Abstract
High-level simulation tools are used for optimization and design space exploration of digital circuits for a target Field Programmable Gate Array (FPGA) or Application Specific Integrated Circuit (ASIC) implementation. Compared to ASICs, FPGAs are slower and less power-efficient, but they are programmable, flexible and offer faster prototyping. One reason for the slow performance in FPGA is their finer granularity as they operate at bit-level. The possible solution is Coarse Grained Reconfigurable Architectures (CGRAs) that work at word-level. There already exists a myriad of CGRAs based on their architectural parameters. However, the CGRA research lacks in design automation since high-level simulation and optimization tools targeted at CGRAs are nearly non-existent. In this paper, we propose a high-level simulation and optimization framework for mesh-based homogeneous CGRAs. As expected, the results show that auto-generated homogeneous CGRAs consume 54% more resources when compared with academic FPGAs while providing around 63.3% faster mapping time.
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Pasha, M.A., Farooq, U., Ali, M., Siddiqui, B. (2017). A Framework for High Level Simulation and Optimization of Coarse-Grained Reconfigurable Architectures. In: Wong, S., Beck, A., Bertels, K., Carro, L. (eds) Applied Reconfigurable Computing. ARC 2017. Lecture Notes in Computer Science(), vol 10216. Springer, Cham. https://doi.org/10.1007/978-3-319-56258-2_12
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DOI: https://doi.org/10.1007/978-3-319-56258-2_12
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