EE260: Digital Design, Spring /16/18. n Example: m 0 (=x 1 x 2 ) is adjacent to m 1 (=x 1 x 2 ) and m 2 (=x 1 x 2 ) but NOT m 3 (=x 1 x 2 )
|
|
- Esmond Atkins
- 5 years ago
- Views:
Transcription
1 EE26: Digital Desig, Sprig 28 3/6/8 EE 26: Itroductio to Digital Desig Combiatioal Datapath Yao Zheg Departmet of Electrical Egieerig Uiversity of Hawaiʻi at Māoa Combiatioal Logic Blocks Multiplexer Ecoders/Decoders Priority Ecoders Three-State Buffers Parity Fuctios Comparators Adders/Subtractors Multipliers/Dividers Shifters Memory/Cache Overview Caoical ad Stadard Forms Karaugh Maps We eed to cosider formal techiques for the simplificatio of Boolea fuctios. Miterms ad Maxterms Sum-of-Miterms ad Product-of-Maxterms Product ad Sum terms Sum-of-Products (SOP) ad Product-of-Sums (POS) Karaugh maps (K-maps) are graphical represetatios of boolea fuctios. Oe map cell correspods to a row i the truth table. Also, oe map cell correspods to a miterm or a maxterm i the boolea expressio Multiple-cell areas of the map correspod to stadard terms. 3 4 x x 2 Two-Variable Map m 2 3 m 2 m m 3 OR x 2 x 2 NOTE: orderig of variables is IMPORTANT for f(x,x2), x is the row, x2 is the colum. Cell represets x x2 ; Cell represets x x2; etc. If a miterm is preset i the fuctio, the a is placed i the correspodig cell. m 3 m m 2 m 3 5 Two-Variable Map (cot.) Ay two adjacet cells i the map differ by ONLY oe variable, which appears complemeted i oe cell ad ucomplemeted i the other. Example: m (=x x 2 ) is adjacet to m (=x x 2 ) ad m 2 (=x x 2 ) but NOT m 3 (=x x 2 ) 6 Chapter 6-8: Combiatioal Datapath
2 EE26: Digital Desig, Sprig 28 3/6/8 Simplificatio Eter miterms of the Boolea fuctio ito the map, the group terms Example: f(a,b,c) = a c + abc + bc Result: f(a,b,c) = a c + b a bc 7 Elimiatig static hazards Key idea: Glitches happe whe a chagig iput spas separate K-map ecirclemets Example: to chage ca cause a static- glitch AB A CD C B D Combiatioal Logic Blocks With K map, you ca build ay combiatioal fuctios you wat, but ot everythig should be build from K map Miimum SOP/POS is ot always globally optimum Some fuctios have special structures to be take advatage of Some fuctios are so frequetly used they have become covetios Major examples Multiplexer Ecoders/decoders Arithmetic: adders, subtractors, multipliers, dividers, etc. Logic: shifters Memory: ROM, RAM Multiplexer Selects biary iformatio from oe of may iput lies ad directs it to a sigle output lie. Also kow as the selector circuit, Selectio is cotrolled by a particular set of iputs lies whose # depeds o the # of the data iput lies. For a 2 -to- multiplexer, there are 2 data iput lies ad selectio lies whose bit combiatio determies which iput is selected. 2-to--Lie Multiplexer Sice 2 = 2, = The sigle selectio variable S has two values: S = selects iput I S = selects iput I The equatio: Y = S I + SI The circuit: S Decoder I I Eablig Circuits Y Implemetig Boolea fuctios with Multiplexers Ay Boolea fuctio of variables ca be implemeted usig a 2 - -to- multiplexer. A MUX is basically a decoder with outputs ORed together, hece this is t surprisig. The SELECT sigals geerate the miterms of the fuctio. The data iputs idetify which miterms are to be combied with a OR. Chapter 6-8: Combiatioal Datapath 2
3 EE26: Digital Desig, Sprig 28 3/6/8 Example F(X,Y,Z) = X Y Z + X YZ + XYZ + XYZ = Σm(,2,6,7) There are =3 iputs, thus we eed a 2 2 -to- MUX The first - (=2) iputs serve as the selectio lies Decoders A combiatioal circuit that coverts biary iformatio from coded iputs to a maximum 2 coded outputs à -to- 2 decoder -to-m decoder, m 2 Examples: BCD-to-7-segmet decoder, where =4 ad m= -2 Decoder Implemetig Boolea fuctios usig decoders Ay combiatioal circuit ca be costructed usig decoders ad OR gates! Why? Here is a example: Implemet a full adder circuit with a decoder ad two OR gates. Recall full adder equatios, ad let X, Y, ad Z be the iputs: S(X,Y,Z) = X+Y+Z = Sm(,2,4,7) C (X,Y,Z) = Sm(3, 5, 6, 7). Sice there are 3 iputs ad a total of 8 miterms, we eed a 3-to-8 decoder. Implemetig a Biary Adder Usig a Decoder S(X,Y,Z) = SUM m(,2,4,7) C(X,Y,Z) = SUM m(3,5,6,7) Ecoders A ecoder is a digital circuit that performs the iverse operatio of a decoder. A ecoder has 2 iput lies ad output lies. The output lies geerate the biary equivalet to the iput lie whose value is. Chapter 6-8: Combiatioal Datapath 3
