scholarly journals CONTANGO: Integrated Optimization of SoC Clock Networks

VLSI Design ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Dong-Jin Lee ◽  
Igor L. Markov

On-chip clock networks are remarkable in their impact on the performance and power of synchronous circuits, in their susceptibility to adverse effects of semiconductor technology scaling, as well as in their strong potential for improvement through better CAD algorithms and tools. Existing literature is rich in ideas and techniques but performs large-scale optimization using analytical models that lost accuracy at recent technology nodes and have rarely been validated by realistic SPICE simulations on large industry designs. Our work offers a methodology for SPICE-accurate optimization of clock networks, coordinated to satisfy slew constraints and achieve best tradeoffs between skew, insertion delay, power, as well as tolerance to variations. Our implementation, called Contango, is evaluated on 45 nm benchmarks from IBM Research and Texas Instruments with up to 50 K sinks. It outperforms all published results in terms of skew and shows superior scalability.

2020 ◽  
Vol 53 (2) ◽  
pp. 12572-12577
Author(s):  
Fernando Lezama ◽  
Ricardo Faia ◽  
Omid Abrishambaf ◽  
Pedro Faria ◽  
Zita Vale

Author(s):  
Jie Guo ◽  
Zhong Wan

A new spectral three-term conjugate gradient algorithm in virtue of the Quasi-Newton equation is developed for solving large-scale unconstrained optimization problems. It is proved that the search directions in this algorithm always satisfy a sufficiently descent condition independent of any line search. Global convergence is established for general objective functions if the strong Wolfe line search is used. Numerical experiments are employed to show its high numerical performance in solving large-scale optimization problems. Particularly, the developed algorithm is implemented to solve the 100 benchmark test problems from CUTE with different sizes from 1000 to 10,000, in comparison with some similar ones in the literature. The numerical results demonstrate that our algorithm outperforms the state-of-the-art ones in terms of less CPU time, less number of iteration or less number of function evaluation.


Sign in / Sign up

Export Citation Format

Share Document