Achieving supercomputer performane for neural net simulation with an array of digital signal processors

Author

Muller, Urs A. ; Baumle, Bernhard ; Kohler, Peter ; Gunzinger, Anton ; Guggenbuhl, Walter

Author_Institution

Electron. Lab., Swiss Federal Inst. of Technol., Zurich, Switzerland

Volume

12

Issue

5

fYear

1992

Firstpage

55

Lastpage

65

Abstract

Music, a digital signal processor (DSP)-based system with a parallel distributed-memory architecture that provides enormous computing power yet retains the flexibility of a general-purpose computer, is discussed. It is shown that Music reaches a peak performance of 2.7 Gflops at a significantly lower cost, power consumption, and space requirement than conventional supercomputers. The Music system hardware, programming, and backpropagation implementation are described.<>

Keywords

digital signal processing chips; multiprocessor interconnection networks; neural nets; parallel architectures; parallel programming; virtual machines; 2.7 GFLOPS; Music; backpropagation; digital signal processors array; neural net simulation; parallel distributed-memory architecture; programming; supercomputer performane; Computational modeling; Computer architecture; Concurrent computing; Costs; Digital signal processors; Distributed computing; Energy consumption; Multiple signal classification; Neural networks; Supercomputers;

fLanguage

English

Journal_Title

Micro, IEEE

Publisher

ieee

ISSN

0272-1732

Type

jour

DOI

10.1109/40.166714

Filename

166714