FLOP Decentralized supercomputing ( from Mathworld News, 2006/4/7 ): Grid of tens of thousands networked computers discovers 2 30 402 457 – 1, the 43 rd Mersenne prime, as the largest known prime (9 152 052 digits ) Example 1: Southern oceans heat Modeling (10-minute iterations) 300 GFLOP per iteration 300 000 iterations per 6 yrs = 10 16 FLOP 4096 E-W regions 1024 N-S regions 12 layers in depth Exemplar Programs
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Physics and Astrophysics Biophysics Geophysics and Earth imaging Medical Physics and Medicine Chemistry and Biochemistry Chemical and nuclear reactions Weather and climate Mechanical devices - from prosthetics to spacecraft Manufacturing processes Traditional Scientific and Engineering Problems
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Top 1 in June 2012 Speed: 10 16 operations per second today Big: 4500 square feet Supercomputers
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Supercomputers in the Past Source: Jack Dongarra
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Source: Supercomputing in Plain English: Overview by Neeman at OU 12 Parallelism for Speed Less fish … More fish! Parallelism means doing multiple things at the same time: you can get more work done in the same time.
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Jigsaw analogy Person: CPU Jigsaw pieces: data in memory One person Serial computing, one hour Two persons Parallel computing, about a half hour Four persons A little more than a quarter hour Eight persons ? 13 Diminishing Returns Source: Supercomputing in Plain English: Overview by Neeman at OU 1000 jigsaw pieces
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Two person, each having on his own table with half of the puzzle pieces Two persons can work completely independently, without any contention for a shared resource. BUT, they need Same number of pieces first – workload decomposition and balance Communication, which is costly Supercomputing in Plain English: Overview Tue Jan 25 2011 14 Distributed Parallelism & Overhead
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Supercomputing in plain English Personal computers and limited capability Supercomputers for solving scientific problems Supercomputing and speed Supercomputing for high school students Why should HS students care Supercomputing for HS in the country Roadmap
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Tomorrow’s PCs may be today’s supercomputers During the past 10 years, the trends indicated by ever faster networks, distributed systems, and multi- processor computer architectures (even at the desktop level) clearly show that parallelism is the future of computing. Why Should We or Our Students Care Reason I
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Slide 17 CPU Performance The exponential growth of microprocessor performance, known as Moore’s Law, shown over the past two decades (extrapolated).
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Slide 18 CPU Speed Projection in 2001 From the 2001 edition of the roadmap [Alla02] Calendar year 200120042007201020132016 Halfpitch (nm)1409065453222 Clock freq. (GHz)247122030 Wiring levels78910 Power supply (V)1.11.00.80.70.60.5 Max. power (W)130160190220250290
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The Truth Microprocessor speed stops increasing around 2003 due to physical difficulties
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Multiple, slow cores on a chip Intel Up to 80 cores AMD Integrated CPU and GPU cores (50+ cores) nVidia Hundreds of GPU cores Parallel computing is required to achieve fast execution for a single program 20 The Resulting Multicore Processors
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1.Thousand years ago – experimental Science Description of natural phenomena 2.Last few hundred years – Theoretical Science Newton’s Laws, Maxwell’s Equation 3.Last few decades – Computational Science Simulation of complex phenomena 4.Today – Data intensive Science Scientists overwhelmed with data sets Reason II – Scientific Approaches
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Need to solve grand challenge problems with supercomputing Disaster preparedness Climate change Clean energy National security and defense Reason III: The Burden of Next Generation Scientists
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Particle Physics
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Swine Flu – Pandemic Flu Simulation
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NSF and DOE National supercomputing centers NCSA at UIUC San Diego supercomputer center the National Center for Supercomputing Applications Technical supercomputing conferences IEEE/ACM Supercomputing XSEDE conference Industry Intel Brings Parallel Computing to High School Supercomputing for HS Programs
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Supercomputing Organizations
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Marquette University Several computer clusters Guest accounts available Condor pool Technical help SeWhip: Southeast Wisconsin high performance computing Local Resources
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https://www.xsede.org/web/xup/online-training https://www.xsede.org/web/xup/online-training http://www.citutor.org/ http://www.citutor.org/ http://www.tacc.utexas.edu/user-services/training http://www.tacc.utexas.edu/user-services/training https://www.xsede.org/web/xsede12/students https://www.xsede.org/web/xsede12/students http://sc12.supercomputing.org/ http://sc12.supercomputing.org/ http://hpcuniversity.org/ http://hpcuniversity.org/ Online Training Opportunities
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Thank you
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