POWER-OF-2 BOUNDARIES

Size: px
Start display at page:

Download "POWER-OF-2 BOUNDARIES"

Transcription

1 Warren.3.fm Page 5 Monday, Jne 17, 5:6 PM CHAPTER 3 POWER-OF- BOUNDARIES 3 1 Ronding Up/Down to a Mltiple of a Known Power of Ronding an nsigned integer down to, for eample, the net smaller mltiple of 8, is trivial: & 8 does it. An alternative is ( >> 3) << 3. These work for signed integers as well, provided rond down means to rond in the negative direction (e.g., ( 37) & ( 8) = ). Ronding p is almost as easy. For eample, an nsigned integer can be ronded p to the net greater mltiple of 8 with either of ( + 7) & 8, or + ( & 7). These epressions are correct for signed integers as well, provided rond p means to rond in the positive direction. The second term of the second epression is sefl if yo want to know how mch yo mst add to to make it a mltiple of 8 [Gold]. To rond a signed integer to the nearest mltiple of 8 toward, yo can combine the two epressions above in an obvios way: s t ( >> 31) & 7; ( + t) & 8 An alternative for the first line is t ( >> ) >> 9, which is sefl if the machine lacks and immediate, or if the constant is too large for its immediate field. Sometimes the ronding factor is given as the log of the alignment amont (e.g., a vale of 3 means to rond to a mltiple of 8). In this case, code sch as the following may be sed, where k = log (alignment amont): rond down: & (( 1) << k) ( >> k) << k rond p: t ( 1 << k) 1; ( + t) & t t ( 1) << k; ( t 1) & t s 5

2 Warren.book Page 6 Monday, Jne 17, :37 PM 6 POWER-OF- BOUNDARIES 3 3 Ronding Up/Down to the Net Power of We define two fnctions that are similar to floor and ceiling, bt which are directed rondings to the closest integral power of, rather than to the closest integer. Mathematically, they are defined by flp() ndefined, <, =, =, clp() log, otherwise; = ndefined, <,, =, log, otherwise. The initial letters of the fnction names are intended to sggest floor and ceiling. Ths, flp() is the greatest power of that is, and clp() is the least power of that is. These definitions make sense even when is not an integer (e.g., flp(.1) =.65). The fnctions satisfy several relations analogos to those involving floor and ceiling, sch as those shown below, where n is an integer. = iff is an integer + n = + n = flp() = clp () iff is a power of or is flp( n ) = n flp() clp() = 1 flp1 ( ), Comptationally, we deal only with the case in which is an integer, and we take it to be nsigned, so the fnctions are well defined for all. We reqire the vale compted to be the arithmetically correct vale modlo 3 (that is, we take clp( ) to be for > ). The fnctions are tablated below for a few vales of flp( ) 1 3 clp( ) 1 8

3 Warren.book Page 7 Monday, Jne 17, :37 PM 3 ROUNDING UP/DOWN TO THE NEXT POWER OF 7 Fnctions flp and clp are connected by the relations shown below. These can be sed to compte one from the other, sbject to the indicated restrictions. clp( ) = flp( 1), 1, = flp( 1), 1, flp( ) = clp( + 1),, = clp( + 1), <. The rond-p and rond-down fnctions can be compted qite easily with the nmber of leading zeros instrction, as shown below. However, for these relations to hold for = and >, the compter mst have its shift instrctions defined to prodce for shift amonts of 1, 3, and 63. Many machines (e.g., PowerPC) have mod 6 shifts, which do this. In the case of 1, it is adeqate if the machine shifts in the opposite direction (that is, a shift left of 1 becomes a shift right of 1). flp() = 1 << ( 31 nlz() ) = 1 << ( nlz() 31) = 8 >> nlz() clp() = 1 << ( 3 nlz( 1) ) Ronding Down Figre 3 1 illstrates a branch-free algorithm that might be sefl if nmber of leading zeros is not available. This algorithm is based on right-propagating the leftmost 1-bit, and eectes in 1 instrctions. Figre 3 shows two simple loops that compte the same fnction. All variables are nsigned integers. The loop on the right keeps trning off the rightmost 1-bit of ntil =, and then retrns the previos vale of. = 8 >> ( nlz( 1) 1) nsigned flp(nsigned ) { = ( >> 1); = ( >> ); = ( >> ); = ( >> 8); = ( >>16); retrn - ( >> 1); } FIGURE 3 1. Greatest power of less than or eqal to, branch-free.

4 Warren.book Page 8 Monday, Jne 17, :37 PM 8 POWER-OF- BOUNDARIES 3 y = 8; do { while (y > ) y = ; y = y >> 1; = & ( - 1); retrn } while(!= ); retrn y; The loop on the left eectes in nlz( ) + 3 instrctions. The loop on the right, for, eectes in pop() instrctions, 1 if the comparison to is zerocost. Ronding Up The right-propagation trick yields a good algorithm for ronding p to the net power of. This algorithm, shown in Figre 3 3, is branch-free and rns in 1 instrctions. An attempt to compte this with the obvios loop does not work ot very well: y = 1; FIGURE 3. Greatest power of less than or eqal to, simple loops. while (y < ) y = *y; retrn y; // Unsigned comparison. This code retrns 1 for =, which is probably not what yo want, loops forever for, and eectes in n + 3 instrctions, where n is the power of of the retrned integer. Ths, it is slower than the branch-free code, in terms of instrctions eected, for n 3 ( 8). nsigned clp(nsigned ) { = - 1; = ( >> 1); = ( >> ); = ( >> ); = ( >> 8); = ( >>16); retrn + 1; } FIGURE 3 3. Least power of greater than or eqal to. 1. pop() is the nmber of 1-bits in.

