Two Clustering Preprocessing Techniques for Large-Scale Circuits

Behjat, Laleh; Li, J.; Rakai, Logan; Huang, Jie

doi:10.1109/iscas.2007.378191

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Proposed Degree-based Clustering Algorithm 31 Algorithm Mot1

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2009

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“…However, the connectivity measure usually favors nets with low-degree. For example, in Figure 2 it is illustrated that after one level of clustering using FirstChioce, bestchoice, Net Cluster and hyperedge for ibm11 in ICCAD04 benchmark suite, more than 65% of the clustered nets are ones with degree 2 [18]. benchmark suite [18].…”

Section: Proposed Degree-based Clustering Algorithm 31 Algorithm Motmentioning

confidence: 99%

A Degree-Based Clustering Technique for VLSI Placement

Huang

Behjat

Rakai

et al. 2009

Journal of Algorithms & Computational Technology

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In this paper, clustering for the circuit placement problem is examined from the perspective of wire length contribution from groups of nets.First, the final wire length data of groups of nets with different degrees are extracted and studied. It is illustrated that nets with high-degree contribute a high percentage to the total wire length. To remedy this problem, a clustering algorithm for placement is proposed that focuses on clustering nets with high-degree. This new clustering algorithm is implemented as a preprocessing step in the placement stage. ICCAD04 benchmark circuits abstracted from IBM are used to validate the placement quality by using four academic placers with and without the proposed preprocessing step. Experiments show that the overall placement results can be improved by up to 5%.

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Section: Proposed Degree-based Clustering Algorithm 31 Algorithm Motmentioning

confidence: 99%