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Concept and Rationale. The ideaSplit your program into bits that can be executed simultaneouslyMotivationSpeed, Speed, Speed at a cost effective priceIf we didn't want it to go faster we would not be bothered with the hassles of parallel programming!Reduce the time to solution to acceptable le

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1. COMP4300/COMP6430 Parallel Systems 2011 Richard Brent and Alistair Rendell School of Computer Science Australian National University

2. Concept and Rationale The idea Split your program into bits that can be executed simultaneously Motivation Speed, Speed, Speed… at a cost effective price If we didn’t want it to go faster we would not be bothered with the hassles of parallel programming! Reduce the time to solution to acceptable levels No point waiting 1 week for tomorrow’s weather forecast Simulations that take months to run are not useful in a design environment

3. Sample Application Areas Fluid flow problems Weather forecasting/climate modeling Aerodynamic modeling of cars, planes, rockets etc Structural Mechanics Building bridge, car, etc strength analysis Car crash simulation Speech and character recognition, image processing Visualization, virtual reality Semiconductor design, simulation of new chips Structural biology, molecular level design of drugs Human genome mapping Financial market analysis and simulation Datamining, machine learning Games programming!

4. World Climate Modeling Atmosphere divided into 3D regions or cells Complex mathematical equations describe conditions in each cell, eg pressure, temperature, velocity Conditions change according to neighbour cells Updates repeated frequently as time passes Cells are affected by more distant cells the longer range the forecast Assume Cells are 1x1x1 mile to a height of 10 miles, 5x108 cells 200 flops to update each cell per timestep 10 minute timesteps for total of 10 days 100 days on 100 mflop machine 10 minutes on a tflop machine

5. ParallelSystems@ANU: NCI/NF NCI: National Computational Infrastructure/National Facility History Establishment of APAC in 1998 with $19.5M grant from federal government, renewed in 2004 with a grant of about $29M programs in grid services, education and technology diffusion ANU currently hosts to a 1492 node Sun X6275 Constellation Cluster, each node has two quad core 2.93GHz Intel Nehalem CPUs giving a total of 11936 cores. The interconnect is QDR InfiniBand

6. ParallelSystems@DCS Bunyip: 192 processor PC Cluster winner of 2000 Gordon Bell prize for best price performance

9. Parallelisation Split program up and run parts simultaneously on different processors On N computers the time to solution should (ideally!) be 1/N Parallel Programming: the art of writing the parallel code! Parallel Computer: the hardware on which we run our parallel code! COMP4300 will discuss both Beyond raw compute power other motivations include Enabling more accurate simulations in the same time (finer grids) Providing access to huge aggregate memories Providing more and/or better input/output capacity

10. Parallelism in a Single “CPU” Box Multiple instruction units: Typical processors issue ~4 instructions per cycle Instruction Pipelining: Complicated operations are broken into simple operations that can be overlapped Graphics Engines: Use multiple rendering pipes and processing elments to render millions of polygons a second Interleaved Memory: Multiple paths to memory that can be used at same time Input/Output: Disks are stripped with different blocks of data written to different disks at the same time

11. Big Parallel Systems!

12. Health Warning! Course is run every other year Drop out this year and it won’t be repeated until 2013 It’s a 4000/6000 level course, it’s supposed to: Be more challenging that a 3000 level course! Be less well structured Have a greater expectation on you Have more student participation Be fun!

13. Learning Objectives Parallel Architecture: Basic issues concerning design and likely performance of parallel systems Specific Systems: Will make extensive use of NCI facilities Programming Paradigms: Distributed and shared memory, things in between, data intensive computing Parallel Algorithms: Numeric and non-numeric The future

14. Commitment and Assessment The pieces 2 lectures per week (30 core lecture hours) 6 Labs (not marked, solutions provided) 2 assignments (40%) 1 mid-semester exam (~2 hours, 20%) 1 final exam (3 hours, 40%) Final mark is sum of assignment, mid-semester and final exam mark

15. Lectures Two slots Mon 14:00-16:00 ENGN T Tue 15:00-16:00 ENGN T Exact schedule on web site Partial notes will be posted on the web site bring copy to lecture Attendance at lectures and labs is strongly recommended Attendance at labs will be recorded

16. Course Web Site We will use wattle only for lecture recordings

17. Laboratories Start in week 3 (March 7th) See web page for detailed schedule 2 sessions available Tue 09:00-11:00 N115/N116 Wed 16:00-18:00 N114 Register via streams now Not assessed, but will be examined

18. People Course Convener Richard Brent 2000 Moran Building Phone 6125 3873

19. Course Communication Course web page Bulletin board (forum – available from streams) At lectures and in labs Email In person Office hours (to be set – see web page) Email for appointment if you want specific time

20. Useful Books Principles of Parallel Programming, Calvin Lin and Lawrence Snyder, Pearson International Edition, ISBN 978-0-321-54942-6 Introduction to Parallel Computing, 2nd Ed., Grama, Gupta, Karypis, Kumar, Addison-Wesley, ISBN 0201648652 (Electronic version accessible on line from ANU library – search for title) Parallel Programming: techniques and applications using networked workstations and parallel computers, Barry Wilkinson and Michael Allen. Prentice Hall 2nd edition. ISBN 0131405632. and others on web page

21. Questions so far!?

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