Parallel and Distributed Intelligent Systems Virendrakumar C Bhavsar

Parallel and Distributed Intelligent Systems Virendrakumar C. Bhavsar Professor and Director, Advanced Computational Research Laboratory Faculty of Computer Science University of New Brunswick Fredericton, NB bhavsar@unb. ca www. cs. unb. ca/profs/bhavsar www. cs. unb. ca/acrl

Outline Past Research Work l Current Research Work l Conclusion l

Past Research Work Parallel/Distributed Processing - Parallel Computer Architecture - Design and Analysis of Parallel Algorithms - Real-time and Fault-Tolerant Systems Artificial Neural Networks Learning Machines and Evolutionary Computation Computer Graphics n Visualization

Advanced Computational Research Laboratory High Performance Computational Problem. Solving and Visualization Environment l Computational Experiments in multiple disciplines: CS, Science and Eng. l 16 -Processor IBM SP 3 l Member of C 3. ca Association, Inc. (http: //www. c 3. ca) l

Advanced Computational Research Laboratory www. cs. unb. ca/acrl Virendra Bhavsar, Director l Chris Mac. Phee, Scientific Computing Support l Sean Seeley, System Administrator l

ACRL’s IBM SP l – 16 processors; 24 Gigabit Ethernet GFLOPS l Disk 4 Winterhawk II nodes High Perforrnance Switch

IBM SP at ACRL: The Clustered SMP Four 4 -way SMPs Each node has its own copy of the O/S Processors on the node are closer than those on different nodes

IBM Power 3 SP Switch Bidirectional multistage interconnection networks (MIN) l 300 MB/sec bi-directional l 1. 2 sec latency l

Past Research Work (cont. ) Multimedia for Education: Intelligent Tutoring Systems n. Multi-Lingual Systems and Transliteration n Web Portal with an Intelligent User Profile Generator Multi-Agent Systems Supervision/Co-supervision 50 master's theses; 4 doctoral theses 5 post-doctoral fellows/research associates

Current Research Work Parallel/Distributed Processing -Pa. Grid: A Mesh Partitioner for Computational Grids - Dynamic Partitioning for Efficient Processing on Parallel Computers n Multi-Agent Systems (Distributed Artificial Intelligence) - Multi-Agent System for Automatic Annotation of EST Sequences (funded by ‘The Canadian Potato Genomics’) - CS 6999: Multi-Agent Systems - Dynamic Clustering of Agents in the Café - Agents with Ontology-based Keyphrases and Tree-distance algorithms - Scalability studies of Multi-Agent Systems - e. Commerce applications

Current Research Work ne. Learning (edu. Sorce. Canada Project) - Reuse and exchange course content stored as “learning objects. ’’ - Implementation and testing of learning objects using Can. Core metadata -XML schema for content packaging - other projects

What is a GRID System l Cooperative network of shared resources - Includes computers, network links, human resources and databases l Supports the development of advanced R&D applications in Science, Engineering and Technology Development, Finance and the Arts. March, 2000 Copyright (C) C 3. ca 15

GRID Applications l Large scale and resource intensive frontier applications – R&D applications that go beyond current technological capabilities – Technology development applications in multi-media, finance, production arts, hard sciences and engineering. - Multi-media applications such as embedded video, digital video servers and video conferencing. March, 2000 Copyright (C) C 3. ca 16

Current C 3. ca RP Network March, 2000 Copyright (C) C 3. ca 17

The Canadian Potato Genomics Project ATLANTIC CANADA • 46% of national potato production $1 Billion/year • Home of Mc. Cain Foods Ltd. $5. 5 billion/year • Potato Research Center of AAFC • Solanum Genomics International Inc.

The Canadian Potato Genomics Project Research Areas • Bioinformatic Analysis • Access to resources via CBR membership/node status • Raw sequence processing and analysis by Fredericton bioinformatics group (Vector trimming, base calling, clustering, contig assembly, BLAST, an • Relational database management system of CPGP to link NRC (sequencing), CBR and researchers • In silico assignment of gene function • Microarray data

The Canadian Potato Genomics Project Research Areas • Bioinformatic Research To Suit Project Needs (UNB): • Autonomous agent development to automatically update sequence annotations • Enhancement of bioinformatic algorithm performance with parallel computing • Algorithm development using annotation information to enhance sequence searching • The application of clustering and learning techniques to the analysis of expression data

tom@ucsd. edu ymasrour@ai. it. nrc. ca ucsd. edu ai. it. nrc. ca S e r v e r bob@ai. it. nrc. ca dick@ucsd. edu steve@ai. it. nrc. ca Café anwhere. else foo@anywhere. else Café S e r v e r cs. stir. ac. uk meto. gov. uk S e r v e r Café Clients wibble@cs. stir. ac. uk graham@cs. stir. ac. uk anne@cs. stir. ac. uk joan@unb. ca bhavsar@unb. ca

Performance Evaluation of ACORN l Test-bed: Several Autonomous Servers, each serving autonomous virtual users l Virtual User - capable of creating agents - picks up a topic from a client core’s interest - migrates to other servers - potential destinations

Performance Evaluation of ACORN

Why learning objects? • COST: 1000 s of colleges have common course topics • large numbers of courses are going online • World does not need 1000 s of similar learning topics • World needs only about a dozen Des i(From Downes, 2000) gn c coll ours ecti on o es as obje a f lea cts rnin NOT HTM g L • Expensive to develop so sharing is essential

What is METADATA? data about data Metadata standards are agreed-on criteria for describing data to support interoperability Example: January 31, 2001 31 janvier 2001 -01 -31 -2000 31012000

Metadata and RDF implementation * XML * Resource Description Framework (RDF) = structure Metadata = semantics & resources

Conclusion Parallel/Distributed Processing Multi-Agent Systems (Distributed Artificial Intelligence) NSERC Project, The Canadian Potato Genomics Project ne. Learning (edu. Sorce. Canada Project) n Automated and manually-driven user profile generation and update