THE BSP400 - A MODULAR NEUROCOMPUTER

被引:4
作者
HEEMSKERK, JNH
HOEKSTRA, J
MURRE, JMJ
KEMNA, LHJG
HUDSON, PTW
机构
[1] LEIDEN UNIV,DEPT EXPTL PSYCHOL,2300 RB LEIDEN,NETHERLANDS
[2] DELFT UNIV TECHNOL,DEPT ELECT ENGN,2600 GA DELFT,NETHERLANDS
[3] MRC,APPL PSYCHOL UNIT,CAMBRIDGE CB2 2EF,ENGLAND
[4] UNIV LIMBURG,DEPT COMP SCI,6200 MD MAASTRICHT,NETHERLANDS
关键词
NEUROCOMPUTERS; MULTIPROCESSOR SYSTEMS; NEURAL NETWORKS; MASSIVELY PARALLEL COMPUTERS; REAL-TIME PROCESSING;
D O I
10.1016/0141-9331(94)90027-2
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This paper discusses the main architectural issues, the implementation, and the performance of a parallel neurocomputer, the Brain-Style Processor or BSP400. This project presents a feasibility study for larger parallel neurocomputers. The design principles are hardware modularity, simple processors, and in situ (local) learning. The modular approach of the design ensures extensibility of the present version. The BSP400 consists of 25 modules (boards) each containing 16 simple 8-bit single-chip computers. The module boards are connected to a dedicated connection network. The architectural configuration of the BSP400 supports local activation and learning rules. The ability to communicate activations with the outside world in real-time makes the BSP400 particularly suited for real-world applications. The present version implements a modular type of neural network, the CALM (categorizing and learning module) neural network. In this implementation of CALM, activations are transmitted as single bits, but an internal representation of one byte is kept for both activations and weights. The systems has a capacity of 400 processing elements and 32000 connections. Even with slow and simple processing elements, it still achieves a speed of 6.4 million connections per second for a non-learning CALM network. Some small network simulation studies carried out on the BSP400 are reported. A comparison with a design study (Mark III and Mark IV) is made.
引用
收藏
页码:67 / 78
页数:12
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