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Optimizing coarse-grained units in floating point hybrid FPGA

机译:在浮点混合FPGA中优化粗粒度单元

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This paper introduces a novel methodology to optimize coarse-grained floating point units (FPUs) in a hybrid FPGA. We employ common subgraph extraction to determine the number of floating point adders/subtracters (FAs), multipliers (FMs) and wordblocks (WBs) in the FPUs. We flrst study the area, speed and utilization trade-off of the selected FPU subgraphs in a set of floating point benchmark circuits. We then explore the impact of density and flexibility of FPUs on the system in terms of area, speed and routing resources. We derive an optimized coarse-grained FPU by considering both architectural and system level issues. The results show that: (1) embedding more types of coarse-grained FPU in the system causes at most 21.3% increase in delay, (2) the area of the system can be reduced by 27.4% by embedding high density subgraphs, (3) the high density subgraphs requires 14.8% fewer routing resources.
机译:本文介绍了一种在混合FPGA中优化粗粒度浮点单元(FPU)的新颖方法。我们使用常见的子图提取来确定FPU中的浮点加法器/减法器(FA),乘法器(FM)和字块(WBs)的数量。我们首先在一组浮点基准电路中研究所选FPU子图的面积,速度和利用率的取舍。然后,我们从面积,速度和路由资源的角度探讨FPU的密度和灵活性对系统的影响。通过考虑体系结构和系统级别的问题,我们得出了优化的粗粒度FPU。结果表明:(1)在系统中嵌入更多类型的粗粒度FPU最多导致21.3%的延迟增加;(2)通过嵌入高密度子图可以将系统面积减少27.4%,(3 )高密度子图所需的路由资源减少了14.8%。

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