Fast monte carlo statistical analysis using threshold voltage modeling
A system, method, and computer program product for automatically approximating conventional Monte Carlo statistical device model evaluation for circuit simulation with drastic speed improvements, while preserving significant accuracy. Embodiments enable quick inspection of the effects of process mis...
Gespeichert in:
Hauptverfasser: | , , , |
---|---|
Format: | Patent |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | |
container_volume | |
creator | TIAN MICHAEL DENG ANANG XIE JUSHAN LIU HONGZHOU |
description | A system, method, and computer program product for automatically approximating conventional Monte Carlo statistical device model evaluation for circuit simulation with drastic speed improvements, while preserving significant accuracy. Embodiments enable quick inspection of the effects of process mismatch variations on single devices and even large circuits compared to standard computationally prohibitive Monte Carlo analysis. Statistical device model variation is calculated as if all such variation is due to changes in threshold voltage, even though other physical phenomena are known to contribute. Threshold voltage variation is modeled as a function of statistical variation, device size, and working bias condition. Circuit simulation is faster when the full internal device model parameter set is not rebuilt for every Monte Carlo analysis iteration. Embodiments are compatible with both conventional SPICE and newer Fast SPICE simulations. Circuit designers may capture design sensitivity to manufacture process changes more easily with simplified statistical models. |
format | Patent |
fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US8954908B1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US8954908B1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US8954908B13</originalsourceid><addsrcrecordid>eNqNizEKwkAQRbexEPUOcwFBUSFpFRd7tQ7DZkwWxp2QPwre3hQewOoV7715iJHh9LTiQolHNYKzZ3hOrMSF9YMMeiGXjrwfBb1pS29T506msRWd1DLMHqyQ1Y-LQPF8O13WMlgjGDhJEW_u16o-7OtNddzu_ki-FeE0Eg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Fast monte carlo statistical analysis using threshold voltage modeling</title><source>esp@cenet</source><creator>TIAN MICHAEL ; DENG ANANG ; XIE JUSHAN ; LIU HONGZHOU</creator><creatorcontrib>TIAN MICHAEL ; DENG ANANG ; XIE JUSHAN ; LIU HONGZHOU</creatorcontrib><description>A system, method, and computer program product for automatically approximating conventional Monte Carlo statistical device model evaluation for circuit simulation with drastic speed improvements, while preserving significant accuracy. Embodiments enable quick inspection of the effects of process mismatch variations on single devices and even large circuits compared to standard computationally prohibitive Monte Carlo analysis. Statistical device model variation is calculated as if all such variation is due to changes in threshold voltage, even though other physical phenomena are known to contribute. Threshold voltage variation is modeled as a function of statistical variation, device size, and working bias condition. Circuit simulation is faster when the full internal device model parameter set is not rebuilt for every Monte Carlo analysis iteration. Embodiments are compatible with both conventional SPICE and newer Fast SPICE simulations. Circuit designers may capture design sensitivity to manufacture process changes more easily with simplified statistical models.</description><language>eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2015</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20150210&DB=EPODOC&CC=US&NR=8954908B1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,778,883,25547,76298</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20150210&DB=EPODOC&CC=US&NR=8954908B1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>TIAN MICHAEL</creatorcontrib><creatorcontrib>DENG ANANG</creatorcontrib><creatorcontrib>XIE JUSHAN</creatorcontrib><creatorcontrib>LIU HONGZHOU</creatorcontrib><title>Fast monte carlo statistical analysis using threshold voltage modeling</title><description>A system, method, and computer program product for automatically approximating conventional Monte Carlo statistical device model evaluation for circuit simulation with drastic speed improvements, while preserving significant accuracy. Embodiments enable quick inspection of the effects of process mismatch variations on single devices and even large circuits compared to standard computationally prohibitive Monte Carlo analysis. Statistical device model variation is calculated as if all such variation is due to changes in threshold voltage, even though other physical phenomena are known to contribute. Threshold voltage variation is modeled as a function of statistical variation, device size, and working bias condition. Circuit simulation is faster when the full internal device model parameter set is not rebuilt for every Monte Carlo analysis iteration. Embodiments are compatible with both conventional SPICE and newer Fast SPICE simulations. Circuit designers may capture design sensitivity to manufacture process changes more easily with simplified statistical models.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2015</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNizEKwkAQRbexEPUOcwFBUSFpFRd7tQ7DZkwWxp2QPwre3hQewOoV7715iJHh9LTiQolHNYKzZ3hOrMSF9YMMeiGXjrwfBb1pS29T506msRWd1DLMHqyQ1Y-LQPF8O13WMlgjGDhJEW_u16o-7OtNddzu_ki-FeE0Eg</recordid><startdate>20150210</startdate><enddate>20150210</enddate><creator>TIAN MICHAEL</creator><creator>DENG ANANG</creator><creator>XIE JUSHAN</creator><creator>LIU HONGZHOU</creator><scope>EVB</scope></search><sort><creationdate>20150210</creationdate><title>Fast monte carlo statistical analysis using threshold voltage modeling</title><author>TIAN MICHAEL ; DENG ANANG ; XIE JUSHAN ; LIU HONGZHOU</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US8954908B13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2015</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>TIAN MICHAEL</creatorcontrib><creatorcontrib>DENG ANANG</creatorcontrib><creatorcontrib>XIE JUSHAN</creatorcontrib><creatorcontrib>LIU HONGZHOU</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>TIAN MICHAEL</au><au>DENG ANANG</au><au>XIE JUSHAN</au><au>LIU HONGZHOU</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Fast monte carlo statistical analysis using threshold voltage modeling</title><date>2015-02-10</date><risdate>2015</risdate><abstract>A system, method, and computer program product for automatically approximating conventional Monte Carlo statistical device model evaluation for circuit simulation with drastic speed improvements, while preserving significant accuracy. Embodiments enable quick inspection of the effects of process mismatch variations on single devices and even large circuits compared to standard computationally prohibitive Monte Carlo analysis. Statistical device model variation is calculated as if all such variation is due to changes in threshold voltage, even though other physical phenomena are known to contribute. Threshold voltage variation is modeled as a function of statistical variation, device size, and working bias condition. Circuit simulation is faster when the full internal device model parameter set is not rebuilt for every Monte Carlo analysis iteration. Embodiments are compatible with both conventional SPICE and newer Fast SPICE simulations. Circuit designers may capture design sensitivity to manufacture process changes more easily with simplified statistical models.</abstract><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | |
ispartof | |
issn | |
language | eng |
recordid | cdi_epo_espacenet_US8954908B1 |
source | esp@cenet |
subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Fast monte carlo statistical analysis using threshold voltage modeling |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T12%3A56%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=TIAN%20MICHAEL&rft.date=2015-02-10&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS8954908B1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |