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An Overlap-based MILP Formulation for Task Allocation and Scheduling
Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore, Alberto Sangiovanni-Vincentelli

Citation
Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore, Alberto Sangiovanni-Vincentelli. "An Overlap-based MILP Formulation for Task Allocation and Scheduling". submitted, October, 2006.

Abstract
The deployment of applications on heterogeneous multi-core platforms is one of the most important challenges in the embedded systems design flow. In this paper, we develop an automated approach to tackle this problem that uses an efficient and extensible Mixed Integer Linear Programming (MILP) formulation. We show the effectiveness of our approach with extensive computational testing. For a case study involving the deployment of a Motion JPEG encoder application onto a Xilinx Virtex II Pro FPGA platform, we demonstrate that our automated approach can accurately capture the design space and yield systems that are competitive with manual designs.

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  • HTML
    Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore,
    Alberto Sangiovanni-Vincentelli. <a
    href="http://chess.eecs.berkeley.edu/pubs/119.html"
    >An Overlap-based MILP Formulation for Task Allocation
    and Scheduling</a>, submitted, October, 2006.
  • Plain text
    Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore,
    Alberto Sangiovanni-Vincentelli. "An Overlap-based MILP
    Formulation for Task Allocation and Scheduling".
    submitted, October, 2006.
  • BibTeX
    @inproceedings{DavareChongZhuDensmoreSangiovanniVincentelli06_OverlapbasedMILPFormulationForTaskAllocationScheduling,
        author = {Abhijit Davare and Jike Chong and Qi Zhu and
                  Douglas Densmore and Alberto
                  Sangiovanni-Vincentelli},
        title = {An Overlap-based MILP Formulation for Task
                  Allocation and Scheduling},
        booktitle = {submitted},
        month = {October},
        year = {2006},
        abstract = {The deployment of applications on heterogeneous
                  multi-core platforms is one of the most important
                  challenges in the embedded systems design flow. In
                  this paper, we develop an automated approach to
                  tackle this problem that uses an efficient and
                  extensible Mixed Integer Linear Programming (MILP)
                  formulation. We show the effectiveness of our
                  approach with extensive computational testing. For
                  a case study involving the deployment of a Motion
                  JPEG encoder application onto a Xilinx Virtex II
                  Pro FPGA platform, we demonstrate that our
                  automated approach can accurately capture the
                  design space and yield systems that are
                  competitive with manual designs. },
        URL = {http://chess.eecs.berkeley.edu/pubs/119.html}
    }
    

Posted by Abhijit Davare on 15 May 2006.
Groups: chesslocal
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