Abstract
In the embedded computer system domain, MPSoC systems have become increasingly popular due to the ever-increasing performance demands of modern embedded applications. The number of processing elements in these MPSoCs also steadily increases. Whereas current MPSoCs still contain a limited number of processing elements, future MPSoCs will feature tens up to hundreds of (heterogeneous) processing elements that are all integrated on a single chip. On these future large-scale MPSoC systems, the mapping of applications onto the hardware resources plays an important role to fully explore the parallelism of applications. In this article, a hierarchical run-time adaptive resource allocation framework which uses an intelligent task remapping approach is proposed to improve the system performance for large-scale MPSoCs.
Original language | English |
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Pages (from-to) | 311-339 |
Number of pages | 29 |
Journal | Design Automation for Embedded Systems |
Volume | 20 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1 Dec 2016 |
Externally published | Yes |
Keywords
- Embedded systems
- KPN
- MPSoC
- Simulation
- Task mapping