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University of Florida - ESI - 6323
University of Florida - ESI - 6323
University of Florida - ESI - 6323
University of Florida - ESI - 6323
EEL 6323Advanced VLSI DesignSpring 2010Section: 6963Lecture 0: Introduction Course Outline CMOS Trends and Scaling1Practical Information InstructorRizwan BashirullahOffice: 527 NEB,E-mail: rizwan@ufl.eduTel: (352) 392-0622,Fax: (352) 392-838
University of Florida - ESI - 6323
Homework 1 Find the following for 180nm, 130nm, 90nm, 65nmand 45nm CMOS technologiesDue Wed Jan 20, 2009 Effective channel length Equivalent and physical oxide thickness Supply voltage (Vdd) Draw the layout for the following Latch (use TSMC0.25um
University of Florida - ESI - 6323
Lecture 3: LayoutCMOS EnhancementsScalable rulesPoly orderingDesign PartitioningFloorplanningLayout Min. feature size expressed in terms of = f/2 E.g. = 0.3 m in 0.6 m process Lambda rules are conservative All dimensions rounded to integer multi
University of Florida - ESI - 6323
Lecture 4: DC and Transient AnalysisDC AnalysisSkewed GatesLogic Levels and Noise MarginsTransient ResponseDelay Estimation Reading: Ch. 2Load Line AnalysisFor a given Vin:Region Plot Idsn, Idsp vs. Vout Vout must be where |currents|are equal
University of Florida - ESI - 6323
EEL 6323 Advanced VLSI Design - Spring 2011Instructor: R. BashirullahTA: Qiuzhong Wu (qiuzhongwu@ufl.edu)(Due Friday April 27, 2010)The goal of the project is to study one of the topics specified and design an architecture which consumeslow power, is
University of Florida - ESI - 6323
Lecture 5: Logical Effort Logical Effort (g, h, p) Examples Reading: Ch. 4IntroductionChip designers face a bewildering array of choices What is the best circuit topology for a function? How many stages of logic give least delay? How wide should t
University of Florida - ESI - 6323
Lecture 6: Multistage Logic Networks Multistage Logic Networks Reading: Ch. 4Multistage Logic Networks Path Logical Effort10xg1 =g2 =yg3 =zg4 =h1 =h2 =h3 =h4 =201Multistage Logic Networks Path Electrical Effort10xg1 = 1g2 = 5/3yg
University of Florida - ESI - 6323
Lecture 8: Circuit Simulations Circuit Characterization (Brief) Reading: Ch. 5IV curves: Basic Shapes IDS vs VDS (two regions) Linear (Low VDS) Effective Resistance Saturated (High VDS) Current, gm, gds IDS vs VGS Linear IDS (above threshold) L
University of Florida - ESI - 6323
Lecture 9: Power Dissipation Power and Energy Dynamic and Static Power Leakage Reading: Ch. 4Power Trends Trend in CMOS power dissipation Proportional to chip area and frequency[M. Horowitz, EE246, Stanford Univ]1Power Issues Three reasons why
University of Florida - ESI - 6323
Lecture 11: Power Dissipation Low Power DesignThroughput oriented designClock gatingLeakage reduction techniquesMulti-processing trendsTypes of Processing Fixed-rate Processing (i.e. Signal processing formultimedia or communications) Stream based
University of Florida - ESI - 6323
Phases of Design Flow Phase 1: Design Planning From application requirements to specificationsOverview of Digital IC Design Flow Phase 2: Design Implementation and Verification From SPEC to layout (GDSII) Phase 3: Design Review and Tape-outQiuzhong
University of Florida - ESI - 6323
Synthesizable RTL CodingRTL Coding and Simulation When writing RTL, Always think of Hardware! Think of Synchronous Hardware Synchronousdesign can run smoothly during synthesis, test,simulation, and layout. Think of RTL, writing in RTL coding style,
University of Florida - ESI - 6323
Logic Synthesis Logic Synthesis= Translation+ Optimization+ MappingLogic Synthesis2Gate-Level OptimizationLogic Synthesis Flow34Design Compiler ProcedureLogic Synthesis Input/Output56Describing Design EnvironmentDesign Environment Beware th
University of Florida - ESI - 6323
Lecture 15: Circuit Families Pseudo-nMOS Logic Dynamic, Domino, NP-Domino CVSL, LEAN, CPLDelay What makes a circuit fast?I = C dV/dt -> tpd (C/I) Vlow capacitancehigh currentsmall swing Logical effort is proportional to C/I pMOS are the enemy!
University of Florida - ESI - 6323
Lecture 16: AddersSingle-bit AdditionCarry-Ripple AdderCarry-Skip AdderCarry-Select AdderCarry-Lookahead AdderTree Adder Reading: Chapter 10, W&HSingle-Bit AdditionHalf AdderS =ABCout = ABAB0ABFull AdderAS=Cout =CoutCoutCSSCout S
University of Florida - ESI - 6323
Lecture 17: AddersSingle-bit AdditionCarry-Ripple AdderCarry-Skip AdderCarry-Select AdderCarry-Lookahead AdderTree Adder Reading: Chapter 10, W&HCarry Generation and PropagationDefine 3 new variables that depend only on A and B Generate: Cout =
University of Florida - ESI - 6323
Lecture 18: DatapathsMultipliersShiftersComparatorsCountersLFSRsMultiplication Example:1100 : 12100101 : 510110000001100000000111100 : 6010multiplicandmultiplierpartialproductsproduct M x N-bit multiplication Produce N M-bit partial p
University of Florida - ESI - 6323
Lecture 19: Clock DistributionClock distribution trendsDistribution networksClock PowerClock SkewTiming Definitions Source: Ch 7 J. Rabaey notes, Weste and Harris Notes, S. Russu, ISSCC,Clocking Synchronous systems use a clock to keep operations
University of Florida - ESI - 6323
Lecture 20: Sequential Circuits Sequencing Elements Simple Latch/FF Timing Definitions Source: Ch 7 (W&H)SequencingUse flip-flops to delay fast tokens so they move throughexactly one stage each cycle.Inevitably adds some delay to the slow tokensC
University of Florida - ESI - 6323
Lecture 21: Sequential CircuitsSetup and Hold timeMS FF Power PCPulsed FF HLFF, SDFF, SAFFSource: Ch 7 J. Rabaey notes, Weste and Harris NotesReview: Timing Definitions TCQ: Propagation Delay from Ck to Q, assuming D has been setearly enough relat
University of the East - BUS - 101
Active CellIn a worksheet, the cell with the black outline. Data is always entered into the active cell.Column LetterColumns run vertically on a worksheet and each one is identified by a letter in the columnheader.Formula BarLocated above the worksh
Grand Canyon - MKT - 607
Week 3 DB Due by day 3With respect to the articles assigned and any otherarticles/research that you are able to draw upon, do marketershave an obligation to avoid marketing to vulnerable consumers asdefined by Smith and Cooper-Martin in "Ethics and Ta
Grand Canyon - MKT - 607
Week 3 DB due by day 5Explain the reason for positioning and repositioning products. Choose a product with which youare familiar, preferably one in your industry, and explain how it might berepositioned. Indicateits current position in the market, a de
Grand Canyon - MKT - 607
Week 4 DB Due by day 3As stated in this week's reading, "Whether a company grows,survives, and makes a profit could depend upon how theirproducts or services are defined." What does this statement meanin to a company or to consumer perception?Greetin
Grand Canyon - MKT - 607
Week 4 DB Due by day 5Keller, in "Branding Shortcuts," provides some shortcuts toestablishing a brand. Which of his suggestions resonates withyou and why?Greetings Class,The suggestion that resonates with me is memorability. Thissuggestion resonates
Grand Canyon - MKT - 607
Week 5 DB Due by day 3Define integrated marketing communications (IMC) and discuss theimportance of teamwork in achieving a successful IMC effort.Provide examples of how this concept would apply to a specificorganization. Use the Schultz and Kitchen a
Grand Canyon - MKT - 607
Week 5 DB Due by day 5Identify possible ethical issues involved with the dominance oflarge retailers (e.g., Wal-Mart, Home Depot, etc.). Explain yourposition regarding these issues and propose possible solutionsfor avoiding such issues if possible.Gr
Rutgers - PHARM - 300
! http:/www.pitt.edu/~super1 JIT http:/www.pitt.edu/~super1 : . . . . :
Rutgers - PHARM - 300
Medical Aspects of Blast InjuriesAssistant Professor of Emergency Medicine Mayo Clinic sztajnkrycer.matthew@mayo.eduMatthew D. Sztajnkrycer, MD, PhDAmado Alejandro Bez MD Mscbaez.amado@mayo.eduLearning Objectivess Discuss the epidemiology of blast
Rutgers - PHARM - 300
Disaster and Multi-Casualty TriageAmado Alejandro Bez MD MSc Matthew Sztajnkrycer MD PhDLearning Objectives Describe the key elements of disaster triage Understand the basic principles of Mass Casualty Triage (START)Performance Objectives At the end
Rutgers - PHARM - 300
Kansas 9/14/04 TornadoSpring storm and tornadoes in KansasSatellite image taken Thursday at 11:15 p.m. EDT.
