Self-Scaling Stream Processing: a Bio-Inspired Approach to Resource Allocation through Dynamic Task Replication

In this article, we show how the use of a bio-inspired dynamic task replication algorithm, in the context of stream processing, can be used to significantly improve the performance of embedded programs. We also show that this programming methodology, which is not tied to a particular implementation, can also be used as an heuristic for task mapping in the context of embedded multiprocessors systems. The technique was applied to a 36-processor system implemented on a scalable mesh of FPGAS for two different case studies: for AES encryption, it resulted in a tenfold speedup compared to a static implementation, while for MJPEG compression a throughput multiplication of 11 was obtained.

Published in:
Proc. of the 4th NASA/ESA Conference on Adaptive Hardware and Systems
Presented at:
NASA/ESA Conference on Adaptive Hardware and Systems, San Francisco, July 29
Ieee Computer Soc Press, Customer Service Center, Po Box 3014, 10662 Los Vaqueros Circle, Los Alamitos, Ca 90720-1264 Usa

 Record created 2009-05-04, last modified 2019-08-12

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