Conference proceeding
Statistical Timing Analysis of Nonzero Clock Skew Circuits
2008 51ST MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1 AND 2, pp 605-608
01 Jan 2008
Abstract
Statistical Static Timing Analysis (SSTA) methods, which model process variations statistically as probability distribution functions (PDFs) rather than deterministically, have emerged to more accurately portray integrated circuit performance. This analysis has been thoroughly performed on traditional zero clock skew circuits where the synchronizing clock signal is assumed to arrive in phase with respect to each register. However, designers will often schedule the clock skew to different registers in order to decrease the minimum clock period of the entire circuit. Clock skew scheduling (CSS) imparts very different timing constraints that are based, in part, on the topology of the circuit. In this paper, SSTA is applied to nonzero clock skew circuits in order to determine the accuracy improvement relative to their zero skew counterparts, and also to assess how the results of skew scheduling might be impacted with more accurate statistical modeling. For 99.7% timing yield (3 sigma variation), SSTA is observed to improve tire accuracy of measurement, thereby increasing the average clock period improvement to 38.25% as compared to zero clock skew circuits.
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Details
- Title
- Statistical Timing Analysis of Nonzero Clock Skew Circuits
- Creators
- Shannon Kurtas - Drexel UniversityBaris Taskin - Drexel UniversityIEEE
- Publication Details
- 2008 51ST MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1 AND 2, pp 605-608
- Series
- Midwest Symposium on Circuits and Systems Conference Proceedings
- Publisher
- IEEE
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000261729500152
- Scopus ID
- 2-s2.0-54249167159
- Other Identifier
- 991019169113704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Hardware & Architecture
- Computer Science, Information Systems
- Engineering, Electrical & Electronic