A Fast Clustering‐Based Min‐Cut Placement AlgorithmWith Simulated‐Annealing Performance

Abstract

Placement is an important constrained optimization problem in the design of very large scale (VLSI) integrated circuits [1–4]. Simulated annealing [5] and min-cut placement [6] are two of the most successful approaches to the placement problem. Min-cut methods yield less congested and more routable placements at the expense of more wire-length, while simulated annealing methods tend to optimize more the total wire-length with little emphasis on the minimization of congestion. It is also well known that min-cut algorithms are substantially faster than simulated-annealing-based methods. In this paper, a fast min-cut algorithm (ROW-PLACE) for row-based placement is presented and is empirically shown to achieve simulated-annealing-quality wire-length on a number of benchmark circuits. In comparison with Timberwolf 6 [7], ROW-PLACE is at least 12 times faster in its normal mode and is at least 25 times faster in its faster mode. The good results of ROW-PLACE are achieved using a very effective clustering-based partitioning algorithm in combination with constructive methods that reduce the wire-length of nets involved in terminal propagation.

Congestion driven incremental placement algorithm for standard cell layout

“…Then estimating the congestion of a global bin can be replaced by computing the total overflow of the global edges as (2) and cost function is defined as (3). Most of the algorithms for reducing congestion [6][7][8][9][10] ) ( cos (3) This method to estimate congestion is ill behaved.…”

“…Most of the algorithms for reducing congestion [6][7][8][9][10] ) ( cos (3) This method to estimate congestion is ill behaved. It can only detect the congestion area that is crossed by a global edge.…”

“…Because of its constructive nature, min-cut based strategies minimize the number of net crossings but fail to distribute them uniformly [3]. For the same reason, traditional placement schemes which are based mainly on wirelength minimization can not adequately account for congestion.…”

Congestion driven quadratic placement

“…Due to their constructive nature, min-cut based strategies minimize the number of net crossings but fail to uniformly distribute them [14]. Quad-partitioning schemes, first demonstrated in [8] did account for some global routing resources, but did not address supply nor account for internal routing.…”

Congestion driven incremental placement algorithm for standard cell layout

“…Traditional placement objectives involve reducing net-cut costs or minimizing wire length [1][2]. Because of its constructive nature, min-cut based strategies minimize the number of net crossings but fail to distribute them uniformly [3]. For the same reason, traditional placement schemes which are based mainly on wirelength minimization can not adequately account for congestion.…”