4 EE26: Digital Desig, Sprig 28 3/6/8 Ecoder Example Example: 8-to-3 biary ecoder (octal-to-biary) A = D + D 3 + D 5 + D 7 A = D 2 + D 3 + D 6 + D 7 A 2 = D 4 + D 5 + D 6 + D 7 Ecoder Desig Issues There are two ambiguities associated with the desig of a simple ecoder:. Oly oe iput ca be active at ay give time. If two iputs are active simultaeously, the output produces a udefied combiatio (for example, if D 3 ad D 6 are simultaeously, the output of the ecoder will be. 2. A output with all 's ca be geerated whe all the iputs are 's,or whe D is equal to. Priority Ecoders Solves the ambiguities metioed above. Multiple asserted iputs are allowed; oe has priority over all others. Separate idicatio of o asserted iputs. Example: 4-to-2 Priority Ecoder Truth Table Example: 4-to-2 Priority Ecoder K-Maps Buffers The umber of circuit iputs that ca be drive by a sigle output is limited If a circuit output must drive may iputs, we use buffers to icrease the drivig capability Buffers does ot perform ay logic fuctio, i.e. its logic equatio is F=C. It oly icreases the drivig capability Chapter 6-8: Combiatioal Datapath 4
5 EE26: Digital Desig, Sprig 28 3/6/8 Three-state buffers Logic values for buses sigals Output = LOW, HIGH, or Hi-Z. lca tie multiple outputs together, if at most oe at a time is drive. Circuit with tri-state buffers S S2 X Z X X X X X X X X X Z X Z Table : Logic values for bus sigals ad the resultig value whe they are coected together Exclusive-OR (XOR) Fuctio XOR (also Å) : the ot-equal fuctio XOR(X,Y) = X Å Y = X Y + XY Idetities: X Å = X X Å = X X Å X = X Å X = Properties: X Å Y = Y Å X (X Å Y) Å W = X Å ( Y Å W) Parity Fuctios Odd Parity Circuit : The output is if odd umber of iputs are Eve Parity Circuit : The output is if eve umber of iputs are Example : 4-bit Parity Circuit I I I2 I3 Daisy-Chai Structure EVEN ODD Iput : Odd Parity output : Eve Parity output : I I I2 I3 Tree structure EVEN ODD 28 Parity-Checkig Applicatio: memory Comparators Compares Two biary words ad idicate if they are equal A B Comparator A=B? Magitude Comparators : A B Comparator A=B A>B A<B 29 3 Chapter 6-8: Combiatioal Datapath 5
6 EE26: Digital Desig, Sprig 28 3/6/8 Equality Comparators Iterative Comparator -bit comparator l4-bit comparator EQ_L 3 32 Performs -bit additio. Iputs: A, B Half Adder Outputs: S, C Idex idicates sigificace, is for LSB ad is for the ext higher sigificat bit. Boolea equatios: S = A B +A B = A Å B C = A B Truth Table A B S C Full Adder Full adder (for higher-order bit additio) Combiatioal circuit that performs the additios of 3 bits (two bits ad a carry-i bit) C i+ B i bit full adder C i S i Full Adder (cot.) -bit Combiatioal Adders The K-maps for C i+ : S i : B i C i B i C i B i C i S i C i+ Perform parallel multi-bit additio Ripple Carry Adder Simple desig Time cosumig. Why? (you ll see i a bit!) Carry Lookahead Adder More complex tha ripple-carry adder Reduces circuit delay Chapter 6-8: Combiatioal Datapath 6
7 EE26: Digital Desig, Sprig 28 3/6/8 -bit Ripple Carry Adder Costructed usig -bit full adder blocks i parallel. Cascade the full adders so that the carry out from oe becomes the carry i to the ext higher bit positio. Carry Lookahead Adder From a FA, separate betwee carry geeratio (a ew carry sigal is geerated, i.e. C out =) ad carry propagatio (a existig C i is propagated to C out ) Geerate: G i = B i : if, C i+ = Propagate: P i = Å B i : if true, C i+ = C i Full Adder (FA) Partial Full Adder (PFA) B i B i S i C i+ C i S i G i P i Ci 4-bit Biary Adder/Subtractor Multiplicatio XOR gates act as programmable iverters Flashback to 3 rd grade Multiplier Multiplicad Partial products Fial sum Base : 8 x 9 = 72 PP: = 72 How wide is the result? log( x m) = log() + log(m) 32b x 32b = 64b result x Array Multiplier x Addig all partial products simultaeously usig a array of basic cells S i C i B j Full Adder C out S out,b j Multiplier Multiplicad 32 bits 32-bit ALU Shift right Product Write 64 bits x Cotrol test Chapter 6-8: Combiatioal Datapath 7
8 EE26: Digital Desig, Sprig 28 3/6/8 Booth s Ecodig Search for a ru of bits i the multiplier E.g. has a ru of 2 bits i the middle Multiplyig by (6 i decimal) is equivalet to multiplyig by 8 ad subtractig twice, sice 6 x m = (8 2) x m = 8m 2m Hece, iterate right to left ad: Subtract multiplicad from product at first Add multiplicad to product after last Do t do either for bits i the middle Iteger Divisio Agai, back to 3 rd grade (74 8 = 9 rem 2) Quotiet Divisor Divided - - Remaider 32-bit ALU Divisor 32 bits Divider Shift right Remaider Shift left Write 64 bits Cotrol test Logical Operatios Bitwise AND, OR, XOR, NOR Implemet w/ 32 gates i parallel Shifts ad rotates rol => rotate left (MSB->LSB) ror => rotate right (LSB->MSB) sll -> shift left logical (->LSB) srl -> shift right logical (->LSB) sra -> shift right arithmetic (old MSB->ew MSB) Memory: ROM Memory: RAM Iput: a -bit address Output: data of width w stored at locatio ROM[addr] (2^ such locatios) Sice it is read-oly, the ROM s cotets have to be iitialized by a offlie process If you just read the memory, memory is combiatioal The same address always returs the same aswer It is equivalet to a -iput combiatioal fuctio, each address is a miterim Chapter 6-8: Combiatioal Datapath 8