5 Warren.book Page 9 Monday, Jne 17, :37 PM 3 3 DETECTING A POWER-OF- BOUNDARY CROSSING Detecting a Power-of- Bondary Crossing Assme memory is divided into blocks that are a power of in size, starting at address. The blocks may be words, doblewords, pages, and so on. Then, given a starting address a and a length l, we wish to determine whether or not the address range from a to a + l 1, l, crosses a block bondary. The qantities a and l are nsigned and any vales that fit in a register are possible. If l = or 1, a bondary crossing does not occr, regardless of a. If l eceeds the block size, a bondary crossing does occr, regardless of a. For very large vales of l (wraparond is possible), a bondary crossing can occr even if the first and last bytes of the address range are in the same block. There is a srprisingly concise way to detect bondary crossings on the IBM System/37 [CJS]. This method is illstrated below for a block size of 96 bytes (a common page size). O RA,=A(-96) ALR RA,RL BO CROSSES The first instrction forms the logical or of RA (which contains the starting address a) and the nmber FFFFF. The second instrction adds in the length, and sets the machine s -bit condition code. For the add logical instrction, the first bit of the condition code is set to 1 if a carry occrred, and the second bit is set to 1 if the 3-bit register reslt is nonzero. The last instrction branches if both bits are set. At the branch target, RA will contain the length that etends beyond the first page (this is an etra featre that was not asked for). If, for eample, a = and l = 96, a carry occrs bt the register reslt is, so the program properly does not branch to label CROSSES. Let s see how this method can be adapted to RISC machines, which generally do not have branch on carry and register reslt nonzero. Using a block size of 8 for notational simplicity, the method of [CJS] branches to CROSSES if a carry occrred (( a 8) + l 3 ) and the register reslt is nonzero (( a 8) + l 3 ). Ths, it is eqivalent to the predicate ( a 8) + l > 3. This in trn is eqivalent to getting a carry in the final addition in evalating (( a 8) 1) + l. If the machine has branch on carry, this can be sed directly, giving a soltion in abot five instrctions conting a load of the constant 8. If the machine does not have branch on carry, we can se the fact that carry occrs in + y iff < y (see Unsigned Add/Sbtract on page 9) to obtain the epression (( a 8) 1) l. <

6 Warren.book Page 5 Monday, Jne 17, :37 PM 5 POWER-OF- BOUNDARIES 3 3 Using varios identities sch as ( 1) = gives the following eqivalent epressions for the bondary crossed predicate: ( a 8) l These can be evalated in five or si instrctions on most RISC compters. Using another tack, clearly an 8-byte bondary is crossed iff This cannot be directly evalated becase of the possibility of overflow (which occrs if l is very large), bt it is easily rearranged to 8 ( a & 7) < l, which can be directly evalated on the compter (no part of it overflows). This gives the epression which can be evalated in five instrctions on most RISCs (for if it has sbtract from immediate). If a bondary crossing occrs, the length that etends beyond the first block is given by l ( 8 ( a & 7) ), which can be calclated with one additional instrction (sbtract). < ( a 8) + 1 l < ( a & 7) + 1 l < ( a & 7) + l ( a & 7) < l,

Multiple-Choice Test Chapter Golden Section Search Method Optimization COMPLETE SOLUTION SET

Multiple-Choice Test Chapter Golden Section Search Method Optimization COMPLETE SOLUTION SET Mltiple-Choice Test Chapter 09.0 Golden Section Search Method Optimization COMPLETE SOLUTION SET. Which o the ollowing statements is incorrect regarding the Eqal Interval Search and Golden Section Search

More information

Review. How to represent real numbers

Review. How to represent real numbers PCWrite PC IorD Review ALUSrcA emread Address Write data emory emwrite em Data IRWrite [3-26] [25-2] [2-6] [5-] [5-] RegDst Read register Read register 2 Write register Write data RegWrite Read data Read

More information

EXAMINATIONS 2003 END-YEAR COMP 203. Computer Organisation

EXAMINATIONS 2003 END-YEAR COMP 203. Computer Organisation EXAINATIONS 2003 COP203 END-YEAR Compter Organisation Time Allowed: 3 Hors (180 mintes) Instrctions: Answer all qestions. There are 180 possible marks on the eam. Calclators and foreign langage dictionaries

More information

Prof. Kozyrakis. 1. (10 points) Consider the following fragment of Java code:

Prof. Kozyrakis. 1. (10 points) Consider the following fragment of Java code: EE8 Winter 25 Homework #2 Soltions De Thrsday, Feb 2, 5 P. ( points) Consider the following fragment of Java code: for (i=; i

More information

Review Multicycle: What is Happening. Controlling The Multicycle Design

Review Multicycle: What is Happening. Controlling The Multicycle Design Review lticycle: What is Happening Reslt Zero Op SrcA SrcB Registers Reg Address emory em Data Sign etend Shift left Sorce A B Ot [-6] [5-] [-6] [5-] [5-] Instrction emory IR RegDst emtoreg IorD em em

More information

EXAMINATIONS 2010 END OF YEAR NWEN 242 COMPUTER ORGANIZATION

EXAMINATIONS 2010 END OF YEAR NWEN 242 COMPUTER ORGANIZATION EXAINATIONS 2010 END OF YEAR COPUTER ORGANIZATION Time Allowed: 3 Hors (180 mintes) Instrctions: Answer all qestions. ake sre yor answers are clear and to the point. Calclators and paper foreign langage

More information

EEC 483 Computer Organization

EEC 483 Computer Organization EEC 483 Compter Organization Chapter 4.4 A Simple Implementation Scheme Chans Y The Big Pictre The Five Classic Components of a Compter Processor Control emory Inpt path Otpt path & Control 2 path and

More information

The final datapath. M u x. Add. 4 Add. Shift left 2. PCSrc. RegWrite. MemToR. MemWrite. Read data 1 I [25-21] Instruction. Read. register 1 Read.

