Abstract
The patterns and evolution of man-made complex networks have been topics of interest in recent years. Herein, we define appropriate metrics to quantify the correlations between circuit performance and the complex network characteristics regarding the physical design of circuits. The experimental results show that circuit performance differs due to the optimization tools, both at placement and routing. The strength of the correlations with placement design follows the order of average distance, betweenness, average strength, and the clustering coefficient; the strength of the correlations with layout design follows the order of betweenness, average strength, average distance, and the clustering coefficient. The correlation between performance and betweenness has been further strengthened after routing and presents a remarkable difference in comparison with other characteristic parameters, which indicates its significance to the dynamic correlation with circuit performance.
Highlights
INTRODUCTIONWith the enormous progress of semiconductor manufacturing technology, VLSI (very-large-scale integration circuit) design has achieved rapid development following Moore’s Law
With the enormous progress of semiconductor manufacturing technology, VLSI design has achieved rapid development following Moore’s Law
The correlation between circuit performance and betweenness has been further strengthened after routing, and it presents a remarkable difference in comparison with other characteristic parameters
Summary
With the enormous progress of semiconductor manufacturing technology, VLSI (very-large-scale integration circuit) design has achieved rapid development following Moore’s Law. Oshida et al investigated the network-on-chip (NoC) performance with different structures through dynamic flow analysis They found that the NoC architecture constructed with the topology in which hubs mostly connect to lower-degree nodes achieves short latency and low packet loss ratio [28]. Zhan et al devised a multi-layered design architecture to capture favorable characteristics of biological mechanisms for the application of electronic circuit design. This demonstrates that utilizing biological mechanisms for engineering design is a promising approach for building intelligent systems [29]. We analyze the correlations between circuit performance and the complex network characteristics of the physical design of integrated circuits, and explore the strength of the correlations with placement and routing. It introduces the fundamental characteristic related to weighted complex networks in the second section, conducts experiment schemes and analyze results in the third section, and concludes in the fourth section
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