We present a methodology for generating optimized architectures for data bandwidth constrained extensible processors. We describe a scalable Integer Linear Programming (ILP)

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Abstract-In partially reconfigurable architectures, system components can be dynamically loaded and unloaded allowing resources to be shared over time. This paper focuses on the relation between the design options of partial reconfiguration modules and their placement at run-time. For a set of dynamic system components, we propose a design method that optimizes the feasible positions of the resulting partial reconfiguration modules to minimize position overlaps. We introduce the concept of subregions, which guarantees the parallel execution of a certain number of partial reconfiguration modules for tiled reconfigurable systems. Experimental results, which are based on a Xilinx Virtex-4 implementation, show that at run-time the average number of available positions can be increased up to 6.4 times and the number of placement violations can be reduced up to 60.6%.

Hardware sharing can be used to reduce the area and the power dissipation of a design. This is of particular interest in the field of image and video compression, where an encoder must deal with different design tradeoffs depending on the characteristics of the signal to be encoded and the constraints imposed by the users. This paper introduces a novel methodology for exploring the design space based on the amount of hardware sharing between different functional blocks, giving as a result a set of feasible solutions which are broad in terms of hardware cost and throughput capabilities. The proposed approach, inspired by the notion of a partition in set theory, has been applied to optimize and to evaluate the sharing alternatives of a group of image and video compression key computational kernels when mapped onto a Xilinx Virtex-5 FPGA.

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