PARNEU:: general-purpose partial tree computer

被引:11
作者
Kolinummi, P [1 ]
Hämäläinen, P [1 ]
Hämäläinen, T [1 ]
Saarinen, J [1 ]
机构
[1] Tampere Univ Technol, Digital & Comp Syst Lab, FIN-33101 Tampere, Finland
基金
芬兰科学院;
关键词
neurocomputer; scalable parallel implementation; partial tree shape architecture; artificial neural networks;
D O I
10.1016/S0141-9331(99)00075-7
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
PARNEU is a parallel co-processor system for a PC designed for artificial neural networks, and other computationally intensive applications. PARNEU topology includes a bus, ring and reconfigurable partial tree, which are motivated due to analysis of several algorithms. The architecture provides very versatile mapping possibilities and allows modular hardware implementation. An important feature is practical expandability without signal and clock skew problems. Analog Devices ADSP-21062 digital signal processors and Xilinx field programmable gate arrays are used for cost-effective and reliable implementation. PARNEU programming is convenient due to C-primitives, which hide the complex communication and allow high level language software development. In addition, PARNEU can be remotely used over Internet due to a TCP/IP server. The hardware performance metrics as well as the application performance for Multilayer Perceptron (MLP), Self-Organizing Map (SOM) and Sparse Distributed Memory (SDM) neural networks are given. Performance improvements of the order of 20-40 times are achieved compared to our previous neurocomputer implementation called TUTNC. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:23 / 42
页数:20
相关论文
共 32 条
[1]  
*AN DEV INC, 1996, ADSP 2106X SHARC US
[2]  
Bertsekas Dimitri P., 1989, PARALLEL DISTRIBUTED
[3]   Competitive learning algorithms and neurocomputer architecture [J].
Card, HC ;
Rosendahl, GK ;
McNeill, DK ;
McLeod, RD .
IEEE TRANSACTIONS ON COMPUTERS, 1998, 47 (08) :847-858
[4]  
Cornu T., 1994, Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems, P87, DOI 10.1109/ICMNN.1994.593203
[5]  
Culler DavidE., 1999, PARALLEL COMPUTER AR
[6]   TUTNC: A general purpose parallel computer for neural network computations [J].
Hamalainen, T ;
Saarinen, J ;
Kaski, K .
MICROPROCESSORS AND MICROSYSTEMS, 1995, 19 (08) :447-465
[7]  
HAMMERSTROM D, 1990, VLSI ARTIFICIAL INTE
[8]  
Haykin S., 1994, NEURAL NETWORKS COMP
[9]  
IENNE P, 1995, CRITICAL REV SERI CR, V57, P314
[10]  
JAECKEL L, 1989, ALTERANTIVE DESIGN S