High Sigma Analysis - University of California, Los...
17
High Sigma Analysis
Transcript of High Sigma Analysis - University of California, Los...
High Sigma Analysis
Outline
• Preliminary of High Sigma Analysis
• A Fast and Provably Bounded Failure Analysis of Memory Circuits in High Dimensions
• Hyperspherical Clustering and Sampling for Rare Event Analysis with Multiple Failure Region Coverage
• REscope: High-dimensional Statistical Circuit Simulation towards Full Failure Region Coverage
High Sigma Analysis
High Sigma Analysis
High Sigma Analysis
Basic Idea in Importance Sampling
The Proposed Method
Stage2: Choosing Mean and Sigma for Yt
Stage3: Evaluation of Conditional Probability
High Sigma Analysis
High Sigma Analysis
High Sigma Analysis
Hyperspherical clustering and sampling (HSCS)
• Phase 1: Hyperspherical clustering: identify multiple failure regions
• Iteratively update cluster centroid
• Samples are associated with different weight during clustering
• Cluster centroid are biased to more important samples (with higher weights)
High Sigma Analysis
High Sigma Analysis
Another alternative
• Presampling: sketch the circuit behavior
• Parameter pruning: each parameter is analyzed in terms of how sensitive it is to cause a circuit failure.
ReliefF specifically looks at the sensitivity around the decision boundary
Another alternative
• Classification: relies on support vector machine (SVM) with Guassianradial basis function (RBF) kernel to identify failure regions and to train and classify samples. It is also a classification method to co-recognize the multiple failure regions.
