This paper discusses design methodology of high-throughput arithmetic pipeline modules for an FPGA-based biochemical simulator. Since limitation of data-input bandwidth caused by port constraints often has a negative impact on pipeline scheduling results, we propose a priority assignment method of input data which enables efficient arithmetic pipeline scheduling under given input port constraints. Evaluation results with frequently used rate-law functions in biochemical models revealed that the proposed method achieved shorter latency compared to ASAP and ALAP scheduling with random input orders, reducing hardware costs by 17.57% and by 27.43% on average, respectively.
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