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Incremental Communication Error Analysis

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Advanced Computational Research Laboratory (ACRL) Virendra C. Bhavsar ... Dr. Sousa ( fire propagation, CFD) Dr. Biden (artificial limbs) Chemical Engineering ... – PowerPoint PPT presentation

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Title: Incremental Communication Error Analysis


1
Advanced Computational Research Laboratory
(ACRL) Virendra C. Bhavsar
Faculty of Computer Science University of New
Brunswick Fredericton, NB, E3B 5A3 Canada
2
OUTLINE
? ACRL Research Groups ? Introduction to
Parallel Processing ? ACRL Research Groups
? Conclusion
3
ARCL
Advanced Computational Research Laboratory ?
High Performance Computational Problem-Solving
Environment and Visualization Environment ?
Computational Experiments in multiple
disciplines Computer Science, Science and
Engineering ? Located in the Information
Technology Center (ITC)
4
ACRL Researchers and Groups
Faculty of Computer Science ? Artificial
Intelligence Group - Dr. Spencer, Dr.
Nickerson ? Parallel/Distributed Processing
Group - Dr. Bhavsar, Dr. Du, Dr. Ghorbani
Dr. Kaser, Dr. Shaw ? Computational
Geometry Group - Dr. Bremner, Dr. Itturiaga ?
Automated Reasoning Group - Dr. Spencer, Dr.
Horton ? Bioinformatics Group
5
ACRL Researchers and Groups
Faculty of Science ? Physics - Dr. Hamza
(plasma physics,
ionospehere, solar corona) Dr. Balcolm
(magnetic resonance
Imaging) Dr. Xu (methanol to gasoline
process) ? Chemistry - Dr.
Thakkar (optical computing
materials) Dr. Grein (ozone related
reactions) Dr. Mattar (cancer drugs,
fisheries) ? Bioinformatics Group
6
ACRL Researchers and Groups
Faculty of Engineering ? Mechanical
Engineering Dr. Hussein (threat-material
detection) Dr. Sousa ( fire propagation,
CFD) Dr. Biden (artificial limbs) ?
Chemical Engineering Dr. Bendrich (plastics
manufacturing) ?
Electrical Engineering Dr. Chang (electrical
machines Forestry and Environment Management
? New CFI Application
7
Scientific Computation
8
Parallel Computing
  • Parallel computing
  • - simultaneous use of multiple compute resources
    to solve a computational problem
  • Why Parallel Computing?
  • - to save time (wall clock time)
  • - to solve larger problems
  • - to alleviate memory
  • constraints
  • - larger databases

9
Parallel Computing
  • Grand Challenge Problems
  • - weather and climate
  • - mechanical devices - from prosthetics to
    spacecraft
  • - electronic circuits
  • - manufacturing processes
  • - geological, seismic activity
  • - biological, human genome
  • - chemical and nuclear reactions

10
Parallel Computing
  • Commercial applications
  • - parallel databases, data mining
  • - oil exploration
  • - computer-aided diagnosis in medicine
  • - management of national and multi-national
    corporations
  • - advanced graphics and virtual reality,
    particularly in the entertainment industry
  • - networked video and multi-media technologies
  • - collaborative work environments

11
Parallel Computing
  • Ultimately, parallel computing is an attempt to
    maximize the infinite but seemingly scarce
    commodity called time

12
IBM SP

13
Shared Memory Model
  • Quad-Processor System

14
Distributed Memory Model
15
Hybrid Model
  • Similar to IBM SP

16
ARCL
Advanced Computational Research Laboratory ?
High Performance Multiprocessor
(16-processor) System with 24 GFLOPS
(peak) performance with 72 GB internal disk
storage and 109.2 GB external disk storage ?
Software for Computational Studies and
Visualization ? Parallel Programming tools ?
E-Commerce Software, including datamining
software
17
ARCL
  • Nodes
  • 4 Compute Nodes total of 16 processors.
  • Switch
  • 300 MB/sec bi-directional
  • 1.2 µsec latency


18
ARCL
  • Node
  • 2 x 2-way 375 Mhz POWER3 64-bit

  • Winterhawk II Processor Cards
  • 258 MB Memory (1 GB total)
  • 2 x 9.1 GB Ultra-SCSI Disk Drives
  • 10/100 Mbit Ethernet Adapter
  • Gigabit Ethernet Card

19
MIMD Processing
  • Multiple Instruction Stream Multiple Data Stream
    Model

20
Array Processing
21
Threads
22
Message Passing Model
  • Example - MPI

23
Data Parallel Model
24
Domain Decomposition
25
Domain Decomposition
26
Functional Decomposition
27
Inter-Process Communication
28
Load Balancing
29
Monte Carlo Method
30
Heat Equation
31
Heat Equation
32
Conclusion
  • Future Workshops
  • Feb. 13, 2001 Parallel Prog.
  • Workshop
  • Feb 24, 2001 AC3 Workshop
  • Feb. 26-27, 2001 IBM
  • Workshop
  • - Visualization using Open DX
  • - Atlantic Canada High Performance Computing
    Workshop
  • HPCS2001 at Windsor, ON
  • June 18-20, 2001
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