9 EE26: Digital Desig, Sprig 28 3/6/8 4 9 Processor Memory Hierarchy Small Fast Memory (RF, SRAM) Big Slow Memory (DRAM) Capacity: Register << SRAM << DRAM Latecy: Register << SRAM << DRAM Badwidth: o-chip >> off-chip O a data access: if data is i fast memory -> low-latecy access to SRAM if data is ot i fast memory -> log-latecy access to DRAM Memory hierarchies oly work if the small, fast memory actually stores data that is reused by the processor Combiatioal Datapath All digital systems comprise Iput ad output Combiatioal stuff that computes a fuctio (has o memory) Sequetial stuff that remembers (upcomig) Chapter 6-8: Combiatioal Datapath 9
Behavioral Modeling in Verilog
Behavioral Modelig i Verilog COE 202 Digital Logic Desig Dr. Muhamed Mudawar Kig Fahd Uiversity of Petroleum ad Mierals Presetatio Outlie Itroductio to Dataflow ad Behavioral Modelig Verilog Operators
More informationCSC 220: Computer Organization Unit 11 Basic Computer Organization and Design
College of Computer ad Iformatio Scieces Departmet of Computer Sciece CSC 220: Computer Orgaizatio Uit 11 Basic Computer Orgaizatio ad Desig 1 For the rest of the semester, we ll focus o computer architecture:
More informationChapter 4 The Datapath
The Ageda Chapter 4 The Datapath Based o slides McGraw-Hill Additioal material 24/25/26 Lewis/Marti Additioal material 28 Roth Additioal material 2 Taylor Additioal material 2 Farmer Tae the elemets that
More informationReversible Realization of Quaternary Decoder, Multiplexer, and Demultiplexer Circuits
Egieerig Letters, :, EL Reversible Realizatio of Quaterary Decoder, Multiplexer, ad Demultiplexer Circuits Mozammel H.. Kha, Member, ENG bstract quaterary reversible circuit is more compact tha the correspodig
More informationChapter 3. Floating Point Arithmetic
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter 3 Floatig Poit Arithmetic Review - Multiplicatio 0 1 1 0 = 6 multiplicad 32-bit ALU shift product right multiplier add
More informationImprovement of the Orthogonal Code Convolution Capabilities Using FPGA Implementation
Improvemet of the Orthogoal Code Covolutio Capabilities Usig FPGA Implemetatio Naima Kaabouch, Member, IEEE, Apara Dhirde, Member, IEEE, Saleh Faruque, Member, IEEE Departmet of Electrical Egieerig, Uiversity
More informationElementary Educational Computer
Chapter 5 Elemetary Educatioal Computer. Geeral structure of the Elemetary Educatioal Computer (EEC) The EEC coforms to the 5 uits structure defied by vo Neuma's model (.) All uits are preseted i a simplified
More informationEE 459/500 HDL Based Digital Design with Programmable Logic. Lecture 13 Control and Sequencing: Hardwired and Microprogrammed Control
EE 459/500 HDL Based Digital Desig with Programmable Logic Lecture 13 Cotrol ad Sequecig: Hardwired ad Microprogrammed Cotrol Refereces: Chapter s 4,5 from textbook Chapter 7 of M.M. Mao ad C.R. Kime,
More informationLecture 1: Introduction and Strassen s Algorithm
5-750: Graduate Algorithms Jauary 7, 08 Lecture : Itroductio ad Strasse s Algorithm Lecturer: Gary Miller Scribe: Robert Parker Itroductio Machie models I this class, we will primarily use the Radom Access
More informationAppendix D. Controller Implementation
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Appedix D Cotroller Implemetatio Cotroller Implemetatios Combiatioal logic (sigle-cycle); Fiite state machie (multi-cycle, pipelied);
More informationLecture 2. RTL Design Methodology. Transition from Pseudocode & Interface to a Corresponding Block Diagram
Lecture 2 RTL Desig Methodology Trasitio from Pseudocode & Iterface to a Correspodig Block Diagram Structure of a Typical Digital Data Iputs Datapath (Executio Uit) Data Outputs System Cotrol Sigals Status
More informationIntroduction CHAPTER Computers
Iside a Computer CHAPTER Itroductio. Computers A computer is a electroic device that accepts iput, stores data, processes data accordig to a set of istructios (called program), ad produces output i desired
