1. Dr. Virendrakumar (Virendra) C. Bhavsar
Supercomputing
Dr. Virendrakumar (Virendra) C. Bhavsar
Professor
Faculty of Computer Science
University of New Brunswick (UNB)
Fredericton, Canada

2. Outline Definitions Applications Hardware Software Current Status
University of New Brunswick
Future 2 2

3. Definitions Computing Supercomputing
- A supercomputer is a computer that is at the frontline of current processing capacity, particularly speed of calculation.
High Performance Computing (HPC)/High Productivity Computing
- supercomputing - a subset of HPC
Parallel Computing
many calculations are carried out simultaneously
10**6 Million, 10**9 Billion, 10**12 Trillion

4. Human Brain 10**10 Neurons 10**4 Fan-in
Wires much slower than chips
Millions of times more volume
10**14 Inputs (Connection strngths
10**12 Connection strengths can affect processing in 5 msec
Lower bound on the computational power of brain
~ 10**10 neurons, 10 spikes/sec, 10**14 connections
~10**15 operations/sec or 10**18 bits/sec 4 4

5. Connection Machine CM-2
65K Processors,
5 CM-2 = 1.8 x 10**13 bits/sec
10**5 times slower than brain 5 5

6. Early Computers
1950: 5,000 operations/sec; : 1 Million Operations/sec

7. Advances in Microprocessor Technology
MHz clock
1988 – 40 MHz
2002 – 2 GHz
2009 – P4 3.0 GHz, Quadcore 2.66 MHz
Intel Montecito chip
1.72 Billion transistors
NVidia 280 series GPU 1.4 Billion transistors
Circuit complexity doubles every 18 months
 Computing power at a given cost doubles every 18 months
- Processor clock rates: 40% increase/year + more instr./cycle
- DRAM Access Times: 10% increase/year  caches required 7 7

8. Applications Grand Challenge Applications
cannot be solved in a reasonable amount of time with today's computers
Environment, Ecosystems, Molecular engineering, cognition, weapon design, Artificial Intelligence,
(near) Real-Time Applications
Military/Defense Applications
Space
Financial Forecasting; Live data (e.g. online stock market data)

9. Applications (near) Real-Time Applications Google
Software as a Service (SaaS) delivery model
ATMs, online banking
Data Intensive Applications
Walmart – inventory management
Data Mining 9 9

10. Applications Computational Modeling and Simulation
Science, Engineering, Social Sciences, …
Parameter sweep applications
Animation and Movies 10 10

11. Applications Compute Intensive Applications Massive Data applications11 11

12. Applications Capability Computing
- Using the maximum computing power to solve a large problem in the shortest amount of time
Capacity computing
Using efficient cost-effective computing power to solve
somewhat large problems
- many small problems 12 12

13. Supercomputer Design Challenges
Cooling
Speed of Light
Compute Bound Problems  I/O Bound problems 13 13

14. Supercomputer Technologies
Pipelining and Vector Processing
Parallel and Distributed Processing
Liquid Cooling
Non-Uniform Memory Access
Striped Disks (RAID)
Parallel File System 14 14

15. Parallel and Distributed Algorithms
Intrinsic parallelism
Design of parallel algorithms
Analysis of parallel algorithms 15 15

16. Programming PVM and MPI – Loosely connected clusters
OpenMP for Shared Memory Machines 16 16

17. Automatic Parallelization
Compilers
Limited success
Application Checkpointing 17 17

18. Current Supercomputer Roadrunner applications
National Security
Planet: Earth and Environmental Sciences
e.g. ground water modeling
Health: Biology, Chemistry, Life Sciences
Science: Engineering, Technology
Universe: Astronomy, Space, Astrophysics
- Modeling the decay of the US nuclear arsenal 18 18

19. Current Supercomputer
Roadrunner
Los Alamos National Laboratory, Los Alamos, NM, USA
>1 Petaflop (Quadrilion): million billion (10**15) floating-point operations/sec (FLOPS)
1.71 Petaflop peak
Weight - 500,000 pounds
Power - 4 Mega Watt
Space – 6000 square feet
Cabling 57 miles 19 19

20. Current Supercomputer
Roadrunner (Installation Year – 2008)
Los Alamos National Lab, USA
~ 3,250 compute nodes
Compute Node: Two AMD Opteron dual-core microprocessors
Each of the Opteron core: Internally attached to one of four enhanced Cell microprocessors.
Enhanced Cell: double-precision arithmetic faster and can access more memory than can the original Cell in a PlayStation 3. The entire machine will have almost 13,000 Cells and half as many dual-core Opterons.
Interconnection Network: off-the-shelf Infiniband 20 20