The final datapath. M u x. Add. 4 Add. Shift left 2. PCSrc. RegWrite. MemToR. MemWrite. Read data 1 I [25-21] Instruction. Read. register 1 Read. The final path PC 4 Add Reg Shift left 2 Add PCSrc Instrction [3-] Instrction I [25-2] I [2-6] I [5 - ] register register 2 register 2 Registers ALU Zero Reslt ALUOp em Data emtor RegDst ALUSrc em I [5

More information

TDT4255 Friday the 21st of October. Real world examples of pipelining? How does pipelining influence instruction

TDT4255 Friday the 21st of October. Real world examples of pipelining? How does pipelining influence instruction Review Friday the 2st of October Real world eamples of pipelining? How does pipelining pp inflence instrction latency? How does pipelining inflence instrction throghpt? What are the three types of hazard

More information

The extra single-cycle adders

The extra single-cycle adders lticycle Datapath As an added bons, we can eliminate some of the etra hardware from the single-cycle path. We will restrict orselves to sing each fnctional nit once per cycle, jst like before. Bt since

More information

The single-cycle design from last time

The single-cycle design from last time lticycle path Last time we saw a single-cycle path and control nit for or simple IPS-based instrction set. A mlticycle processor fies some shortcomings in the single-cycle CPU. Faster instrctions are not

More information

The multicycle datapath. Lecture 10 (Wed 10/15/2008) Finite-state machine for the control unit. Implementing the FSM

The multicycle datapath. Lecture 10 (Wed 10/15/2008) Finite-state machine for the control unit. Implementing the FSM Lectre (Wed /5/28) Lab # Hardware De Fri Oct 7 HW #2 IPS programming, de Wed Oct 22 idterm Fri Oct 2 IorD The mlticycle path SrcA Today s objectives: icroprogramming Etending the mlti-cycle path lti-cycle

More information

Chapter 6: Pipelining

Chapter 6: Pipelining CSE 322 COPUTER ARCHITECTURE II Chapter 6: Pipelining Chapter 6: Pipelining Febrary 10, 2000 1 Clothes Washing CSE 322 COPUTER ARCHITECTURE II The Assembly Line Accmlate dirty clothes in hamper Place in

More information

PART I: Adding Instructions to the Datapath. (2 nd Edition):

PART I: Adding Instructions to the Datapath. (2 nd Edition): EE57 Instrctor: G. Pvvada ===================================================================== Homework #5b De: check on the blackboard =====================================================================

More information

Review. A single-cycle MIPS processor

Review. A single-cycle MIPS processor Review If three instrctions have opcodes, 7 and 5 are they all of the same type? If we were to add an instrction to IPS of the form OD $t, $t2, $t3, which performs $t = $t2 OD $t3, what wold be its opcode?

More information

CS 251, Winter 2019, Assignment % of course mark

CS 251, Winter 2019, Assignment % of course mark CS 25, Winter 29, Assignment.. 3% of corse mark De Wednesday, arch 3th, 5:3P Lates accepted ntil Thrsday arch th, pm with a 5% penalty. (7 points) In the diagram below, the mlticycle compter from the corse

More information

CS 251, Spring 2018, Assignment 3.0 3% of course mark

CS 251, Spring 2018, Assignment 3.0 3% of course mark CS 25, Spring 28, Assignment 3. 3% of corse mark De onday, Jne 25th, 5:3 P. (5 points) Consider the single-cycle compter shown on page 6 of this assignment. Sppose the circit elements take the following

More information

Lecture 7. Building A Simple Processor

Lecture 7. Building A Simple Processor Lectre 7 Bilding A Simple Processor Christos Kozyrakis Stanford University http://eeclass.stanford.ed/ee8b C. Kozyrakis EE8b Lectre 7 Annoncements Upcoming deadlines Lab is de today Demo by 5pm, report

More information

Pipelining. Chapter 4

Pipelining. Chapter 4 Pipelining Chapter 4 ake processor rns faster Pipelining is an implementation techniqe in which mltiple instrctions are overlapped in eection Key of making processor fast Pipelining Single cycle path we

More information

4.13 Advanced Topic: An Introduction to Digital Design Using a Hardware Design Language 345.e1

4.13 Advanced Topic: An Introduction to Digital Design Using a Hardware Design Language 345.e1 .3 Advanced Topic: An Introdction to Digital Design Using a Hardware Design Langage 35.e.3 Advanced Topic: An Introdction to Digital Design Using a Hardware Design Langage to Describe and odel a Pipeline

More information

Computer Architecture Chapter 5. Fall 2005 Department of Computer Science Kent State University