More informationEE123 Digital Signal Processing
Last Time EE Digital Sigal Processig Lecture 7 Block Covolutio, Overlap ad Add, FFT Discrete Fourier Trasform Properties of the Liear covolutio through circular Today Liear covolutio with Overlap ad add
More informationPolynomial Functions and Models. Learning Objectives. Polynomials. P (x) = a n x n + a n 1 x n a 1 x + a 0, a n 0
Polyomial Fuctios ad Models 1 Learig Objectives 1. Idetify polyomial fuctios ad their degree 2. Graph polyomial fuctios usig trasformatios 3. Idetify the real zeros of a polyomial fuctio ad their multiplicity
More information1. SWITCHING FUNDAMENTALS
. SWITCING FUNDMENTLS Switchig is the provisio of a o-demad coectio betwee two ed poits. Two distict switchig techiques are employed i commuicatio etwors-- circuit switchig ad pacet switchig. Circuit switchig
More informationCode No: R Set No. 1
Code No: R059210504 Set No. 1 II B.Tech I Semester Regular Examinations, November 2006 DIGITAL LOGIC DESIGN ( Common to Computer Science & Engineering, Information Technology and Computer Science & Systems
More informationDigital System Design
July, 22 9:55 vra235_ch Sheet umber Page umber 65 black chapter Digital System Desig a b c d e f g h 8 7 6 5 4 3 2. Bd3 g6+, Ke8 d8 65 July, 22 9:55 vra235_ch Sheet umber 2 Page umber 66 black 66 CHAPTER
More informationFast Fourier Transform (FFT) Algorithms
Fast Fourier Trasform FFT Algorithms Relatio to the z-trasform elsewhere, ozero, z x z X x [ ] 2 ~ elsewhere,, ~ e j x X x x π j e z z X X π 2 ~ The DFS X represets evely spaced samples of the z- trasform
More informationComputer Systems - HS
What have we leared so far? Computer Systems High Level ENGG1203 2d Semester, 2017-18 Applicatios Sigals Systems & Cotrol Systems Computer & Embedded Systems Digital Logic Combiatioal Logic Sequetial Logic
More informationBOOLEAN MATHEMATICS: GENERAL THEORY
CHAPTER 3 BOOLEAN MATHEMATICS: GENERAL THEORY 3.1 ISOMORPHIC PROPERTIES The ame Boolea Arithmetic was chose because it was discovered that literal Boolea Algebra could have a isomorphic umerical aspect.
More informationCSC165H1 Worksheet: Tutorial 8 Algorithm analysis (SOLUTIONS)
CSC165H1, Witer 018 Learig Objectives By the ed of this worksheet, you will: Aalyse the ruig time of fuctios cotaiig ested loops. 1. Nested loop variatios. Each of the followig fuctios takes as iput a
More informationPython Programming: An Introduction to Computer Science
Pytho Programmig: A Itroductio to Computer Sciece Chapter 1 Computers ad Programs 1 Objectives To uderstad the respective roles of hardware ad software i a computig system. To lear what computer scietists
More informationEnd Semester Examination CSE, III Yr. (I Sem), 30002: Computer Organization
Ed Semester Examiatio 2013-14 CSE, III Yr. (I Sem), 30002: Computer Orgaizatio Istructios: GROUP -A 1. Write the questio paper group (A, B, C, D), o frot page top of aswer book, as per what is metioed
More informationChapter 9. Pointers and Dynamic Arrays. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 9 Poiters ad Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 9.1 Poiters 9.2 Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Slide 9-3
More informationEE University of Minnesota. Midterm Exam #1. Prof. Matthew O'Keefe TA: Eric Seppanen. Department of Electrical and Computer Engineering
EE 4363 1 Uiversity of Miesota Midterm Exam #1 Prof. Matthew O'Keefe TA: Eric Seppae Departmet of Electrical ad Computer Egieerig Uiversity of Miesota Twi Cities Campus EE 4363 Itroductio to Microprocessors
More informationComputers and Scientific Thinking
Computers ad Scietific Thikig David Reed, Creighto Uiversity Chapter 15 JavaScript Strigs 1 Strigs as Objects so far, your iteractive Web pages have maipulated strigs i simple ways use text box to iput
More informationCreating Exact Bezier Representations of CST Shapes. David D. Marshall. California Polytechnic State University, San Luis Obispo, CA , USA
Creatig Exact Bezier Represetatios of CST Shapes David D. Marshall Califoria Polytechic State Uiversity, Sa Luis Obispo, CA 93407-035, USA The paper presets a method of expressig CST shapes pioeered by
More informationCIS 121 Data Structures and Algorithms with Java Spring Stacks, Queues, and Heaps Monday, February 18 / Tuesday, February 19
CIS Data Structures ad Algorithms with Java Sprig 09 Stacks, Queues, ad Heaps Moday, February 8 / Tuesday, February 9 Stacks ad Queues Recall the stack ad queue ADTs (abstract data types from lecture.
