Automatic data mapping of signal processing applications

This paper presents a technique to map automatically a complete digital signal processing (DSP) application onto a parallel machine with distributed memory. Unlike other applications where coarse or medium grain scheduling techniques can be used, DSP applications integrate several thousand of tasks...

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Bibliographic Details
Published in:Proceedings / IEEE International Conference on Application-Specific Systems, Architectures, and Processors pp. 350 - 362
Main Authors: Ancourt, C., Barthou, D., Guettier, C., Irigoin, F., Jeannet, B., Jourdan, J., Mattioli, J.
Format: Conference Proceeding
Language:English
Published: IEEE 1997
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ISBN:081867959X, 9780818679599
ISSN:2160-0511
Online Access:Get full text
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Summary:This paper presents a technique to map automatically a complete digital signal processing (DSP) application onto a parallel machine with distributed memory. Unlike other applications where coarse or medium grain scheduling techniques can be used, DSP applications integrate several thousand of tasks and hence necessitate fine grain considerations. Moreover finding an effective mapping imperatively require to take into account both architectural resources constraints and real time constraints. The main contribution of this paper is to show how it is possible to handle and to solve data partitioning, and fine-grain scheduling under the above operational constraints using concurrent constraints logic programming languages (CCLP). Our concurrent resolution technique undertaking linear and nonlinear constraints takes advantage of the special features of signal processing applications and provides a solution equivalent to a manual solution for the representative panoramic analysis (PA) application.
ISBN:081867959X
9780818679599
ISSN:2160-0511
DOI:10.1109/ASAP.1997.606840