Computer Architecture Chapter 5. Fall 2005 Department of Computer Science Kent State University Compter Architectre Chapter 5 Fall 25 Department of Compter Science Kent State University The Processor: Datapath & Control Or implementation of the MIPS is simplified memory-reference instrctions: lw,

More information

5 Performance Evaluation

5 Performance Evaluation 5 Performance Evalation his chapter evalates the performance of the compared to the MIP, and FMIP individal performances. We stdy the packet loss and the latency to restore the downstream and pstream of

More information

Comp 303 Computer Architecture A Pipelined Datapath Control. Lecture 13

Comp 303 Computer Architecture A Pipelined Datapath Control. Lecture 13 Comp 33 Compter Architectre A Pipelined path Lectre 3 Pipelined path with Signals PCSrc IF/ ID ID/ EX EX / E E / Add PC 4 Address Instrction emory RegWr ra rb rw Registers bsw [5-] [2-6] [5-] bsa bsb Sign

More information

CS 251, Winter 2018, Assignment % of course mark

CS 251, Winter 2018, Assignment % of course mark CS 25, Winter 28, Assignment 3.. 3% of corse mark De onday, Febrary 26th, 4:3 P Lates accepted ntil : A, Febrary 27th with a 5% penalty. IEEE 754 Floating Point ( points): (a) (4 points) Complete the following

More information

Enhanced Performance with Pipelining

Enhanced Performance with Pipelining Chapter 6 Enhanced Performance with Pipelining Note: The slides being presented represent a mi. Some are created by ark Franklin, Washington University in St. Lois, Dept. of CSE. any are taken from the

More information

CS 251, Winter 2018, Assignment % of course mark

CS 251, Winter 2018, Assignment % of course mark CS 25, Winter 28, Assignment 4.. 3% of corse mark De Wednesday, arch 7th, 4:3P Lates accepted ntil Thrsday arch 8th, am with a 5% penalty. (6 points) In the diagram below, the mlticycle compter from the

More information

1048: Computer Organization

1048: Computer Organization 48: Compter Organization Lectre 5 Datapath and Control Lectre5A - simple implementation (cwli@twins.ee.nct.ed.tw) 5A- Introdction In this lectre, we will try to implement simplified IPS which contain emory

More information

Bits, Bytes, and Integers. Bits, Bytes, and Integers. The Decimal System and Bases. Everything is bits. Converting from Decimal to Binary

Bits, Bytes, and Integers. Bits, Bytes, and Integers. The Decimal System and Bases. Everything is bits. Converting from Decimal to Binary with contribtions from Dr. Bin Ren, College of William & Mary Addition, negation, mltiplication, shifting 1 Everything is bits The Decimal System and Bases Each bit is or 1 By encoding/interpreting sets

More information

This chapter is based on the following sources, which are all recommended reading:

This chapter is based on the following sources, which are all recommended reading: Bioinformatics I, WS 09-10, D. Hson, December 7, 2009 105 6 Fast String Matching This chapter is based on the following sorces, which are all recommended reading: 1. An earlier version of this chapter

More information

Ma Lesson 18 Section 1.7

Ma Lesson 18 Section 1.7 Ma 15200 Lesson 18 Section 1.7 I Representing an Ineqality There are 3 ways to represent an ineqality. (1) Using the ineqality symbol (sometime within set-bilder notation), (2) sing interval notation,

More information

Chapter 6 Enhancing Performance with. Pipelining. Pipelining. Pipelined vs. Single-Cycle Instruction Execution: the Plan. Pipelining: Keep in Mind

Chapter 6 Enhancing Performance with. Pipelining. Pipelining. Pipelined vs. Single-Cycle Instruction Execution: the Plan. Pipelining: Keep in Mind Pipelining hink of sing machines in landry services Chapter 6 nhancing Performance with Pipelining 6 P 7 8 9 A ime ask A B C ot pipelined Assme 3 min. each task wash, dry, fold, store and that separate

More information

Chapter 3 & Appendix C Pipelining Part A: Basic and Intermediate Concepts

Chapter 3 & Appendix C Pipelining Part A: Basic and Intermediate Concepts CS359: Compter Architectre Chapter 3 & Appendi C Pipelining Part A: Basic and Intermediate Concepts Yanyan Shen Department of Compter Science and Engineering Shanghai Jiao Tong University 1 Otline Introdction

More information

CAPL Scripting Quickstart

CAPL Scripting Quickstart CAPL Scripting Qickstart CAPL (Commnication Access Programming Langage) For CANalyzer and CANoe V1.01 2015-12-03 Agenda Important information before getting started 3 Visal Seqencer (GUI based programming

More information

Review: Computer Organization

Review: Computer Organization Review: Compter Organization Pipelining Chans Y Landry Eample Landry Eample Ann, Brian, Cathy, Dave each have one load of clothes to wash, dry, and fold Washer takes 3 mintes A B C D Dryer takes 3 mintes

More information

Page # CISC360. Integers Sep 11, Encoding Integers Unsigned. Encoding Example (Cont.) Topics. Twoʼs Complement. Sign Bit

Page # CISC360. Integers Sep 11, Encoding Integers Unsigned. Encoding Example (Cont.) Topics. Twoʼs Complement. Sign Bit Topics CISC3 Integers Sep 11, 28 Nmeric Encodings Unsigned & Twoʼs complement Programming Implications C promotion rles Basic operations Addition, negation, mltiplication Programming Implications Conseqences

More information

Winter 2013 MIDTERM TEST #2 Wednesday, March 20 7:00pm to 8:15pm. Please do not write your U of C ID number on this cover page.

