Newsgroups: comp.parallel From: eskfoo@alpha.ntu.ac.sg (Hello... I'm Shou King) Subject: ***** NEW BOOK ANOUNCEMENT ***** Organization: Nanyang Technological University - Singapore Date: Tue, 16 Jul 1996 11:37:01 +0800 Message-ID: <4sintf$mpl@usenet.srv.cis.pitt.edu> BOOK ANNOUNCEMENT ----------------- Title: Parallel Implementations of Backpropagation Neural Networks on Transputers - A Study of Training Set Parallelism Publication Date: July 1996 Brief description ----------------- This book presents a systematic approach to parallel implementation of feedforward neural networks on an array of transputers. The emphasis is on backpropagation learning and training set parallelism. Using systematic analysis, a theoretical model is developed for the parallel implementation. The model is then used to find the optimal mapping to minimize the training time for large backpropagation neural networks. The model is also validated experimentally on several well known benchmark problems. Use of genetic algorithms for optimizing the performance of the parallel implementations is described. Guidelines for efficient parallel implementations are highlighted. Table of contents ----------------- 1. Introduction 1.1 Multilayer Feedforward Neural Networks 1.2 The Basic BP Algorithm 1.3 Parallelism in the BP Algorithm 1.4 Some Parallel Implementations 2. Transputer Topologies for Parallel Implementation 2.1 The Transputer 2.2 Topologies 2.3 Topology Chosen in this Study 2.4 Software Used 2.5 Performance Metrics and Benchmark Problems 3. Development of a Theoretical Model for Training Set Parallelism in a Homogeneous Array of Transputers 3.1 Time Components of Parallel Transputer Implementation 3.2 Timing Aspects of Parallelizing the Backpropagation Algorithm 3.3 Time Components for the Parallelized Backpropagation Algorithm 3.4 Validation of the T-epoch Model 4. Equal Distribution of Patterns Amongst a Homogeneous Array of Transputers 4.1 Analytical Model for Time per Epoch 4.2 Validation of the Model for Equal Distribution 4.3 Optimal Number of Transputers Needed for the case of Equal distribution 4.4 Cost Benefit Analysis of adding Additional Processors 5. Optimization Model for Unequal Distribution of Patterns in a Homogeneous Array of Transputers 5.1 Constraints for Optimization 5.2 Optimal Pattern Distribution 5.3 Validation of Pattern Optimization Model 5.4 Experimental Results for Benchmark Problems 5.5 Locating Surplus Processors and to Find out the Optimal number of Processors needed to Obtain Minimum Time per epoch 6. Optimization Model for Unequal Distribution of Patterns in a Heterogeneous Array of Transputers 6.1 Experimental Results for Benchmark Problems 6.2 Statistical Verification of the Optimal Epoch Time 6.3 Discussion 7. Pattern Allocation Schemes Using Genetic Algorithm 7.1 Optimization Algorithm and Computational Complexity 7.2 Solution Time for Optimal Pattern Distribution 7.3 Suboptimal Method: Heuristic Distribution 7.4 Genetic Algorithm for Pattern Allocation 7.5 Comparison between Genetic Algorithm and Mixed Integer Programming (MIP) 7.6 Inclusion of `A Priori' Information 7.7 GA with the Proposed Stopping Criterion versus MIP Appendices A: Comparison Between Pipelined Ring Topology and Ring Topology B: A Sample Parallel C Program C: The Branch and Bound Method for Solving Mixed Integer Programming problems Bibliography Index Readership ---------- Graduate students, research scientists and practicing engineers in artificial neural networks and parallel computing. Bibliographic Data: ------------------- Title: Parallel Implementations of Backpropagation Neural Networks on Transputers - A Study of Training Set Parallelism Authors: P Saratchandran (School of Electrical & Electronic Engg, Nanyang Technological University, Singapore) N Sundararajan (School of Electrical & Electronic Engg, Nanyang Technological University, Singapore) Shou King Foo (School of Electrical & Electronic Engg, Nanyang Technological University, Singapore) Publisher: World Scientific Publishing Co. ISBN: 981-02-2654-3 Pages: 250 pages (Approx) Series Title: Progress in Neural Processing. Series Advisors: Alan Murray (University of Edinburgh) Lionel Tarassenko (University of Oxford) John Taylor (King's College, London) Andreas Weigend (University of Colorado) List Price: US$38.00, UK Pounds 26.00 Order Information: ------------------ World-Wide Web: http://www.singnet.com.sg/~wspclibk or http://www.wspc.co.uk Please send orders to your regular book supplier or directly to your nearest World Scientific office: USA: World Scientific Publishing Co., Inc. 1060 Main Street, River Edge, NJ 07661, USA Fax: 1-201-487-9656 Tel: 1-201-487-9655 Toll-free: 1-800-227-7562 UK: World Scientific Publishing Co., Ltd. 57 Shelton Street, Covent Garden, London WC2H 9HE, UK. Fax: 44-171-836-2020 Tel: 44-171-836-0888 SINGAPORE: World Scientific Publishing Co. Pte. Ltd. Farrer Road, P O Box 128, SINGAPORE 912805. Cable: COSPUB Tlx: RS 28561WSPC Fax: 65-382-5919 Tel: 65-382-5663 HONG KONG: World Scientific Publishing (HK) Co. Ltd. P O Box 72482, Kowloon Central Post Office, HONG KONG. 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