首页> 外文期刊>Journal of Circuits, Systems, and Computers >MODERN FLOORPLANNING WITH BOUNDARY AND FIXED-OUTLINE CONSTRAINTS VIA GENETIC CLUSTERING ALGORITHM
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MODERN FLOORPLANNING WITH BOUNDARY AND FIXED-OUTLINE CONSTRAINTS VIA GENETIC CLUSTERING ALGORITHM

机译:通过遗传聚类算法进行边界和固定轮廓约束的现代平面规划

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摘要

Typical floorplanning problem concerns a series of objectives, such as area, wirelength and routability, etc., without any specific constraint in a free-outline style. Entering SOC era; however, modern floorplanning takes more care of providing extra options, such as boundary constraint for I/O connections and fixed-outline constraint for hierarchical designs. It has been empirically shown that one of the modern constraints extremely restricts the solution space; that is, a large number of randomly generated floorplans might be infeasible. This paper tackles modern floorplanning with both boundary and fixed-outline constraints. A novel genetic clustering algorithm was proposed to guarantee to produce slicing floorplans with satisfying boundary constraint. By analyzing the properties of the slicing floorplan, the algorithm is effective to cluster the boundary-constrained modules into four constrained sub-floorplans. Afterward, the four sub-floorplans were combined to satisfy the boundary constraint. We then extend the algorithm with minor modification to enable the slicing floorplans with boundary constraint to be gradually fit into the desirable fixed outline. The methods were verified by using the MCNC and GSRC benchmarks, and the empirical results show that our methods can obtain promising solutions using short time.
机译:典型的布局问题涉及一系列目标,例如面积,线长和可布线性等,在自由轮廓样式中没有任何特定限制。进入SOC时代;但是,现代布局规划更注重提供额外的选择,例如I / O连接的边界约束和分层设计的固定轮廓约束。经验表明,现代约束之一极大地限制了求解空间。也就是说,大量随机生成的平面图可能是不可行的。本文解决了具有边界和固定轮廓约束的现代平面规划。提出了一种新的遗传聚类算法,以保证产生满足边界约束的切片平面图。通过分析切片平面图的属性,该算法可有效地将边界约束模块聚类为四个约束子平面图。之后,将四个子平面图组合起来以满足边界约束。然后,我们以较小的修改扩展算法,以使具有边界约束的切片平面图逐渐适合所需的固定轮廓。通过使用MCNC和GSRC基准对方法进行了验证,经验结果表明我们的方法可以在短时间内获得有希望的解决方案。

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