Classification, Customization, and Characterization: Using MILP for Task Allocation and Scheduling

Task allocation and scheduling for heterogeneous multicore 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.

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