Granularity experiments for the adaptive multiprocessor system (AMPS)

Author

Carlson, Bradley S. ; Lo, N.W. ; Tao, D.L. ; Zheng, Zhu

Author_Institution

Dept. of Electr. Eng., State Univ. of New York, Stony Brook, NY, USA

Volume

3

fYear

1996

fDate

18-21 Aug 1996

Firstpage

1285

Abstract

AMPS (Adaptive MultiProcessor System) is a shared-memory MIMD architecture intended for digital signal processing applications. We present our investigations on task granularity for AMPS. We have investigated task decomposition (granularity reduction) for matrix multiplication and fast Fourier transform (FFT) and task grouping (granularity enlargement) for Gram-Schmidt orthogonalization (GSO). The results indicate that significant performance improvement can be obtained for matrix multiplication and GSO by selecting the appropriate task granularity

Keywords

adaptive signal processing; fast Fourier transforms; matrix multiplication; shared memory systems; task analysis; AMPS; Gram-Schmidt orthogonalization; adaptive multiprocessor system; digital signal processing applications; fast Fourier transform; granularity experiments; matrix multiplication; shared-memory MIMD architecture; task decomposition; task granularity; task grouping; Adaptive systems; Application specific integrated circuits; Arithmetic; Digital signal processing; Fast Fourier transforms; Flexible printed circuits; Flow graphs; Matrix decomposition; Multiprocessing systems; Processor scheduling;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1996., IEEE 39th Midwest symposium on

Conference_Location

Ames, IA

Print_ISBN

0-7803-3636-4

Type

conf

DOI

10.1109/MWSCAS.1996.593158

Filename

593158