ICCAD '92 1992 IEEE/ACM international conference proceedings on Computer-aided design
Introduction to Algorithms
On the performance of level-clocked circuits
ARVLSI '95 Proceedings of the 16th Conference on Advanced Research in VLSI (ARVLSI'95)
First-order incremental block-based statistical timing analysis
Proceedings of the 41st annual Design Automation Conference
Convergence-provable statistical timing analysis with level-sensitive latches and feedback loops
ASP-DAC '06 Proceedings of the 2006 Asia and South Pacific Design Automation Conference
mPL6: enhanced multilevel mixed-size placement
Proceedings of the 2006 international symposium on Physical design
Statistical timing analysis under spatial correlations
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Statistical timing verification for transparently latched circuits
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Advances in Computation of the Maximum of a Set of Gaussian Random Variables
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Statistical Timing Analysis: From Basic Principles to State of the Art
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Fast statistical timing analysis of latch-controlled circuits for arbitrary clock periods
Proceedings of the International Conference on Computer-Aided Design
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Level-sensitive transparent latches are widely used in high-performance sequential circuit designs. Under process variations, the timing of a transparently latched circuit will adapt random delays at runtime due to time borrowing. The central problem to determine the timing yield is to compute the probability of the presence of a positive cycle in the latest latch timing graph. Existing algorithms are either optimistic since cycles are omitted or require iterations that cannot be polynomially bounded. In this paper, we present the first algorithm to compute such probability based on block-based statistical timing analysis that, first, covers all cycles through a structural graph traversal, and second, terminates within a polynomial number of statistical "sum" and "max" operations. Experimental results confirm that the proposed approach is effective and efficient.