A Two-step Genetic Algorithm for Mapping Task Graphs to a Network on Chip Architecture
DSD '03 Proceedings of the Euromicro Symposium on Digital Systems Design
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
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Proceedings of the conference on Design, automation and test in Europe: Proceedings
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Proceedings of the conference on Design, automation and test in Europe: Proceedings
Heuristics for Dynamic Task Mapping in NoC-based Heterogeneous MPSoCs
RSP '07 Proceedings of the 18th IEEE/IFIP International Workshop on Rapid System Prototyping
Incremental run-time application mapping for homogeneous NoCs with multiple voltage levels
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Proceedings of the conference on Design, automation and test in Europe
Energy- and performance-aware mapping for regular NoC architectures
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Communication-aware heuristics for run-time task mapping on NoC-based MPSoC platforms
Journal of Systems Architecture: the EUROMICRO Journal
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Multi-task dynamic mapping onto NoC-based MPSoCs
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Accelerating throughput-aware runtime mapping for heterogeneous MPSoCs
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An efficient network on-chip architecture based on isolating local and non-local communications
Proceedings of the Conference on Design, Automation and Test in Europe
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The number of tasks executing in MPSoC platform can exceed the available resources, requiring efficient run-time mapping strategies to meet the real-time constraints of the applications. This paper describes two new run-time mapping heuristics for mapping applications onto NoC-based Heterogeneous Multiprocessor Systems-on-Chip (MPSoC). The heuristics proposed in this paper attempt to map the tasks of an application in close proximity to each other so as to minimize the communication overhead. In addition, they have been shown to alleviate NoC congestion bottlenecks to maximize overall computation performance. Based on our evaluations to map applications with varying number of tasks onto an 8脳 8 platform, we demonstrate that the new mapping heuristics are capable of reducing the total execution time, channel load and latency of applications when compared to state-of-the-art run-time mapping heuristics reported in the literature. Moreover, we show that the proposed heuristics are highly scalable and provide for high-speed realization justifying their applicability to complex MPSoC platforms.