Winter 2013 MIDTERM TEST #2 Wednesday, March 20 7:00pm to 8:15pm. Please do not write your U of C ID number on this cover page. page of 7 University of Calgary Departent of Electrical and Copter Engineering ENCM 369: Copter Organization Lectre Instrctors: Steve Noran and Nor Bartley Winter 23 MIDTERM TEST #2 Wednesday, March 2

More information

Image Compression Compression Fundamentals

Image Compression Compression Fundamentals Compression Fndamentals Data compression refers to the process of redcing the amont of data reqired to represent given qantity of information. Note that data and information are not the same. Data refers

More information

Hardware Design Tips. Outline

Hardware Design Tips. Outline Hardware Design Tips EE 36 University of Hawaii EE 36 Fall 23 University of Hawaii Otline Verilog: some sbleties Simlators Test Benching Implementing the IPS Actally a simplified 6 bit version EE 36 Fall

More information

EEC 483 Computer Organization

EEC 483 Computer Organization EEC 83 Compter Organization Chapter.6 A Pipelined path Chans Y Pipelined Approach 2 - Cycle time, No. stages - Resorce conflict E E A B C D 3 E E 5 E 2 3 5 2 6 7 8 9 c.y9@csohio.ed Resorces sed in 5 Stages

More information

Pavlin and Daniel D. Corkill. Department of Computer and Information Science University of Massachusetts Amherst, Massachusetts 01003

Pavlin and Daniel D. Corkill. Department of Computer and Information Science University of Massachusetts Amherst, Massachusetts 01003 From: AAAI-84 Proceedings. Copyright 1984, AAAI (www.aaai.org). All rights reserved. SELECTIVE ABSTRACTION OF AI SYSTEM ACTIVITY Jasmina Pavlin and Daniel D. Corkill Department of Compter and Information

More information

Bias of Higher Order Predictive Interpolation for Sub-pixel Registration

Bias of Higher Order Predictive Interpolation for Sub-pixel Registration Bias of Higher Order Predictive Interpolation for Sb-pixel Registration Donald G Bailey Institte of Information Sciences and Technology Massey University Palmerston North, New Zealand D.G.Bailey@massey.ac.nz

More information

Lecture 10: Pipelined Implementations

Lecture 10: Pipelined Implementations U 8-7 S 9 L- 8-7 Lectre : Pipelined Implementations James. Hoe ept of EE, U Febrary 23, 29 nnoncements: Project is de this week idterm graded, d reslts posted Handots: H9 Homework 3 (on lackboard) Graded

More information

Exceptions and interrupts

Exceptions and interrupts Eceptions and interrpts An eception or interrpt is an nepected event that reqires the CPU to pase or stop the crrent program. Eception handling is the hardware analog of error handling in software. Classes

More information

1048: Computer Organization

1048: Computer Organization 48: Compter Organization Lectre 5 Datapath and Control Lectre5B - mlticycle implementation (cwli@twins.ee.nct.ed.tw) 5B- Recap: A Single-Cycle Processor PCSrc 4 Add Shift left 2 Add ALU reslt PC address

More information

Maximum Weight Independent Sets in an Infinite Plane

Maximum Weight Independent Sets in an Infinite Plane Maximm Weight Independent Sets in an Infinite Plane Jarno Nosiainen, Jorma Virtamo, Pasi Lassila jarno.nosiainen@tkk.fi, jorma.virtamo@tkk.fi, pasi.lassila@tkk.fi Department of Commnications and Networking

More information

(2, 4) Tree Example (2, 4) Tree: Insertion

(2, 4) Tree Example (2, 4) Tree: Insertion Presentation for se with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015 B-Trees and External Memory (2, 4) Trees Each internal node has 2 to 4 children:

More information

Overview of Pipelining

Overview of Pipelining EEC 58 Compter Architectre Pipelining Department of Electrical Engineering and Compter Science Cleveland State University Fndamental Principles Overview of Pipelining Pipelined Design otivation: Increase

More information

Evaluating Influence Diagrams

Evaluating Influence Diagrams Evalating Inflence Diagrams Where we ve been and where we re going Mark Crowley Department of Compter Science University of British Colmbia crowley@cs.bc.ca Agst 31, 2004 Abstract In this paper we will

More information

Functions of Combinational Logic

Functions of Combinational Logic CHPTER 6 Fnctions of Combinational Logic CHPTER OUTLINE 6 6 6 6 6 5 6 6 6 7 6 8 6 9 6 6 Half and Fll dders Parallel inary dders Ripple Carry and Look-head Carry dders Comparators Decoders Encoders Code

More information

What do we have so far? Multi-Cycle Datapath

What do we have so far? Multi-Cycle Datapath What do we have so far? lti-cycle Datapath CPI: R-Type = 4, Load = 5, Store 4, Branch = 3 Only one instrction being processed in datapath How to lower CPI frther? #1 Lec # 8 Spring2 4-11-2 Pipelining pipelining

More information

EEC 483 Computer Organization. Branch (Control) Hazards

EEC 483 Computer Organization. Branch (Control) Hazards EEC 483 Compter Organization Section 4.8 Branch Hazards Section 4.9 Exceptions Chans Y Branch (Control) Hazards While execting a previos branch, next instrction address might not yet be known. s n i o

