Adaptive multiclient network-on-chip memory core: hardware architecture, software abstraction layer, and application exploration

  • Authors:
  • Diana Göhringer;Lukas Meder;Stephan Werner;Oliver Oey;Jürgen Becker;Michael Hübner

  • Affiliations:
  • Institute for Data Processing and Electronics, Karlsruhe Institute of Technology and Object Recognition Department, Fraunhofer IOSB, Ettlingen, Germany;Institute for Information Processing Technology, Karlsruhe Institute of Technology, Karlsruhe, Germany;Institute for Information Processing Technology, Karlsruhe Institute of Technology, Karlsruhe, Germany;Institute for Information Processing Technology, Karlsruhe Institute of Technology, Karlsruhe, Germany;Institute for Information Processing Technology, Karlsruhe Institute of Technology, Karlsruhe, Germany;Ruhr-University of Bochum, Bochum, Germany

  • Venue:
  • International Journal of Reconfigurable Computing - Special issue on Selected Papers from the 2011 International Conference on Reconfigurable Computing and FPGAs (ReConFig 2011)
  • Year:
  • 2012

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Abstract

This paper presents the hardware architecture and the software abstraction layer of an adaptive multiclient Network-on-Chip (NoC) memory core. The memory core supports the flexibility of a heterogeneous FPGA-based runtime adaptive multiprocessor system called RAMPSoC. The processing elements, also called clients, can access the memory core via the Network-on-Chip (NoC). The memory core supports a dynamic mapping of an address space for the different clients as well as different data transfer modes, such as variable burst sizes. Therefore, two main limitations of FPGA-based multiprocessor systems, the restricted on-chip memory resources and that usually only one physical channel to an off-chip memory exists, are leveraged. Furthermore, a software abstraction layer is introduced, which hides the complexity of the memory core architecture and which provides an easy to use interface for the application programmer. Finally, the advantages of the novel memory core in terms of performance, flexibility, and user friendliness are shown using a real-world image processing application.