More informationAlpha Individual Solutions MAΘ National Convention 2013
Alpha Idividual Solutios MAΘ Natioal Covetio 0 Aswers:. D. A. C 4. D 5. C 6. B 7. A 8. C 9. D 0. B. B. A. D 4. C 5. A 6. C 7. B 8. A 9. A 0. C. E. B. D 4. C 5. A 6. D 7. B 8. C 9. D 0. B TB. 570 TB. 5
More informationLecture 5. Counting Sort / Radix Sort
Lecture 5. Coutig Sort / Radix Sort T. H. Corme, C. E. Leiserso ad R. L. Rivest Itroductio to Algorithms, 3rd Editio, MIT Press, 2009 Sugkyukwa Uiversity Hyuseug Choo choo@skku.edu Copyright 2000-2018
More informationEE260: Logic Design, Spring n Integer multiplication. n Booth s algorithm. n Integer division. n Restoring, non-restoring
EE 260: Introduction to Digital Design Arithmetic II Yao Zheng Department of Electrical Engineering University of Hawaiʻi at Mānoa Overview n Integer multiplication n Booth s algorithm n Integer division
More informationLesson 1. The datapath
Lesso. Computers Structure ad Orgaizatio Graduate i Computer Scieces / Graduate i Computers Egieerig Computers Structure ad Orgaizatio. Graduate i Computer Scieces / Graduate i Computer Egieerig Automatic
More informationModule Instantiation. Finite State Machines. Two Types of FSMs. Finite State Machines. Given submodule mux32two: Instantiation of mux32two
Give submodule mux32two: 2-to- MUX module mux32two (iput [3:] i,i, iput sel, output [3:] out); Module Istatiatio Fiite Machies esig methodology for sequetial logic -- idetify distict s -- create trasitio
More informationChapter 3 Classification of FFT Processor Algorithms
Chapter Classificatio of FFT Processor Algorithms The computatioal complexity of the Discrete Fourier trasform (DFT) is very high. It requires () 2 complex multiplicatios ad () complex additios [5]. As
More informationCopyright 2016 Ramez Elmasri and Shamkant B. Navathe
Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe CHAPTER 19 Query Optimizatio Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe Itroductio Query optimizatio Coducted by a query optimizer i a DBMS Goal:
More informationCMSC Computer Architecture Lecture 10: Caches. Prof. Yanjing Li University of Chicago
CMSC 22200 Computer Architecture Lecture 10: Caches Prof. Yajig Li Uiversity of Chicago Midterm Recap Overview ad fudametal cocepts ISA Uarch Datapath, cotrol Sigle cycle, multi cycle Pipeliig Basic idea,
More informationImproving Template Based Spike Detection
Improvig Template Based Spike Detectio Kirk Smith, Member - IEEE Portlad State Uiversity petra@ee.pdx.edu Abstract Template matchig algorithms like SSE, Covolutio ad Maximum Likelihood are well kow for
More informationUNIVERSITY OF MORATUWA
UNIVERSITY OF MORATUWA FACULTY OF ENGINEERING DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING B.Sc. Egieerig 2014 Itake Semester 2 Examiatio CS2052 COMPUTER ARCHITECTURE Time allowed: 2 Hours Jauary 2016
More informationWavelet Transform. CSE 490 G Introduction to Data Compression Winter Wavelet Transformed Barbara (Enhanced) Wavelet Transformed Barbara (Actual)
Wavelet Trasform CSE 49 G Itroductio to Data Compressio Witer 6 Wavelet Trasform Codig PACW Wavelet Trasform A family of atios that filters the data ito low resolutio data plus detail data high pass filter
More information9 x and g(x) = 4. x. Find (x) 3.6. I. Combining Functions. A. From Equations. Example: Let f(x) = and its domain. Example: Let f(x) = and g(x) = x x 4
1 3.6 I. Combiig Fuctios A. From Equatios Example: Let f(x) = 9 x ad g(x) = 4 f x. Fid (x) g ad its domai. 4 Example: Let f(x) = ad g(x) = x x 4. Fid (f-g)(x) B. From Graphs: Graphical Additio. Example:
More informationCOMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 4. The Processor. Part A Datapath Design
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter The Processor Part A path Desig Itroductio CPU performace factors Istructio cout Determied by ISA ad compiler. CPI ad
More informationLecture 3. RTL Design Methodology. Transition from Pseudocode & Interface to a Corresponding Block Diagram
Lecture 3 RTL Desig Methodology Trasitio from Pseudocode & Iterface to a Correspodig Block Diagram Structure of a Typical Digital Data Iputs Datapath (Executio Uit) Data Outputs System Cotrol Sigals Status
More informationComputer Architecture. Microcomputer Architecture and Interfacing Colorado School of Mines Professor William Hoff
Computer rchitecture Microcomputer rchitecture ad Iterfacig Colorado School of Mies Professor William Hoff Computer Hardware Orgaizatio Processor Performs all computatios; coordiates data trasfer Iput
More informationModule 8-7: Pascal s Triangle and the Binomial Theorem
Module 8-7: Pascal s Triagle ad the Biomial Theorem Gregory V. Bard April 5, 017 A Note about Notatio Just to recall, all of the followig mea the same thig: ( 7 7C 4 C4 7 7C4 5 4 ad they are (all proouced
More informationtop() Applications of Stacks
CS22 Algorithms ad Data Structures MW :00 am - 2: pm, MSEC 0 Istructor: Xiao Qi Lecture 6: Stacks ad Queues Aoucemets Quiz results Homework 2 is available Due o September 29 th, 2004 www.cs.mt.edu~xqicoursescs22
More informationENGI 4421 Probability and Statistics Faculty of Engineering and Applied Science Problem Set 1 Descriptive Statistics
