Treffer: An environment for exploring data-driven architectures

Title:
An environment for exploring data-driven architectures
Source:
FPL 2004 : field-programmable logic and applications (Antwerp, 30 August - 1 September 2004)Lecture notes in computer science. :1022-1026
Publisher Information:
Berlin: Springer, 2004.
Publication Year:
2004
Physical Description:
print, 11 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Departamento de Informática, Universidade Federal de Viçosa, Viçosa 36570 000, Brazil
Universidade do Algarve, Campus de Gambelas, 8000-117, Faro, Portugal
INESC-ID, 1000-029, Lisboa, Portugal
Instituto Superior Técnico, Lisboa, Portugal
ISSN:
0302-9743
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Electronics
Accession Number:
edscal.16107491
Database:
PASCAL Archive

Weitere Informationen

A wide range of reconfigurable coarse-grain architectures has been proposed in recent years, for an extensive set of applications. These architectures vary widely in the interconnectivity, number, granularity and complexity of the processing elements (PEs). The performance of a specific application usually depends heavily on the adequacy of the PEs to the particular tasks involved, but tools to efficiently experiment architectural features are lacking. This work proposes an environment for exploration and simulation of coarse-grain reconfigurable data-driven architectures. The proposed environment takes advantage of Java and XML technologies to enable a very efficient backend for experiments with different architectural trade-offs, from the array connectivity and topology to the granularity and complexity of each PE. For a proof of concept, we show results on implementing different versions of a FIR filter on a hexagonal data-driven array.