Title :
Statistical Blockade: A Novel Method for Very Fast Monte Carlo Simulation of Rare Circuit Events, and its Application
Author :
Singhee, Amith ; Rutenbar, Rob A.
Author_Institution :
Dept. of ECE, Carnegie Mellon Univ., Pittsburgh, PA
Abstract :
Circuit reliability under statistical process variation is an area of growing concern. For highly replicated circuits such as SRAMs and flip flops, a rare statistical event for one circuit may induce a not-so-rare system failure. Existing techniques perform poorly when tasked to generate both efficient sampling and sound statistics for these rare events. Statistical blockade is a novel Monte Carlo technique that allows us to efficiently filter - to block - unwanted samples insufficiently rare in the tail distributions we seek. The method synthesizes ideas from data mining and extreme value theory, and shows speed-ups of 10times - 100times over standard Monte Carlo
Keywords :
Monte Carlo methods; SRAM chips; circuit reliability; circuit simulation; data mining; flip-flops; importance sampling; statistical analysis; circuit reliability; data mining; extreme value theory; highly replicated circuits; rare circuit events; statistical blockade; statistical process variation; tail distributions; unwanted samples blocking; very fast Monte Carlo simulation; Circuit simulation; Data mining; Filters; Measurement; Monte Carlo methods; Probability distribution; Random access memory; Statistical distributions; Statistics; Tail;
Conference_Titel :
Design, Automation & Test in Europe Conference & Exhibition, 2007. DATE '07
Conference_Location :
Nice
Print_ISBN :
978-3-9810801-2-4
DOI :
10.1109/DATE.2007.364490