ENGI 44 Probability ad Statistics Faculty of Egieerig ad Applied Sciece Problem Set Descriptive Statistics. If, i the set of values {,, 3, 4, 5, 6, 7 } a error causes the value 5 to be replaced by 50,
More informationPseudocode ( 1.1) Analysis of Algorithms. Primitive Operations. Pseudocode Details. Running Time ( 1.1) Estimating performance
Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Pseudocode ( 1.1) High-level descriptio of a algorithm More structured
More informationThe Magma Database file formats
The Magma Database file formats Adrew Gaylard, Bret Pikey, ad Mart-Mari Breedt Johaesburg, South Africa 15th May 2006 1 Summary Magma is a ope-source object database created by Chris Muller, of Kasas City,
More informationCMSC Computer Architecture Lecture 3: ISA and Introduction to Microarchitecture. Prof. Yanjing Li University of Chicago
CMSC 22200 Computer Architecture Lecture 3: ISA ad Itroductio to Microarchitecture Prof. Yajig Li Uiversity of Chicago Lecture Outlie ISA uarch (hardware implemetatio of a ISA) Logic desig basics Sigle-cycle
More informationCustom single-purpose processors: Hardware. 4.1 Introduction. 4.2 Combinational logic design 4-1
Chapter 4: Custom sigle-purpose processors: Hardware 4- Chapter 4 Custom sigle-purpose processors: Hardware 4. Itroductio As metioed i the previous chapter, a sigle-purpose processor is a digital sstem
More informationLecturers: Sanjam Garg and Prasad Raghavendra Feb 21, Midterm 1 Solutions
U.C. Berkeley CS170 : Algorithms Midterm 1 Solutios Lecturers: Sajam Garg ad Prasad Raghavedra Feb 1, 017 Midterm 1 Solutios 1. (4 poits) For the directed graph below, fid all the strogly coected compoets
More informationK-NET bus. When several turrets are connected to the K-Bus, the structure of the system is as showns
K-NET bus The K-Net bus is based o the SPI bus but it allows to addressig may differet turrets like the I 2 C bus. The K-Net is 6 a wires bus (4 for SPI wires ad 2 additioal wires for request ad ackowledge
More informationCode No: R Set No. 1
Code No: R059210504 Set No. 1 II B.Tech I Semester Supplementary Examinations, February 2007 DIGITAL LOGIC DESIGN ( Common to Computer Science & Engineering, Information Technology and Computer Science
More informationSolutions to Final COMS W4115 Programming Languages and Translators Monday, May 4, :10-5:25pm, 309 Havemeyer
Departmet of Computer ciece Columbia Uiversity olutios to Fial COM W45 Programmig Laguages ad Traslators Moday, May 4, 2009 4:0-5:25pm, 309 Havemeyer Closed book, o aids. Do questios 5. Each questio is
More informationBezier curves. Figure 2 shows cubic Bezier curves for various control points. In a Bezier curve, only
Edited: Yeh-Liag Hsu (998--; recommeded: Yeh-Liag Hsu (--9; last updated: Yeh-Liag Hsu (9--7. Note: This is the course material for ME55 Geometric modelig ad computer graphics, Yua Ze Uiversity. art of
More informationEVALUATION OF TRIGONOMETRIC FUNCTIONS
EVALUATION OF TRIGONOMETRIC FUNCTIONS Whe first exposed to trigoometric fuctios i high school studets are expected to memorize the values of the trigoometric fuctios of sie cosie taget for the special
More informationAbstract. Chapter 4 Computation. Overview 8/13/18. Bjarne Stroustrup Note:
Chapter 4 Computatio Bjare Stroustrup www.stroustrup.com/programmig Abstract Today, I ll preset the basics of computatio. I particular, we ll discuss expressios, how to iterate over a series of values
More informationAPPLICATION NOTE PACE1750AE BUILT-IN FUNCTIONS
APPLICATION NOTE PACE175AE BUILT-IN UNCTIONS About This Note This applicatio brief is iteded to explai ad demostrate the use of the special fuctios that are built ito the PACE175AE processor. These powerful
More informationCode No: R Set No. 1
Code No: R059210504 Set No. 1 II B.Tech I Semester Regular Examinations, November 2007 DIGITAL LOGIC DESIGN ( Common to Computer Science & Engineering, Information Technology and Computer Science & Systems
More informationCombinational Circuits
Combinational Circuits Combinational circuit consists of an interconnection of logic gates They react to their inputs and produce their outputs by transforming binary information n input binary variables
More informationDescriptive Statistics Summary Lists
Chapter 209 Descriptive Statistics Summary Lists Itroductio This procedure is used to summarize cotiuous data. Large volumes of such data may be easily summarized i statistical lists of meas, couts, stadard
More informationBACHMANN-LANDAU NOTATIONS. Lecturer: Dr. Jomar F. Rabajante IMSP, UPLB MATH 174: Numerical Analysis I 1 st Sem AY
BACHMANN-LANDAU NOTATIONS Lecturer: Dr. Jomar F. Rabajate IMSP, UPLB MATH 174: Numerical Aalysis I 1 st Sem AY 018-019 RANKING OF FUNCTIONS Name Big-Oh Eamples Costat O(1 10 Logarithmic O(log log, log(
More informationMath 3201 Notes Chapter 4: Rational Expressions & Equations
Learig Goals: See p. tet.. Equivalet Ratioal Epressios ( classes) Read Goal p. 6 tet. Math 0 Notes Chapter : Ratioal Epressios & Equatios. Defie ad give a eample of a ratioal epressio. p. 6. Defie o-permissible
More informationAutomatic Generation of Polynomial-Basis Multipliers in GF (2 n ) using Recursive VHDL
