• DocumentCode
    3433101
  • Title

    MAX: A Multi Objective Memory Architecture eXploration Framework for Embedded Systems-on-Chip

  • Author

    Kumar, T. S Rajesh ; Ravikumar, C.P. ; Govindarajan, R.

  • Author_Institution
    Texas Instruments India Ltd., Bangalore
  • fYear
    2007
  • fDate
    Jan. 2007
  • Firstpage
    527
  • Lastpage
    533
  • Abstract
    Today´s feature-rich multimedia products require embedded system solution with complex System-on-Chip (SoC) to meet market expectations of high performance at a low cost and lower energy consumption. The memory architecture of the embedded system strongly influences these parameters. Hence the embedded system designer performs a complete memory architecture exploration. This problem is a multi-objective optimization problem and can be tackled as a two-level optimization problem. The outer level explores various memory architecture while the inner level explores placement of data sections (data layout problem) to minimize memory stalls. Further, the designer would be interested in multiple optimal design points to address various market segments. However, tight time-to-market constraints enforces short design cycle time. In this paper we address the multi-level multi-objective memory architecture exploration problem through a combination of Multi-objective Genetic Algorithm (Memory Architecture exploration) and an efficient heuristic data placement algorithm. At the outer level the memory architecture exploration is done by picking memory modules directly from a ASIC memory Library. This helps in performing the memory architecture exploration in a integrated framework, where the memory allocation, memory exploration and data layout works in a tightly coupled way to yield optimal design points with respect to area, power and performance. We experimented our approach for 3 embedded applications and our approach explores several thousand memory architecture for each application, yielding a few hundred optimal design points in a few hours of computation time on a standard desktop
  • Keywords
    application specific integrated circuits; embedded systems; genetic algorithms; memory architecture; system-on-chip; ASIC memory library; application specific integrated circuits; data sections; embedded systems-on-chip; genetic algorithm; heuristic data placement; market segments; memory stalls; multi-objective memory architecture; Application specific integrated circuits; Costs; Embedded system; Energy consumption; Genetic algorithms; Heuristic algorithms; Memory architecture; System-on-a-chip; Time to market; Videos;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    VLSI Design, 2007. Held jointly with 6th International Conference on Embedded Systems., 20th International Conference on
  • Conference_Location
    Bangalore
  • ISSN
    1063-9667
  • Print_ISBN
    0-7695-2762-0
  • Type

    conf

  • DOI
    10.1109/VLSID.2007.102
  • Filename
    4092096