21. Current Supercomputer
Roadrunner (Installation Year – 2008)
DOE/NNSA/LANL
System Family - IBM Cluster
System Model - BladeCenter QS22 Cluster
Computer - BladeCenter QS22/LS21 Cluster, PowerXCell 8i 3.2 Ghz / Opteron DC 1.8 GHz , Voltaire Infiniband
Operating System - Linux
Interconnect – Infiniband
Processor - PowerXCell 8i 3200 MHz (12.8 GFlops) 21 21

22. Hardware: Building Blocks
Building blocks – processors, memory, interconnection networks
Processors
Memory – main and secondary storage
Interconnection networks 22 22

23. Hardware: Architectures
Taxonomy: SISD, SIMD, MISD and MIMD
Shared Memory Processing versus Distributed
Memory Processing
Symmetric Multi-Processing (SMP) versus Non-Uniform Memory Access (NUMA)
Processors
Clusters 23 23

24. Special Purpose Supercomputers
Specially Programmed FPGA chips
Custom VLSI Chips
Reconfigurable Computing
GPUs (Graphics Processing Units) 24 24

25. University of New Brunswick25 25

26. High Performance Computing and Networking @ University of New Brunswick

27. ACEnet: Atlantic Computational Excellence Network
“People, Research, Excellence”
Hosting sites:
Member sites:

28. ACEnet
Atlantic Canada is a distributed environment
$30 million initiative
Waterways make networking solutions difficult (e.g. Cabot Strait)

29. World-class HPC facilities
ACEnet
World-class HPC facilities
Behave as a single, regionally distributed “computational power grid”
Create and operate sophisticated collaboration facilities to bind together geographically dispersed research communities.

30. Advaced Computational Research Lab (ACRL) Infrastructure

31. Major Users UNB Biology Gary Saunders
UNB Chemistry Scott Brownridge Larry Calhoun Ghislain Deslongchamps Friedrich Grein
UNB Computer Science Eric Aubanel Virendra Bhavsar Brad Nickerson Ruth Shaw
UNB Text Processing Centre Alan Burk David Gants
UNB Geodesy Petr Vanícek Richard Langley
UNB Mathematics Keith De’Bell Abraham Punnen
UNB Mechanical Engineering Mohammad Bagher Ayani David Bonham Andrew Gerber Marwan Hassan Esam Hussein
UNB Physics Dr. Eugene K Ho Dr. Zong-Chao Yan Dr. Li-Hong Xu
UNB Forestry Evelyn Richards
UNB Biomedical Kevin Englehart
DAL Physics Andrew Rutenberg
MTA Chemistry Stacey Wetmore
MUN Computer Science Dwight Kuo
Sick Kids Hospital, Toronto Regis Pomes Ching-Hsing Yu Len Zaifman
StFX Computer Science Laurence Yang
UofCalgary Computer Science Peter Tieleman Justin MacCallum
UdeM Environmental Studies Yves Gagnon
UdeM Computer Science Jalal Almhana
UPEI Physics Sheldon Opps James Polson
UofT Computer Science Hue Sun Chan Maria Sabaye Moghaddam

32. Fundy: SUN cluster, AMD Opeteron, 632 cores
ACEnet at UNB
Fundy: SUN cluster, AMD Opeteron, 632 cores
ACEnet: 3324 cores
Internet connectivity > 2Gbps at UNB

34. Collaboration gear across Atlantic Canada
Collaboration Grid
Collaboration gear across Atlantic Canada
Lecture rooms equipped so ACEnet sites can share seminars and participate remotely
ACEnet cafés at each site sharing continuous video feeds
Desktop level collaboration equipment for personal communication
Access Grid streams tens to hundreds of Mbps across the CANARIE network
ACEnet

35. My Research Work Special Purpose computers for Military Applications
Design and development of MICRON and PLEXUS
Parallel Monte Carlo Algorithms
Graphics and Visualization
PaGrid
Artificial Intelligence – artificial neural networks, e-Business
Bioinformatics – Canadian Potato Genome project

36. Future
IBM Cyclops64 – supercomputer on a chip
C-DAC initiative for 2010 –petaflop machine
NCSA, USA 2011 petaflop machine
NASA, SGI and Intel Pleiades – 10 petaflop by 2012
1 Exaflop (10**18 flops) by 2019
Human brain neural simulations – 10 exaflop by 2025
2-week Full Weather modeling – 1 zeta flops (10**21 flops) by 2030