Automatic Geeratio of Polyomial-Basis Multipliers i GF (2 ) usig Recursive VHDL J. Nelso, G. Lai, A. Teca Abstract Multiplicatio i GF (2 ) is very commoly used i the fields of cryptography ad error correctig
More informationArithmetic Logic Unit. Digital Computer Design
Arithmetic Logic Unit Digital Computer Design Arithmetic Circuits Arithmetic circuits are the central building blocks of computers. Computers and digital logic perform many arithmetic functions: addition,
More information6.1 Combinational Circuits. George Boole ( ) Claude Shannon ( )
6. Combinational Circuits George Boole (85 864) Claude Shannon (96 2) Signals and Wires Digital signals Binary (or logical ) values: or, on or off, high or low voltage Wires. Propagate digital signals
More informationSIDDHARTH GROUP OF INSTITUTIONS :: PUTTUR Siddharth Nagar, Narayanavanam Road QUESTION BANK (DESCRIPTIVE)
SIDDHARTH GROUP OF INSTITUTIONS :: PUTTUR Siddharth Nagar, Narayanavanam Road 517583 QUESTION BANK (DESCRIPTIVE) Subject with Code : STLD(16EC402) Year & Sem: II-B.Tech & I-Sem Course & Branch: B.Tech
More informationOnes Assignment Method for Solving Traveling Salesman Problem
Joural of mathematics ad computer sciece 0 (0), 58-65 Oes Assigmet Method for Solvig Travelig Salesma Problem Hadi Basirzadeh Departmet of Mathematics, Shahid Chamra Uiversity, Ahvaz, Ira Article history:
More informationLecture Topics. Announcements. Today: Integer Arithmetic (P&H ) Next: continued. Consulting hours. Introduction to Sim. Milestone #1 (due 1/26)
Lecture Topics Today: Integer Arithmetic (P&H 3.1-3.4) Next: continued 1 Announcements Consulting hours Introduction to Sim Milestone #1 (due 1/26) 2 1 Overview: Integer Operations Internal representation
More information1. Mark the correct statement(s)
1. Mark the correct statement(s) 1.1 A theorem in Boolean algebra: a) Can easily be proved by e.g. logic induction b) Is a logical statement that is assumed to be true, c) Can be contradicted by another
More informationThe Closest Line to a Data Set in the Plane. David Gurney Southeastern Louisiana University Hammond, Louisiana
The Closest Lie to a Data Set i the Plae David Gurey Southeaster Louisiaa Uiversity Hammod, Louisiaa ABSTRACT This paper looks at three differet measures of distace betwee a lie ad a data set i the plae:
More information9.1. Sequences and Series. Sequences. What you should learn. Why you should learn it. Definition of Sequence
_9.qxd // : AM Page Chapter 9 Sequeces, Series, ad Probability 9. Sequeces ad Series What you should lear Use sequece otatio to write the terms of sequeces. Use factorial otatio. Use summatio otatio to
More informationMapReduce and Hadoop. Debapriyo Majumdar Data Mining Fall 2014 Indian Statistical Institute Kolkata. November 10, 2014
MapReduce ad Hadoop Debapriyo Majumdar Data Miig Fall 2014 Idia Statistical Istitute Kolkata November 10, 2014 Let s keep the itro short Moder data miig: process immese amout of data quickly Exploit parallelism
More informationCopyright 2016 Ramez Elmasri and Shamkant B. Navathe
Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe CHAPTER 22 Database Recovery Techiques Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe Itroductio Recovery algorithms Recovery cocepts Write-ahead
More informationLoad balanced Parallel Prime Number Generator with Sieve of Eratosthenes on Cluster Computers *
Load balaced Parallel Prime umber Geerator with Sieve of Eratosthees o luster omputers * Soowook Hwag*, Kyusik hug**, ad Dogseug Kim* *Departmet of Electrical Egieerig Korea Uiversity Seoul, -, Rep. of
More informationEND-TERM EXAMINATION
(Please Write your Exam Roll No. immediately) END-TERM EXAMINATION DECEMBER 2006 Exam. Roll No... Exam Series code: 100919DEC06200963 Paper Code: MCA-103 Subject: Digital Electronics Time: 3 Hours Maximum
More informationRunning Time. Analysis of Algorithms. Experimental Studies. Limitations of Experiments
Ruig Time Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Most algorithms trasform iput objects ito output objects. The
More informationParabolic Path to a Best Best-Fit Line:
Studet Activity : Fidig the Least Squares Regressio Lie By Explorig the Relatioship betwee Slope ad Residuals Objective: How does oe determie a best best-fit lie for a set of data? Eyeballig it may be
More informationBasic allocator mechanisms The course that gives CMU its Zip! Memory Management II: Dynamic Storage Allocation Mar 6, 2000.
5-23 The course that gives CM its Zip Memory Maagemet II: Dyamic Storage Allocatio Mar 6, 2000 Topics Segregated lists Buddy system Garbage collectio Mark ad Sweep Copyig eferece coutig Basic allocator
More informationMath Section 2.2 Polynomial Functions
Math 1330 - Sectio. Polyomial Fuctios Our objectives i workig with polyomial fuctios will be, first, to gather iformatio about the graph of the fuctio ad, secod, to use that iformatio to geerate a reasoably
More informationRunning Time ( 3.1) Analysis of Algorithms. Experimental Studies. Limitations of Experiments
Ruig Time ( 3.1) Aalysis of Algorithms Iput Algorithm Output A algorithm is a step- by- step procedure for solvig a problem i a fiite amout of time. Most algorithms trasform iput objects ito output objects.
