False-noise analysis for domino circuits

Abstract

High-performance digital circuits are facing increasingly severe noise problems due to cross-coupled noise injection. Traditionally, noise analysis tools use the conservative assumption that all neighbors of a net can switch simultaneously, producing the worst-case noise. However, due to logic correlations in the circuit, this worst-case noise may not be realizable, resulting in a so-called false noise failure. Some techniques for computing logic correlations have been designed targeting static CMOS circuits. However high performance microprocessors commonly use domino logic for their ALU. The domino circuits have lower noise margins than static CMOS circuits and are more sensitive to coupled noise. Any unnecessary pessimism of the noise analysis tool results in large number of false noise violations and either requires additional extensive SPICE simulations or circuit over-design. Unfortunately false noise analysis developed for static CMOS circuits fails to compute many logic correlations in domino circuits. In this paper we propose a novel technique of computing logic correlations in domino circuits. It takes into account the fact that both pull up and pull down networks of a domino gate can be in non conducting state. The proposed technique generates additional logic correlations for such states of domino gates. In order to improve the capability of logic correlation derivation technique we combine the resolution method with recursive learning algorithm. The proposed technique is implemented in an industrial noise analysis tool and tested on high performance ALU blocks.