Advanced Computational Research Laboratory (ACRL)

Virendra C. Bhavsar

Faculty of Computer ScienceUniversity of New Brunswick

Fredericton, NB, E3B 5A3Canada

OUTLINE

ACRL Research Groups

Introduction to Parallel Processing

ACRL Research Groups

Conclusion

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)

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

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

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

Scientific Computation

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

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

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

Parallel Computing

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

IBM SP

Shared Memory Model

• Quad-Processor System

Distributed Memory Model

Hybrid Model

• Similar to IBM SP

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

ARCL

Nodes

• 4 Compute Nodes: total of 16 processors.

Switch• 300 MB/sec bi-directional • 1.2 µsec latency

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

MIMD Processing

• Multiple Instruction Stream Multiple Data Stream Model

Array Processing

Threads

Message Passing Model

• Example - MPI

Data Parallel Model

Domain Decomposition

Domain Decomposition

Functional Decomposition

Inter-Process Communication

Load Balancing

Monte Carlo Method

Heat Equation

Heat Equation

Conclusion

Future Workshops

Feb. 13, 2001: Parallel Prog. Workshop

Feb 24, 2001: AC3 WorkshopFeb. 26-27, 2001: IBM Workshop

- Visualization using Open DX

- Atlantic Canada High Performance Computing Workshop

-HPCS’2001 at Windsor, ON June 18-20, 2001