More informationAnalysis of Algorithms
Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Ruig Time Most algorithms trasform iput objects ito output objects. The
More information. Written in factored form it is easy to see that the roots are 2, 2, i,
CMPS A Itroductio to Programmig Programmig Assigmet 4 I this assigmet you will write a java program that determies the real roots of a polyomial that lie withi a specified rage. Recall that the roots (or
More informationCS Polygon Scan Conversion. Slide 1
CS 112 - Polygo Sca Coversio Slide 1 Polygo Classificatio Covex All iterior agles are less tha 180 degrees Cocave Iterior agles ca be greater tha 180 degrees Degeerate polygos If all vertices are colliear
More informationPython Programming: An Introduction to Computer Science
Pytho Programmig: A Itroductio to Computer Sciece Chapter 6 Defiig Fuctios Pytho Programmig, 2/e 1 Objectives To uderstad why programmers divide programs up ito sets of cooperatig fuctios. To be able to
More informationUniversity of Waterloo Department of Electrical and Computer Engineering ECE 250 Algorithms and Data Structures
Uiversity of Waterloo Departmet of Electrical ad Computer Egieerig ECE 250 Algorithms ad Data Structures Midterm Examiatio ( pages) Istructor: Douglas Harder February 7, 2004 7:30-9:00 Name (last, first)
More informationExamples and Applications of Binary Search
Toy Gog ITEE Uiersity of Queeslad I the secod lecture last week we studied the biary search algorithm that soles the problem of determiig if a particular alue appears i a sorted list of iteger or ot. We
More informationUNIT- V COMBINATIONAL LOGIC DESIGN
UNIT- V COMBINATIONAL LOGIC DESIGN NOTE: This is UNIT-V in JNTUK and UNIT-III and HALF PART OF UNIT-IV in JNTUA SYLLABUS (JNTUK)UNIT-V: Combinational Logic Design: Adders & Subtractors, Ripple Adder, Look
More informationMath 10C Long Range Plans
Math 10C Log Rage Plas Uits: Evaluatio: Homework, projects ad assigmets 10% Uit Tests. 70% Fial Examiatio.. 20% Ay Uit Test may be rewritte for a higher mark. If the retest mark is higher, that mark will
More information3D Model Retrieval Method Based on Sample Prediction
20 Iteratioal Coferece o Computer Commuicatio ad Maagemet Proc.of CSIT vol.5 (20) (20) IACSIT Press, Sigapore 3D Model Retrieval Method Based o Sample Predictio Qigche Zhag, Ya Tag* School of Computer
More informationA Very Simple Approach for 3-D to 2-D Mapping
A Very Simple Approach for -D to -D appig Sadipa Dey (1 Ajith Abraham ( Sugata Sayal ( Sadipa Dey (1 Ashi Software Private Limited INFINITY Tower II 10 th Floor Plot No. - 4. Block GP Salt Lake Electroics
More informationChapter 11. Friends, Overloaded Operators, and Arrays in Classes. Copyright 2014 Pearson Addison-Wesley. All rights reserved.
Chapter 11 Frieds, Overloaded Operators, ad Arrays i Classes Copyright 2014 Pearso Addiso-Wesley. All rights reserved. Overview 11.1 Fried Fuctios 11.2 Overloadig Operators 11.3 Arrays ad Classes 11.4
More informationChapter 4. Procedural Abstraction and Functions That Return a Value. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 4 Procedural Abstractio ad Fuctios That Retur a Value Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 4.1 Top-Dow Desig 4.2 Predefied Fuctios 4.3 Programmer-Defied Fuctios 4.4
More informationData Structures and Algorithms. Analysis of Algorithms
Data Structures ad Algorithms Aalysis of Algorithms Outlie Ruig time Pseudo-code Big-oh otatio Big-theta otatio Big-omega otatio Asymptotic algorithm aalysis Aalysis of Algorithms Iput Algorithm Output
More informationChapter 5: Processor Design Advanced Topics. Microprogramming: Basic Idea
5-1 Chapter 5 Processor Desig Advaced Topics Chapter 5: Processor Desig Advaced Topics Topics 5.3 Microprogrammig Cotrol store ad microbrachig Horizotal ad vertical microprogrammig 5- Chapter 5 Processor
More informationLower Bounds for Sorting
Liear Sortig Topics Covered: Lower Bouds for Sortig Coutig Sort Radix Sort Bucket Sort Lower Bouds for Sortig Compariso vs. o-compariso sortig Decisio tree model Worst case lower boud Compariso Sortig
More informationSorting in Linear Time. Data Structures and Algorithms Andrei Bulatov
Sortig i Liear Time Data Structures ad Algorithms Adrei Bulatov Algorithms Sortig i Liear Time 7-2 Compariso Sorts The oly test that all the algorithms we have cosidered so far is compariso The oly iformatio
More informationChapter 5. Functions for All Subtasks. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 5 Fuctios for All Subtasks Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 5.1 void Fuctios 5.2 Call-By-Referece Parameters 5.3 Usig Procedural Abstractio 5.4 Testig ad Debuggig
More informationMorgan Kaufmann Publishers 26 February, COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 5
Morga Kaufma Publishers 26 February, 28 COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter 5 Set-Associative Cache Architecture Performace Summary Whe CPU performace icreases:
More informationcondition w i B i S maximum u i
ecture 10 Dyamic Programmig 10.1 Kapsack Problem November 1, 2004 ecturer: Kamal Jai Notes: Tobias Holgers We are give a set of items U = {a 1, a 2,..., a }. Each item has a weight w i Z + ad a utility
More information