More information

Lab 8 (All Sections) Prelab: ALU and ALU Control

Lab 8 (All Sections) Prelab: ALU and ALU Control Lab 8 (All Sections) Prelab: and Control Name: Sign the following statement: On my honor, as an Aggie, I have neither given nor received nathorized aid on this academic work Objective In this lab yo will

More information

OPTI-502 Optical Design and Instrumentation I John E. Greivenkamp Homework Set 9 Fall, 2018

OPTI-502 Optical Design and Instrumentation I John E. Greivenkamp Homework Set 9 Fall, 2018 OPTI-502 Optical Design and Instrmentation I John E. Greivenkamp Assigned: 10/31/18 Lectre 21 De: 11/7/18 Lectre 23 Note that in man 502 homework and exam problems (as in the real world!!), onl the magnitde

More information

10.2 Solving Quadratic Equations by Completing the Square

10.2 Solving Quadratic Equations by Completing the Square . Solving Qadratic Eqations b Completing the Sqare Consider the eqation We can see clearl that the soltions are However, What if the eqation was given to s in standard form, that is 6 How wold we go abot

More information

Networks An introduction to microcomputer networking concepts

Networks An introduction to microcomputer networking concepts Behavior Research Methods& Instrmentation 1978, Vol 10 (4),522-526 Networks An introdction to microcompter networking concepts RALPH WALLACE and RICHARD N. JOHNSON GA TX, Chicago, Illinois60648 and JAMES

More information

EECS 487: Interactive Computer Graphics f

EECS 487: Interactive Computer Graphics f Interpolating Key Vales EECS 487: Interactive Compter Graphics f Keys Lectre 33: Keyframe interpolation and splines Cbic splines The key vales of each variable may occr at different frames The interpolation

More information

arxiv: v1 [cs.cg] 26 Sep 2018

arxiv: v1 [cs.cg] 26 Sep 2018 Convex partial transversals of planar regions arxiv:1809.10078v1 [cs.cg] 26 Sep 2018 Vahideh Keikha Department of Mathematics and Compter Science, University of Sistan and Balchestan, Zahedan, Iran va.keikha@gmail.com

More information

Animating the Datapath. Animating the Datapath: R-type Instruction. Animating the Datapath: Load Instruction. MIPS Datapath I: Single-Cycle

Animating the Datapath. Animating the Datapath: R-type Instruction. Animating the Datapath: Load Instruction. MIPS Datapath I: Single-Cycle nimating the atapath PS atapath : Single-Cycle npt is either (-type) or sign-etended lower half of instrction (load/store) op offset/immediate W egister File 6 6 + from instrction path beq,, offset if

More information

1048: Computer Organization

1048: Computer Organization 8: Compter Organization Lectre 6 Pipelining Lectre6 - pipelining (cwli@twins.ee.nct.ed.tw) 6- Otline An overview of pipelining A pipelined path Pipelined control Data hazards and forwarding Data hazards

More information

Dynamic Maintenance of Majority Information in Constant Time per Update? Gudmund S. Frandsen and Sven Skyum BRICS 1 Department of Computer Science, Un

Dynamic Maintenance of Majority Information in Constant Time per Update? Gudmund S. Frandsen and Sven Skyum BRICS 1 Department of Computer Science, Un Dynamic Maintenance of Majority Information in Constant Time per Update? Gdmnd S. Frandsen and Sven Skym BRICS 1 Department of Compter Science, University of arhs, Ny Mnkegade, DK-8000 arhs C, Denmark

More information

Quiz #1 EEC 483, Spring 2019

Quiz #1 EEC 483, Spring 2019 Qiz # EEC 483, Spring 29 Date: Jan 22 Name: Eercise #: Translate the following instrction in C into IPS code. Eercise #2: Translate the following instrction in C into IPS code. Hint: operand C is stored

More information

Solutions for Chapter 6 Exercises

Solutions for Chapter 6 Exercises Soltions for Chapter 6 Eercises Soltions for Chapter 6 Eercises 6. 6.2 a. Shortening the ALU operation will not affect the speedp obtained from pipelining. It wold not affect the clock cycle. b. If the

More information

CSE 141 Computer Architecture Summer Session I, Lectures 10 Advanced Topics, Memory Hierarchy and Cache. Pramod V. Argade

CSE 141 Computer Architecture Summer Session I, Lectures 10 Advanced Topics, Memory Hierarchy and Cache. Pramod V. Argade CSE 141 Compter Architectre Smmer Session I, 2004 Lectres 10 Advanced Topics, emory Hierarchy and Cache Pramod V. Argade CSE141: Introdction to Compter Architectre Instrctor: TA: Pramod V. Argade (p2argade@cs.csd.ed)

More information

Discrete Cost Multicommodity Network Optimization Problems and Exact Solution Methods

Discrete Cost Multicommodity Network Optimization Problems and Exact Solution Methods Annals of Operations Research 106, 19 46, 2001 2002 Klwer Academic Pblishers. Manfactred in The Netherlands. Discrete Cost Mlticommodity Network Optimization Problems and Exact Soltion Methods MICHEL MINOUX

More information

Chapter 6: Pipelining

Chapter 6: Pipelining Chapter 6: Pipelining Otline An overview of pipelining A pipelined path Pipelined control Data hazards and forwarding Data hazards and stalls Branch hazards Eceptions Sperscalar and dynamic pipelining

