Title :
A systolic algorithm for back-propagation: mapping onto a transputer network
Author :
Bofill, P. ; Manyer, J. ; Millán, J.R. ; Salvans, V.
Author_Institution :
Dept. d´´Arquitectura d´´Ordinadors, Univ. Politecnica de Catalunya, Barcelona, Spain
Abstract :
The paper is devoted to the implementation of Back-Propagation (BP) on local memory multiprocessor systems (LMM). First, a systolic algorithm (SA) is described, where dependencies are considered at the data item level. Next, the systolic array is partitioned and mapped onto a multiprocessor system. At this stage, the level of granularity is increased, in order to reduce communication cost. Finally, each stage is implemented on a transputer based multiprocessor, and their performance is compared with a simple sequential version of the learning rule. A parallelization rate of about 0.9 is obtained. Back-Propagation is a supervised, gradient descent learning rule for multilayered, feed-forward connectionist networks
Keywords :
computer architecture; learning systems; parallel algorithms; transputers; Back-Propagation; learning rule; local memory multiprocessor systems; parallelization; systolic algorithm; transputer network;
Conference_Titel :
Symbols Versus Neurons, IEE Colloquium on
Conference_Location :
London