A Flexible Software Framework for Dynamic Task Allocation on MPSoCs Evaluated in an Automotive Context

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• 作者：Jens Rettkowski (17)
  Philipp Wehner (17)
  Marc Sch眉lper (17)
  Diana G枚hringer (17)
  
  17. Ruhr-University Bochum ; Bochum ; Germany
  
• 关键词：Dynamic task allocation ; MPSoC ; Automotive application ; Car2Car communication ; FPGA
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9040
• 期：1
• 页码：255-266
• 全文大小：890 KB
• 参考文献：1. Baloukas, C., Papadopoulos, L., Soudris, D., et al.: Mapping embedded applications on MPSoCs: the MNEMEE approach. In: IEEE Computer Society Annual Symposium on VLSI, pp. 512鈥?17 (July 2010)
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  13. Rettkowski, J., Goehringer, D.: RAR-NoC: A reconfigurable and adaptive routable network-on-chip for FPGA-based multiprocessor systems. In: International Conference on ReConFigurable Computing and FPGAs (ReConFig) (December 2014)
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• 作者单位：Applied Reconfigurable Computing
• 丛书名：978-3-319-16213-3
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

For a wide variety of applications such as multimedia applications, the number of tasks running simultaneously on Multiprocessor Systems-on-Chip (MPSoCs) changes dynamically at runtime. An intelligent resource management is required to efficiently map these tasks onto the processing elements. In this paper, a new flexible software framework for allocating tasks dynamically onto a heterogeneous MPSoC is presented. This MPSoC contains an ARM processor and multiple MicroBlazes. The framework maps the tasks on the MicroBlazes based on various strategies which are selectable to meet the application-specific demands. The performance of the framework is evaluated by an automotive application. In this context, an electronic control unit uses the proposed framework to avoid collisions with other vehicles. Thereby, realistic data given by a car simulator is distributed to the processing elements of the MPSoC. Here, the distance of vehicles influences the scheduling. The evaluation shows that this approach exploits the MPSoC scalability and simplifies the programming and efficient use of such systems.