DRuiD: Designing reconfigurable architectures with decision-making support

Application development for heterogeneous platforms requires to code and map functionalities on a set of different computing elements. As a consequence, the development process needs a clear understanding of both, application requirements and heterogeneous computing technologies. To support the development process, we propose a framework called DRuiD capable of learning application characteristics that make them suitable for certain computing elements. The framework is composed of an expert system that supports the designer in the mapping decision and gives hints on possible code modifications to be applied to make the functionality more suitable for a computing element. The experimental results are tailored for a heterogeneous and reconfigurable platform (the Xilinx-ml510) including two computational elements, i.e. a Virtex5 FPGA and a PowerPC. The expert system identifies 88.9% of the times what are the functionalities that are accelerated efficiently by using the FPGA, without requiring the kernel porting. Additionally, we present two case studies demonstrating the potentialities of the framework to give hints on high level code modifications for an efficient kernel mapping on the FPGA.