Exploring adjacency in floorplanning

Abstract

Abstract-This paper describes a new floorplanning approach called Constrained Adjacency Graph (CAG) that helps exploring adjacency in floorplans. CAG extends the previous adjacency graph approaches by adding explicit adjacency constraints to the graph edges. After sufficient and necessary conditions of CAG are developed based on dissected floorplans, CAG is extended to handle general floorplans in order to improve area without changing the adjacency relations dramatically. These characteristics are currently utilized in a randomized greedy improvement heuristic for wire length optimization. The results show that better floorplans are found with much less running time for problems with 100 to 300 modules in comparison to a simulated annealing floorplanner based on sequence pairs.

Enumeration technique in very large‐scale integration fixed‐outline floorplanning

“…The HPWL results of EFP are compared with the following state‐of‐the‐art and recent floorplanning/placement algorithms: IMF [6], Parquet [1], IARFP [7], Defer [13], PATOMA [10], Capo [3], CAG [30] and Greedy TCG floorplanner (G‐TCG) [31], as shown in Table 3. In Table 3, the best results among the algorithms for individual benchmark test cases are shown in bold case where EFP shows the best results in 6 out of 9 benchmark cases with 66.6%, followed by Defer with 33.3%.…”

A greedy algorithm for wire length optimization

“…Some representative floorplanners are listed as below, Normalized Polish Expression (NPE) [1], Sequence-Pair (SP) [2], Bounded Slicing Grid (BSG) [3], O-Tree [4], B*-Tree [5] and Transitive Closure Graph (TCG) [6]. Other floorplanning algorithms with new ideas are also proposed, such as [7][8][9][10][11][12]. The amount of researches on the topic reflects the importance of floorplanning, but all of them place blocks to the lower-left (upper-right) corner and then evaluate the wire length.…”