A Game-Theoretic Approach for Run-Time Distributed Optimization on MP-SoC
With forecasted hundreds of processing elements (PEs), future embedded systems will be able to handle multiple applications with very diverse running constraints. Systems will integrate distributed decision capabilities. In order to control the power and temperature, dynamic voltage frequency scalin...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2008-01-01
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| Series: | International Journal of Reconfigurable Computing |
| Online Access: | http://dx.doi.org/10.1155/2008/403086 |
| Summary: | With forecasted hundreds of processing elements
(PEs), future embedded systems will be able
to handle multiple applications with very diverse
running constraints. Systems will integrate distributed
decision capabilities. In order to control
the power and temperature, dynamic voltage
frequency scalings (DVFSs) are applied at PE
level. At system level, it implies to dynamically
manage the different voltage/frequency couples of
each tile to obtain a global optimization. This paper
introduces a scalable multiobjective approach
based on game theory, which adjusts at run-time
the frequency of each PE. It aims at reducing the
tile temperature while maintaining the synchronization
between application tasks. Results show that
the proposed run-time algorithm requires an average
of 20 calculation cycles to find the solution
for a 100-processor platform and reaches equivalent
performances when comparing with an offline
method. Temperature reductions of about 23%
were achieved on a demonstrative test-case. |
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| ISSN: | 1687-7195 1687-7209 |