a decentralised task mapping approach for homogeneous multiprocessor network-on-chips
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ID: 210557
2009
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Abstract
We present a heuristic algorithm for the run-time distribution of task sets in a homogeneous Multiprocessor
network-on-chip. The algorithm is itself distributed over the processors and thus can be applied to systems of
arbitrary size. Also, tasks added at run-time can be handled without any difficulty, allowing for inline optimisation.
Based on local information on processor workload, task size, communication requirements, and link contention, iterative decisions on task migrations to other processors are made. The mapping results for several example task
sets are first compared with those of an exact (enumeration) algorithm with global information for a 3×3 processor array. The results show that the mapping quality achieved by our distributed algorithm is within 25%
of that of the exact algorithm. For larger array sizes, simulated annealing is used as a reference and the behaviour of our algorithm is investigated. The mapping quality of the algorithm can be shown to be within a reasonable range (below 30% mostly) of the reference. This adaptability and the low computation and communication overhead of the distributed heuristic clearly indicate that decentralised algorithms are a favourable solution for an
automatic task distribution.
| Reference Key |
zipf2009internationala
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|---|---|
| Authors | ;Peter Zipf;Gilles Sassatelli;Nurten Utlu;Nicolas Saint-Jean;Pascal Benoit;Manfred Glesner |
| Journal | case reports in ophthalmological medicine |
| Year | 2009 |
| DOI |
10.1155/2009/453970
|
| URL | |
| Keywords |
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