First-order incremental block-based statistical timing analysis
Proceedings of the 41st annual Design Automation Conference
Fast statistical timing analysis handling arbitrary delay correlations
Proceedings of the 41st annual Design Automation Conference
Statistical Timing Analysis Considering Spatial Correlations using a Single Pert-Like Traversal
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Statistical Timing Analysis for Intra-Die Process Variations with Spatial Correlations
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Statistical Timing Analysis with Extended Pseudo-Canonical Timing Model
Proceedings of the conference on Design, Automation and Test in Europe - Volume 2
Modeling Within-Die Spatial Correlation Effects for Process-Design Co-Optimization
ISQED '05 Proceedings of the 6th International Symposium on Quality of Electronic Design
Least-Squares Covariance Matrix Adjustment
SIAM Journal on Matrix Analysis and Applications
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Proceedings of the 2007 ACM/SIGDA 15th international symposium on Field programmable gate arrays
Prediction of leakage power under process uncertainties
ACM Transactions on Design Automation of Electronic Systems (TODAES)
ReCycle:: pipeline adaptation to tolerate process variation
Proceedings of the 34th annual international symposium on Computer architecture
Interactive presentation: Statistical dual-Vdd assignment for FPGA interconnect power reduction
Proceedings of the conference on Design, automation and test in Europe
Modeling and estimation of full-chip leakage current considering within-die correlation
Proceedings of the 44th annual Design Automation Conference
A general framework for spatial correlation modeling in VLSI design
Proceedings of the 44th annual Design Automation Conference
Statistical performance modeling and optimization
Foundations and Trends in Electronic Design Automation
Analysis of Power Supply Noise in the Presence of Process Variations
IEEE Design & Test
Static timing: back to our roots
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
Within-die process variations: how accurately can they be statistically modeled?
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Accurate and analytical statistical spatial correlation modeling for VLSI DFM applications
Proceedings of the 45th annual Design Automation Conference
Noninvasive leakage power tomography of integrated circuits by compressive sensing
Proceedings of the 13th international symposium on Low power electronics and design
Proceedings of the conference on Design, automation and test in Europe
System-level mitigation of WID leakage power variability using body-bias islands
CODES+ISSS '08 Proceedings of the 6th IEEE/ACM/IFIP international conference on Hardware/Software codesign and system synthesis
A statistical approach for full-chip gate-oxide reliability analysis
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Proceedings of the 2009 Asia and South Pacific Design Automation Conference
Accounting for non-linear dependence using function driven component analysis
Proceedings of the 2009 Asia and South Pacific Design Automation Conference
Self-Measurement of Combinatorial Circuit Delays in FPGAs
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
Proceedings of the 46th Annual Design Automation Conference
Full-chip model for leakage-current estimation considering within-die correlation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Post-fabrication measurement-driven oxide breakdown reliability prediction and management
Proceedings of the 2009 International Conference on Computer-Aided Design
Efficient additive statistical leakage estimation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Analog automatic test pattern generation for quasi-static structural test
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Analyzing the impact of process variations on parametric measurements: novel models and applications
Proceedings of the Conference on Design, Automation and Test in Europe
On confidence in characterization and application of variation models
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Variation-aware layout-driven scheduling for performance yield optimization
Proceedings of the International Conference on Computer-Aided Design
Active learning framework for post-silicon variation extraction and test cost reduction
Proceedings of the International Conference on Computer-Aided Design
Variation-aware leakage power model extraction for system-level hierarchical power analysis
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
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Increased variability of process parameters and recent progress in statistical static timing analysis make extraction of statistical characteristics of process variation and spatial correlation an important yet challenging problem in modern chip designs. Unfortunately, existing approaches either focus on extraction of only a deterministic component of spatial variation or do not consider actual difficulties in computing a valid spatial correlation function and matrix, simply ignoring the fact that not every function and matrix can be used to describe the spatial correlation. Based upon the mathematical theory of random fields and convex analysis, in this paper, we develop (1) a robust technique to extract a valid spatial correlation function by solving a constrained nonlinear optimization problem; and (2) a robust technique to extract a valid spatial correlation matrix by employing a modified alternative projection algorithm.Our novel techniques guarantee to extract a valid spatial correlation function and matrix that are closest to measurement data, even if those measurements are affected by unavoidable random noises. Experiment results based upon a Monte-Carlo model confirm the accuracy and robustness of our techniques, and show that we are able to recover the correlation function and matrix with very high accuracy even in the presence of significant random noises.