More information

Resolving Linkage Anomalies in Extracted Software System Models

Resolving Linkage Anomalies in Extracted Software System Models Resolving Linkage Anomalies in Extracted Software System Models Jingwei W and Richard C. Holt School of Compter Science University of Waterloo Waterloo, Canada j25w, holt @plg.waterloo.ca Abstract Program

More information

Instruction fetch. MemRead. IRWrite ALUSrcB = 01. ALUOp = 00. PCWrite. PCSource = 00. ALUSrcB = 00. R-type completion

Instruction fetch. MemRead. IRWrite ALUSrcB = 01. ALUOp = 00. PCWrite. PCSource = 00. ALUSrcB = 00. R-type completion . (Chapter 5) Fill in the vales for SrcA, SrcB, IorD, Dst and emto to complete the Finite State achine for the mlti-cycle datapath shown below. emory address comptation 2 SrcA = SrcB = Op = fetch em SrcA

More information

Topic Continuity for Web Document Categorization and Ranking

Topic Continuity for Web Document Categorization and Ranking Topic Continity for Web ocment Categorization and Ranking B. L. Narayan, C. A. Mrthy and Sankar. Pal Machine Intelligence Unit, Indian Statistical Institte, 03, B. T. Road, olkata - 70008, India. E-mail:

More information

A Hybrid Weight-Based Clustering Algorithm for Wireless Sensor Networks

A Hybrid Weight-Based Clustering Algorithm for Wireless Sensor Networks Open Access Library Jornal A Hybrid Weight-Based Clstering Algorithm for Wireless Sensor Networks Cheikh Sidy Mohamed Cisse, Cheikh Sarr * Faclty of Science and Technology, University of Thies, Thies,

More information

CS 4204 Computer Graphics

CS 4204 Computer Graphics CS 424 Compter Graphics Crves and Srfaces Yong Cao Virginia Tech Reference: Ed Angle, Interactive Compter Graphics, University of New Mexico, class notes Crve and Srface Modeling Objectives Introdce types

More information

CS 153 Design of Operating Systems

CS 153 Design of Operating Systems CS 53 Design of Operating Systems Spring 8 Lectre 9: Locality and Cache Instrctor: Chengy Song Slide contribtions from Nael Ab-Ghazaleh, Harsha Madhyvasta and Zhiyn Qian Some slides modified from originals

More information

Date: December 5, 1999 Dist'n: T1E1.4

Date: December 5, 1999 Dist'n: T1E1.4 12/4/99 1 T1E14/99-559 Project: T1E14: VDSL Title: Vectored VDSL (99-559) Contact: J Cioffi, G Ginis, W Y Dept of EE, Stanford U, Stanford, CA 945 Cioffi@stanforded, 1-65-723-215, F: 1-65-724-3652 Date:

More information

CS 153 Design of Operating Systems

CS 153 Design of Operating Systems CS 153 Design of Operating Systems Spring 18 Lectre 25: Dynamic Memory (1) Instrctor: Chengy Song Slide contribtions from Nael Ab-Ghazaleh, Harsha Madhyvasta and Zhiyn Qian Some slides modified from originals

More information

Towards Understanding Bilevel Multi-objective Optimization with Deterministic Lower Level Decisions

Towards Understanding Bilevel Multi-objective Optimization with Deterministic Lower Level Decisions Towards Understanding Bilevel Mlti-objective Optimization with Deterministic Lower Level Decisions Ankr Sinha Ankr.Sinha@aalto.fi Department of Information and Service Economy, Aalto University School

More information

Tdb: A Source-level Debugger for Dynamically Translated Programs

Tdb: A Source-level Debugger for Dynamically Translated Programs Tdb: A Sorce-level Debgger for Dynamically Translated Programs Naveen Kmar, Brce R. Childers, and Mary Lo Soffa Department of Compter Science University of Pittsbrgh Pittsbrgh, Pennsylvania 15260 {naveen,

More information

CS 153 Design of Operating Systems Spring 18

CS 153 Design of Operating Systems Spring 18 CS 153 Design of Operating Systems Spring 18 Lectre 11: Semaphores Instrctor: Chengy Song Slide contribtions from Nael Ab-Ghazaleh, Harsha Madhyvasta and Zhiyn Qian Last time Worked throgh software implementation

More information

Method to build an initial adaptive Neuro-Fuzzy controller for joints control of a legged robot

Method to build an initial adaptive Neuro-Fuzzy controller for joints control of a legged robot Method to bild an initial adaptive Nero-Fzzy controller for joints control of a legged robot J-C Habmremyi, P. ool and Y. Badoin Royal Military Academy-Free University of Brssels 08 Hobbema str, box:mrm,

More information

A sufficient condition for spiral cone beam long object imaging via backprojection

A sufficient condition for spiral cone beam long object imaging via backprojection A sfficient condition for spiral cone beam long object imaging via backprojection K. C. Tam Siemens Corporate Research, Inc., Princeton, NJ, USA Abstract The response of a point object in cone beam spiral

More information

Fast Ray Tetrahedron Intersection using Plücker Coordinates

Fast Ray Tetrahedron Intersection using Plücker Coordinates Fast Ray Tetrahedron Intersection sing Plücker Coordinates Nikos Platis and Theoharis Theoharis Department of Informatics & Telecommnications University of Athens Panepistemiopolis, GR 157 84 Ilissia,

