Xref: utzoo comp.parallel:2646 comp.ai.neural-nets:3559
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From: prechelt@i41s14.ira.uka.de (Lutz Prechelt)
Newsgroups: comp.parallel,comp.ai.neural-nets
Subject: Neural Networks on SIMD-Machines
Keywords: parallel, SIMD, neural network, methodology
Message-ID: <1991Jun11.124119.4476@ira.uka.de>
Date: 11 Jun 91 12:41:19 GMT
Sender: news@ira.uka.de (USENET News System)
Reply-To: prechelt@ira.uka.de (Lutz Prechelt)
Organization: University of Karlsruhe, FRG
Lines: 29
Approved: parallel@hubcap.clemson.edu

Does anybody do any systematic research on implementations of
Neural Networks on SIMD machines ?

I am not thinking of these simple kinds of problems that have of
course long been solved, such as a single net with backpropagation
(for instance the work of Zhang or Rosenberg/Blelloch).

What I am thinking of is a complete methodology for complex NN 
applications: 
- how to lay out irregular nets
- how to train or execute multiple nets of different types in parallel
- how to organize memory usage cleverly
- if I/O is necessary, how to organize it best.
- how to integrate the NNs with the rest of an application on a 
  parallel machine.

I know that there is some work on these issues for MIMD machines
(especially Transputer Arrays), but for SIMD many problems are very
different.

Please reply by email; I'll summarize on the net.

  Lutz

Lutz Prechelt   (++49/721/608-4317,  FAX: ++49/721/697760)
Institut fuer Programmstrukturen und Datenorganisation
Universitaet Karlsruhe;  D-7500 Karlsruhe 1;  Germany
prechelt@ira.uka.de  or  prechelt!ira.uka.de@relay.csnet


-- 
=========================== MODERATOR ==============================
Steve Stevenson                            {steve,fpst}@hubcap.clemson.edu
Department of Computer Science,            comp.parallel
Clemson University, Clemson, SC 29634-1906 (803)656-5880.mabell