Rutgers - PHARM - 300
TornadoesScott R. Lillibridge, M.D.Centers for Disease Control & PreventionINTRODUCTIONBackground and Nature of the ProblemTornadoes are funnel-shaped wind storms that occur when masses of air with differing physical qualities (e.g., density, tempera
Rutgers - PHARM - 300
TORNADO-RELATED DEATHS AND INJURIES DUE TO THE MAY 3, 1999 TORNADOESSheryll Brown, Pam Archer, Elizabeth Kruger, and Sue MalloneeInjury Prevention Service Oklahoma State Department of HealthPath of F5 Tornado Through MooreOBJECTIVESInjuryepidemiolog
Rutgers - PHARM - 300
Public Health Consequences of Earthquakes. Part II.Eric K. Noji, M.D., M.P.H.Centers for Disease Control and Prevention Washington, D.C.PREVENTION AND CONTROL MEASURESUntil earthquake prevention and control measures are adopted and mitigation actions
Rutgers - PHARM - 300
Access to and Need for Counseling Among Children after the September 11th Attacks on the World Trade CenterGerry Fairbrother, PhDNew York Academy of MedicinePresentation to the 2003 Pediatric Academic Societies Annual Meeting May 3-6, 2003 Seattle, WA
Rutgers - PHARM - 300
Laboratory Criteria for Identification of B. anthracisssFrom clinical samples, such as blood, cerebrospinal fluid (CSF), skin lesion (eschar), or oropharyngeal ulcer Encapsulated gram-positive rods on Gram stain From growth on sheep blood agar: Large g
Rutgers - PHARM - 300
Identification of Bioterrorism AgentsRashid A. Chotani, M.D., MPHAssistant Professor of Medicine & Public Health Director, Global Infectious Disease Surveillance & Alert System Johns Hopkins University President, Pakistan Public Health FoundationGIDSAS
Rutgers - PHARM - 300
Assault with a Chemical Weapon: Its worse out there than just BioterrorismFrank Paloucek DABATBiological warfare in history ? 6th Cent Romans 1346 1800's WWI 1933-45 Feces-smeared arrows Assyrians poison wells with ergot Animal cadavers into well wate
Rutgers - PHARM - 300
Cyber Terrorism Part 2 of 2(When the Hackers Grow Up)05/01/09Hacking as Warfare1CYBER WARFIGHTER Terrorists Terrorist sympathizers Government agents Organized Crime Thrill seekersIncidents normally take the form of organized Asymmetric Attacks.05/0
Rutgers - PHARM - 300
Emergencies in the ClassroomGregg S. Margolis, MS, NREMT-PAssistant Professor, Emergency Medicine Program University of Pittsburgh School of Health and Rehabilitation SciencesToday's goalDevelop strategies to deal with emergencies that are most likely
Rutgers - PHARM - 300
Disaster and Hospital Functions - In Relations with Information Transmission -[Slide1] Ladies and Gentlemen, it is my great pleasure to visit Santa Cruz de la Sierra, one of the most beautiful cities in South America and to share a wonderful time with al
LSE - ECON - 201
EC201Lent TermErik EysterFinding a General Competitive Equilibrium in an ExchangeEconomy.1. In an exchange economy, Agent A has endowment (2, 2) and preferences uA (xA , xA ) = xA1215xA22, while Agent B has endowment (2, 1)and preferences uB
LSE - ECON - 201
EC201Lent 2011Erik EysterSecond Worked Example of General Competitive EquilibriumIn this worked example, we use the example of two wheat farmers tradingwheat now for wheat later to explore interest rates set by a competitivemarket.Two farmers trade
LSE - ECON - 201
MACROECONOMICS TEST 1 (Dr Ashwin MOHEEPUT)GENERAL KNOWLEDGE QUESTIONSQuestion 1Suppose a car manufacturer is choosing between two production options. It can produce 100cars with 200 workers and 50 machines, or it can produce 166 cars with 300 workers
LSE - ECON - 201
