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dc.contributor.authorRana, Manish
dc.contributor.authorCanal Corretger, Ramon
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2015-04-17T17:47:50Z
dc.date.created2014
dc.date.issued2014
dc.identifier.citationRana, M.; Canal, R. REEM: failure/non-failure region estimation method for SRAM yield analysis. A: IEEE International Conference on Computer Design. "2014 32nd IEEE International Conference on Computer Design (ICCD): October 19-22, 2014: Seoul, Korea". Seul: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 36-41.
dc.identifier.isbn978-1-4799-6492-5
dc.identifier.urihttp://hdl.handle.net/2117/27445
dc.description.abstractThe big challenge that we face today for designing resilient memories is the huge number of simulations needed to arrive at a good estimate of memory's yield. A lot of work has come up recently focusing on the reduction of these simulations. The majority of these methods have focused on using different Markov Chain Monte Carlo (MCMC) methods, most notably Importance Sampling. SRAMs, though, have an interesting property of failure monotonicity which implies that given a known failure point in SRAM's parameter space all points with larger variations will also be failure points. Our work REEM (Region Estimation by Exploiting Monotonicity), thus, focuses on exploiting the SRAM's failure monotonicity property for faster estimation of the Failure/Non-Failure regions. The usual MCMC methods can then be used without needing actual spice simulations. Our results show that using our method we can achieve an overall 10x reduction in simulations compared to traditional Importance Sampling methods.
dc.format.extent6 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Sistemes d'informació::Emmagatzematge i recuperació de la informació
dc.subjectÀrees temàtiques de la UPC::Enginyeria electrònica::Microelectrònica::Circuits integrats
dc.subject.lcshMemory management (Computer science)
dc.subject.lcshIntegrated circuits
dc.subject.otherImportance sampling
dc.subject.otherMarkov processes
dc.subject.otherStatic random access storage
dc.subject.other10x reductions
dc.subject.otherEstimation methods
dc.subject.otherImportance sampling method
dc.subject.otherMarkov chain Monte Carlo method
dc.subject.otherMonotonicity property
dc.subject.otherParameter spaces
dc.subject.otherSPICE simulations
dc.subject.otherYield analysis
dc.titleREEM: failure/non-failure region estimation method for SRAM yield analysis
dc.typeConference report
dc.subject.lemacGestió de memòria (Informàtica)
dc.subject.lemacCircuits integrats
dc.contributor.groupUniversitat Politècnica de Catalunya. ARCO - Microarquitectura i Compiladors
dc.identifier.doi10.1109/ICCD.2014.6974659
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6974659
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac15415877
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorRana, M.; Canal, R.
local.citation.contributorIEEE International Conference on Computer Design
local.citation.pubplaceSeul
local.citation.publicationName2014 32nd IEEE International Conference on Computer Design (ICCD): October 19-22, 2014: Seoul, Korea
local.citation.startingPage36
local.citation.endingPage41


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