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Cost reduction in bottom-up hierarchical-based VLSI floorplanning designs

机译:自下而上的基于层次的VLSI布局设计中的成本降低

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From the industrial perspective, floorplanning is a crucial step in the VLSI physical design process as its efficiency determines the quality and the time-to-market of the product. A new perturbation method, called Cull-and-Aggregate Bottom-up Floorplanner (CABF), which consists of culling and aggregating stages, is developed to perform variable-order automated floorplanning for VLSI. CABF will generate VLSI floorplan layout by calculating the modules' dimensions' differences (hard module floorplanning problems) and the modules' areas' differences (soft module floorplanning problems). Through mathematical derivation, the hard modules floorplanning area minimization cost function (two-dimensional) during culling stage is proven that a dimensional reduction can be carried out to be the difference-based cost function (one-dimensional) which simplifies the computation. During the culling stage, CABF employs linear ordering method to select and determine the order of modules where this linear runtime complexity property allows CABF to cull the modules faster. The aggregating stage of CABF will reduce the subsequent search space of this floorplanner, and the variable order aggregation enables CABF to search for the best near-optimal solution. Based on Gigascale Systems Research Center and Microelectronics Center of North Carolina circuit benchmarks, CABF gives better optimal solutions and faster runtimes for floorplanning problems involving 9 to 600 modules. This has established that CABF is performing well in respect of reliability and scalability. Besides, CABF shows its potential to be implemented in VLSI physical design as the runtime of CABF is faster with a near-optimal outcome as compared to.the other existing algorithms.
机译:从工业角度来看,布局规划是VLSI物理设计过程中的关键步骤,因为它的效率决定了产品的质量和上市时间。开发了一种新的摄动方法,称为剔除和聚合自下而上的平面规划器(CABF),它由剔除和聚合阶段组成,用于执行VLSI的可变顺序自动平面规划。 CABF将通过计算模块尺寸的差异(硬模块平面规划问题)和模块的面积差异(软模块平面规划问题)来生成VLSI平面布置图。通过数学推导,在剔除阶段将硬模块平面规划面积最小化成本函数(二维)证明,可以将维数减少为基于差异的成本函数(一维),从而简化了计算。在剔除阶段,CABF采用线性排序方法来选择和确定模块的顺序,其中线性运行时复杂度属性使CABF可以更快地剔除模块。 CABF的聚合阶段将减少此布局规划器的后续搜索空间,而可变顺序聚合使CABF可以搜索最佳的接近最优的解决方案。基于北卡罗来纳州Gigascale系统研究中心和微电子中心电路基准,CABF为涉及9到600个模块的布局规划问题提供了更好的最佳解决方案和更快的运行时间。这表明CABF在可靠性和可伸缩性方面表现良好。此外,CABF显示了其在VLSI物理设计中实现的潜力,因为与其他现有算法相比,CABF的运行速度更快,并且结果接近最佳。

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