FPRESSO:实现FPGA架构的快速晶体管级探索

Grace Zgheib, M. Lortkipanidze, Muhsen Owaida, D. Novo, P. Ienne
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引用次数: 15

摘要

理论上,像VTR这样的工具——一种可重新定位的工具链,将电路映射到易于描述的假设FPGA架构上——可以在广泛创新的FPGA架构的开发中发挥关键作用。然而,在实践中,可以使用这些工具进行的实验受到FPGA架构师产生可靠延迟和面积模型的能力的严重限制-这些依赖于需要不同技能的晶体管级设计技术。在本文中,我们介绍了一种新颖的方法,我们称之为Fpresso,以快速和合理的精度对各种不同的FPGA架构的延迟和面积进行建模。我们从标准单元流程执行大规模晶体管尺寸优化的方式中获得灵感,并将相同的概念应用于fpga,只是粒度更粗。熟练的用户准备\fpresso本地优化库的基本组件具有各种驱动优势。然后,普通用户指定任意FPGA架构作为基本组件的互连。这是通过一个普通的逻辑合成工具在几分钟内进行全局优化,该工具选择每个细胞最合适的版本,并在适当的地方添加缓冲区。由此产生的延迟和面积特性可以自动用于VTR。我们的结果表明,fpresso提供的模型平均在最先进的FPGA优化工具的模型的10- 20%之内,并且速度要快几个数量级。尽管建模误差可能显得相对较高,但我们表明它很少导致对一组体系结构的错误排序,从而表明了合理的建模可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FPRESSO: Enabling Express Transistor-Level Exploration of FPGA Architectures
In theory, tools like VTR---a retargetable toolchain mapping circuits onto easily-described hypothetical FPGA architectures---could play a key role in the development of wildly innovative FPGA architectures. In practice, however, the experiments that one can conduct with these tools are severely limited by the ability of FPGA architects to produce reliable delay and area models---these depend on transistor-level design techniques which require a different set of skills. In this paper, we introduce a novel approach, which we call Fpresso, to model the delay and area of a wide range of largely different FPGA architectures quickly and with reasonable accuracy. We take inspiration from the way a standard-cell flow performs large scale transistor-size optimization and apply the same concepts to FPGAs, only at a coarser granularity. Skilled users prepare for \fpresso locally optimized libraries of basic components with a variety of driving strengths. Then, ordinary users specify arbitrary FPGA architectures as interconnects of basic components. This is globally optimized within minutes through an ordinary logic synthesis tool which chooses the most fitting version of each cell and adds buffers wherever appropriate. The resulting delay and area characteristics can be automatically used for VTR. Our results show that \fpresso provides models that are on average within some 10-20\% of those by a state-of-the-art FPGA optimization tool and is orders of magnitude faster. Although the modelling error may appear relatively high,we show that it seldom results in misranking a set of architectures, thus indicating a reasonable modeling faithfulness.
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