Supercomputing and Sciences

1. Supercomputing and Sciences RongGe Marquette University

2. Roadmap • 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

3. Personal Computer Output device Network cable Input device Input device

4. Opening the Box

5. Five Classic Components • Processor: control and ALU • Memory • Input • Output • Like human organs

6. Typical PC Configurations • 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.

7. Not All Programs can Run on PC Are Long to compute Need large quantity of memory large quantity of runs Are Time Critical

8. Example 1: Southern oceans heat Modeling (10-minute iterations) 300 GFLOP per iteration  300 000 iterations per 6 yrs = 1016 FLOP 4096 E-W regions 1024 N-S regions 12 layers in depth Exemplar Programs Example 2: Fluid dynamics calculations (1000  1000  1000 lattice) 109 lattice points  1000 FLOP/point  10 000 time steps = 1016 FLOP Example 3: Monte Carlo simulation of nuclear reactor 1011 particles to track (for 1000 escapes)  104 FLOP/particle = 1015 FLOP Decentralized supercomputing ( from Mathworld News, 2006/4/7 ): Grid of tens of thousands networked computers discovers 230402457– 1, the 43rd Mersenne prime, as the largest known prime (9 152 052 digits )

9. Traditional Scientific and Engineering Problems 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

10. Supercomputers • Top 1 in June 2012 • Speed: 1016 operations per second today • Big: 4500 square feet

11. Supercomputers in the Past Source: Jack Dongarra

12. Parallelism for Speed Parallelism means doing multiple things at the same time: you can get more work done in the same time. Less fish … More fish! Source: Supercomputing in Plain English: Overview by Neeman at OU

13. Diminishing Returns 1000 jigsaw pieces • 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 • ? Source: Supercomputing in Plain English: Overview by Neeman at OU

14. Distributed Parallelism & Overhead Supercomputing in Plain English: Overview TueJan 25 2011 • 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

15. Roadmap • 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

16. Why Should We or Our Students CareReason I 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.

17. CPU Performance The exponential growth of microprocessor performance, known as Moore’s Law, shown over the past two decades (extrapolated).

18. CPU Speed Projection in 2001 From the 2001 edition of the roadmap [Alla02]

19. The Truth Microprocessor speed stops increasing around 2003 due to physical difficulties

20. The Resulting Multicore Processors • 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

21. Reason II – Scientific Approaches • Thousand years ago – experimental Science • Description of natural phenomena • Last few hundred years – Theoretical Science • Newton’s Laws, Maxwell’s Equation • Last few decades – Computational Science • Simulation of complex phenomena • Today – Data intensive Science • Scientists overwhelmed with data sets

22. Reason III: The Burden of Next Generation Scientists • Need to solve grand challenge problems with supercomputing • Disaster preparedness • Climate change • Clean energy • National security and defense

23. Particle Physics

24. Swine Flu – Pandemic Flu Simulation

25. Supercomputing for HS Programs • 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

26. Supercomputing Organizations

27. Local Resources • Marquette University • Several computer clusters • Guest accounts available • Condor pool • Technical help • SeWhip: Southeast Wisconsin high performance computing

28. Online Training Opportunities https://www.xsede.org/web/xup/online-training http://www.citutor.org/ http://www.tacc.utexas.edu/user-services/training https://www.xsede.org/web/xsede12/students http://sc12.supercomputing.org/ http://hpcuniversity.org/

29. Thank you