Performance aspects of mapping neural networks onto a massively parallel SIMD computer

Andreas Zell; Michael C. Vogt; Niels Mache; Markus Huttel

doi:10.1117/12.152537

2 September 1993 Performance aspects of mapping neural networks onto a massively parallel SIMD computer

Andreas Zell, Michael C. Vogt, Niels Mache, Markus Huttel

Proceedings Volume 1965, Applications of Artificial Neural Networks IV; (1993) https://doi.org/10.1117/12.152537
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

In this paper we present and compare three different massively parallel implementations of multilayer feedforward neural networks on a MasPar MP-1216, a parallel SIMD computer with 16,384 processors. For multilayer feedforward networks we have obtained sustained rates of up to 348 MCPS and 129 MCUPS with backpropagation, a high mark for general purpose SIMD computers. After a brief introduction to SNNS, the paper first focuses on the problems of mapping neural networks to parallel hardware. Different aspects of parallelism are presented. Two combinations of unit and training pattern parallelism were implemented as well as link and training pattern parallelism. We describe the implementation problems in obtaining high propagation rates on a SIMD machine and problems with the resulting learning algorithms in general.

Citation Download Citation

Andreas Zell, Michael C. Vogt, Niels Mache, and Markus Huttel "Performance aspects of mapping neural networks onto a massively parallel SIMD computer", Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); https://doi.org/10.1117/12.152537

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available