论文标题
Autocelllibx:基于模式挖掘的自动化标准单元格库扩展
AutoCellLibX: Automated Standard Cell Library Extension Based on Pattern Mining
论文作者
论文摘要
自定义标准单元格库可以提高相应的VLSI设计的最终质量,但是由于VLSI设计的复杂特征,正确自定义标准单元格库仍然具有挑战性。本文提出了一个自动标准细胞库扩展框架,Autocelllibx。它可以根据我们的高效率频繁的子级挖掘算法来考虑标准细胞特征和技术映射约束,从而考虑了一组标准的细胞群集候选闸门级网级候选。同时,为了最大化给定门级网络清单的标准单元定制的区域益处,Autocelllibx包括我们提出的模式组合算法,可以迭代地从众多候选人中找到一组栅极级别的模式,作为给定初始标准单元格的扩展部分。据我们所知,Autocelllibx是第一个自动化标准单元格扩展框架,它在Gate级Netlist的分析和VLSI设计生产力的标准单元格自定义的分析之间关闭了优化循环。来自各个域的FreepDK45库和基准测试的实验表明,AutoCelllibx可以在31个基准设计中的每个基准设计中,在1.1小时内产生最多5个自定义标准单元格,并且标准单元格库的最终扩展可将设计区域的延伸降低4.49%。
Custom standard cell libraries can improve the final quality of the corresponding VLSI designs but properly customizing standard cell libraries remains challenging due to the complex characteristics of the VLSI designs. This paper presents an automatic standard-cell library extension framework, AutoCellLibX. It can find a set of standard cell cluster pattern candidates from the post-technology mapping gate-level netlist, with the consideration of standard cell characteristics and technology mapping constraints, based on our high-efficiency frequent subgraph mining algorithm. Meanwhile, to maximize the area benefit of standard cell customization for the given gate-level netlist, AutoCellLibX includes our proposed pattern combination algorithm which can iteratively find a set of gate-level patterns from numerous candidates as the extension part of the given initial standard cell library. To the best of our knowledge, AutoCellLibX is the first automated standard cell extension framework that closes the optimization loop between the analysis of gate-level netlist and standard cell library customization for VLSI design productivity. The experiments with FreePDK45 library and benchmarks from various domains show that AutoCellLibX can generate the library extension with up to 5 custom standard cells within 1.1 hours for each of the 31 benchmark designs and the resultant extension of the standard cell library can save design area by 4.49% averagely.