EC201Lent TermErik EysterFinding a General Competitive Equilibrium in an ExchangeEconomy.1. In an exchange economy, Agent A has endowment (2, 2) and preferences uA (xA , xA ) = xA1215xA22, while Agent B has endowment (2, 1)and preferences uB
LSE - ECON - 201
EC201Lent 2011Erik EysterSecond Worked Example of General Competitive EquilibriumIn this worked example, we use the example of two wheat farmers tradingwheat now for wheat later to explore interest rates set by a competitivemarket.Two farmers trade
LSE - ECON - 201
Dear EconomistsAs the exams are approaching and we all start digging into past exam papers and old supervisions,Economics Society invites everybody to join our Unofficial Solutions Database.We are going to start accumulating student-made answers on our
LSE - ECON - 201
Dear EconomistsAs the exams are approaching and we all start digging into past exam papers and old supervisions,Economics Society invites everybody to join our Unofficial Solutions Database.We are going to start accumulating student-made answers on our
LSE - ECON - 201
MACROECONOMICS TEST 1 (Dr Ashwin MOHEEPUT)GENERAL KNOWLEDGE QUESTIONSQuestion 1Suppose a car manufacturer is choosing between two production options. It can produce 100cars with 200 workers and 50 machines, or it can produce 166 cars with 300 workers
LSE - ECON - 201
DEMAND FOR INSURANCEA consumer begins with initial wealth w and faces probability p of a loss of L in anaccident. She has concave utility of wealth function u(w) and strictly decreasing marginalutility. Lets call her risky no-insurance endowment X .Th
LSE - ECON - 201
models.CSystematic 2 T O O L S Fis R astlyM P A R A T I and S T A T I C S much less likely to occur. Indeed, suppose34H A P T E R 1 elimination O v C O simpler, V E errors arean economic model reduces to a system of two linear equations in two unknowns
LSE - ECON - 201
Responses to Serial CorrelationIf the disturbances are serially correlated OLS parameter estimates are unbiased OLS parameter estimates are inefficient the OLS standard errors are incorrect (there aremethods which correct for this)There are two poss
LSE - ECON - 201
Regression using time series data stationary I(0) seriesProcedures to be adopted depend on whether timeseries are stationary or nonstationaryHence we need to pretest data using DF and ADFtests Modelling I(0) series - ie all the series are stationary
LSE - ECON - 201
Testing time series for unit rootsWe know that a random walk is a particular type ofAR(1) processwith = 1xt = xt-1 + etHence to test whether xt is a random walk (with zeromean), we could estimatext = xt-1 + etand testH0 : = 1nonstationarityagai
LSE - ECON - 201
Nonstationary stochastic processesStationary processes satisfyE[xt] = Var[xt] = 2 < Cov[xs,xt] = t-sall independent of tMany economic series do not satisfy these conditionsE[GDP1970] > E[GDP1870]Hence they are nonstationary and cannot berepresent
LSE - ECON - 201
Time series - processes andrealisationsWith random sampling the key concepts are populationand sampleThe population can be real (Census) or hypothetical(continuous distribution)Sample statistics are (imprecise) estimates oftheunderlying population
LSE - ECON - 201
Introduction to time series analysisIn many cases (especially in macroeconomics) a sampleconsists of a set of observations measured over timeSuch data cannot be treated as a random sample - infact we need new concept of population and sampleIn time s
LSE - ECON - 201
Variables usedAGEWAGELNWAGEIndividuals ageHourly wage (in $)Log of wageOCC1Categorical variable for occupational category (seebelow)Categorical variable for industrial category (see below)1 if union member, 0 otherwiseIND1UNIONGRADEMARRIED