Title :
A multiprocessor machine for large-scale neural network simulation
Author :
Elias, John G. ; Fisher, Maurice D. ; Monemi, Cameron M.
Author_Institution :
Dept. of Electr. Eng., Delaware Univ., Newark, DE, USA
Abstract :
The architecture of a multiprocessor machine designed specifically for simulating large digital neural networks is described. The single-input multiple data (SIMD) machine comprises a host computer for high-level control and software development, a network controller which has data distribution and control responsibilities, and multiple processor arrays which carry out most of the computation for the network. Each processor array comprises a high-performance reduced instruction set computer (RISC) as a controller and 20 processing elements, each of which consist of a custom VLSI floating point processor and 1.5 Mbytes of private high-speed memory. The peak processing rate for a single processor array is 500 MFLOPS which can be sustained for relatively long vectors
Keywords :
multiprocessing systems; neural nets; reduced instruction set computing; 1.5 MB; 500 MFLOPS; RISC; custom VLSI floating point processor; large-scale neural network simulation; multiple processor arrays; multiprocessor machine; neural network controller; peak processing rate; private high-speed memory; reduced instruction set computer; single-input multiple data; Computational modeling; Computer aided instruction; Computer architecture; Computer networks; Distributed computing; Large-scale systems; Neural networks; Process control; Programming; Reduced instruction set computing;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155224
