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引用次数: 47
摘要
我们展示了随机投影,即将一组点投射到随机选择的低维子空间的技术,可以用于解决VLSI布局中的问题。具体而言,对于在二维网格上布置图以最小化最大边长问题,我们获得了O(log/sup 3.5/ n)近似算法(这是第一个O(n)近似),对于最小化总边长同时保持最大长度有界的双准则问题,我们获得了O(log/sup 3/ n, log/sup 3.5/ n)近似。我们的算法也适用于这些问题的d维版本(对于任何固定的d),具有多对数近似保证。除随机投影外,该算法的主要组成部分是线性规划松弛和尊重体积的欧几里得嵌入。
We show that random projection, the technique of projecting a set of points to a randomly chosen low-dimensional subspace, can be used to solve problems in VLSI layout. Specifically, for the problem of laying out a graph on a 2-dimensional grid so as to minimize the maximum edge length, we obtain an O(log/sup 3.5/ n) approximation algorithm (this is the first o(n) approximation), and for the bicriteria problem of minimizing the total edge length while keeping the maximum length bounded, we obtain an O(log/sup 3/ n, log/sup 3.5/ n) approximation. Our algorithms also work for d-dimensional versions of these problems (for any fixed d) with polylog approximation guarantees. Besides random projection, the main components of the algorithms are a linear programming relaxation, and volume-respecting Euclidean embeddings.