Citation
Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore, Alberto Sangiovanni-Vincentelli. "Classification, Customization, and Characterization: Using MILP for Task Allocation and Scheduling". Technical report, University of California, Berkeley, UCB/EECS-2006-166, December, 2006.

Abstract
Task allocation and scheduling for heterogeneous multi-core platforms must be automated for such platforms to be successful. Techniques such as Mixed Integer Linear Programming (MILP) provide the ability to easily customize the allocation and scheduling problem to application or platform-specific peculiarities. The representation of the core problem in a MILP form has a large impact on the solution time required. In this paper, we investigate a variety of such representations and propose a taxonomy for them. A promising representation is chosen with extensive computational characterization. The MILP formulation is customized for a multimedia case study involving the deployment of a Motion JPEG encoder application onto a Xilinx Virtex II Pro FPGA platform. We demonstrate that our approach can produce solutions that are competitive with manual designs.

Electronic downloads

• http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-166.html

• HTML

  Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore,
  Alberto Sangiovanni-Vincentelli. <a
  href="http://chess.eecs.berkeley.edu/pubs/322.html"
  ><i>Classification, Customization, and
  Characterization: Using MILP for Task Allocation and
  Scheduling</i></a>, Technical report, 
  University of California, Berkeley, UCB/EECS-2006-166,
  December, 2006.

• Plain text

  Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore,
  Alberto Sangiovanni-Vincentelli. "Classification,
  Customization, and Characterization: Using MILP for Task
  Allocation and Scheduling". Technical report, 
  University of California, Berkeley, UCB/EECS-2006-166,
  December, 2006.

• BibTeX

  @techreport{DavareChongZhuDensmoreSangiovanniVincentelli06_ClassificationCustomizationCharacterizationUsingMILP,
      author = {Abhijit Davare and Jike Chong and Qi Zhu and
                Douglas Densmore and Alberto
                Sangiovanni-Vincentelli},
      title = {Classification, Customization, and
                Characterization: Using MILP for Task Allocation
                and Scheduling},
      institution = {University of California, Berkeley},
      number = {UCB/EECS-2006-166},
      month = {December},
      year = {2006},
      abstract = {Task allocation and scheduling for heterogeneous
                multi-core platforms must be automated for such
                platforms to be successful. Techniques such as
                Mixed Integer Linear Programming (MILP) provide
                the ability to easily customize the allocation and
                scheduling problem to application or
                platform-specific peculiarities. The
                representation of the core problem in a MILP form
                has a large impact on the solution time required.
                In this paper, we investigate a variety of such
                representations and propose a taxonomy for them. A
                promising representation is chosen with extensive
                computational characterization. The MILP
                formulation is customized for a multimedia case
                study involving the deployment of a Motion JPEG
                encoder application onto a Xilinx Virtex II Pro
                FPGA platform. We demonstrate that our approach
                can produce solutions that are competitive with
                manual designs.},
      URL = {http://chess.eecs.berkeley.edu/pubs/322.html}
  }
  

Posted by Christopher Brooks on 7 Jun 2007.
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