More information

Today: Bits, Bytes, and Integers. Bits, Bytes, and Integers. For example, can count in binary. Everything is bits. Encoding Byte Values

Today: Bits, Bytes, and Integers. Bits, Bytes, and Integers. For example, can count in binary. Everything is bits. Encoding Byte Values Today: Bits, Bytes, and Integers Representing information as bits Bits, Bytes, and Integers CSci : Machine Architectre and Organization September th-9th, Yor instrctor: Stephen McCamant Bit-level maniplations

More information

PS Midterm 2. Pipelining

PS Midterm 2. Pipelining PS idterm 2 Pipelining Seqential Landry 6 P 7 8 9 idnight Time T a s k O r d e r A B C D 3 4 2 3 4 2 3 4 2 3 4 2 Seqential landry takes 6 hors for 4 loads If they learned pipelining, how long wold landry

More information

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 6, NO. 5, MAY On the Analysis of the Bluetooth Time Division Duplex Mechanism

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 6, NO. 5, MAY On the Analysis of the Bluetooth Time Division Duplex Mechanism IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 6, NO. 5, MAY 2007 1 On the Analysis of the Bletooth Time Division Dplex Mechanism Gil Zssman Member, IEEE, Adrian Segall Fellow, IEEE, and Uri Yechiali

More information

Dr Paolo Guagliardo. Fall 2018

Dr Paolo Guagliardo. Fall 2018 The NULL vale Dr Paolo Gagliardo dbs-lectrer@ed.ac.k Fall 2018 NULL: all-prpose marker to represent incomplete information Main sorce of problems and inconsistencies... this topic cannot be described in

More information

Fault Tolerance in Hypercubes

Fault Tolerance in Hypercubes Falt Tolerance in Hypercbes Shobana Balakrishnan, Füsn Özgüner, and Baback A. Izadi Department of Electrical Engineering, The Ohio State University, Colmbs, OH 40, USA Abstract: This paper describes different

More information

Illumina LIMS. Software Guide. For Research Use Only. Not for use in diagnostic procedures. Document # June 2017 ILLUMINA PROPRIETARY

Illumina LIMS. Software Guide. For Research Use Only. Not for use in diagnostic procedures. Document # June 2017 ILLUMINA PROPRIETARY Illmina LIMS Software Gide Jne 2017 ILLUMINA PROPRIETARY This docment and its contents are proprietary to Illmina, Inc. and its affiliates ("Illmina"), and are intended solely for the contractal se of

More information

CS 153 Design of Operating Systems

CS 153 Design of Operating Systems CS 153 Design of Operating Systems Spring 18 Lectre 3: OS model and Architectral Spport Instrctor: Chengy Song Slide contribtions from Nael Ab-Ghazaleh, Harsha Madhyvasta and Zhiyn Qian Last time/today

More information

h-vectors of PS ear-decomposable graphs

h-vectors of PS ear-decomposable graphs h-vectors of PS ear-decomposable graphs Nima Imani 2, Lee Johnson 1, Mckenzie Keeling-Garcia 1, Steven Klee 1 and Casey Pinckney 1 1 Seattle University Department of Mathematics, 901 12th Avene, Seattle,

More information

FINITE ELEMENT APPROXIMATION OF CONVECTION DIFFUSION PROBLEMS USING GRADED MESHES

FINITE ELEMENT APPROXIMATION OF CONVECTION DIFFUSION PROBLEMS USING GRADED MESHES FINITE ELEMENT APPROXIMATION OF CONVECTION DIFFUSION PROBLEMS USING GRADED MESHES RICARDO G. DURÁN AND ARIEL L. LOMBARDI Abstract. We consider the nmerical approximation of a model convection-diffsion

More information

PARAMETER OPTIMIZATION FOR TAKAGI-SUGENO FUZZY MODELS LESSONS LEARNT

PARAMETER OPTIMIZATION FOR TAKAGI-SUGENO FUZZY MODELS LESSONS LEARNT PAAMETE OPTIMIZATION FO TAKAGI-SUGENO FUZZY MODELS LESSONS LEANT Manfred Männle Inst. for Compter Design and Falt Tolerance Univ. of Karlsrhe, 768 Karlsrhe, Germany maennle@compter.org Brokat Technologies

More information

Multi-lingual Multi-media Information Retrieval System

Multi-lingual Multi-media Information Retrieval System Mlti-lingal Mlti-media Information Retrieval System Shoji Mizobchi, Sankon Lee, Fmihiko Kawano, Tsyoshi Kobayashi, Takahiro Komats Gradate School of Engineering, University of Tokshima 2-1 Minamijosanjima,

More information

A choice relation framework for supporting category-partition test case generation

A choice relation framework for supporting category-partition test case generation Title A choice relation framework for spporting category-partition test case generation Athor(s) Chen, TY; Poon, PL; Tse, TH Citation Ieee Transactions On Software Engineering, 2003, v. 29 n. 7, p. 577-593

More information

Isilon InsightIQ. Version 2.5. User Guide

Isilon InsightIQ. Version 2.5. User Guide Isilon InsightIQ Version 2.5 User Gide Pblished March, 2014 Copyright 2010-2014 EMC Corporation. All rights reserved. EMC believes the information in this pblication is accrate as of its pblication date.

More information

Curves and Surfaces. CS 537 Interactive Computer Graphics Prof. David E. Breen Department of Computer Science

Curves and Surfaces. CS 537 Interactive Computer Graphics Prof. David E. Breen Department of Computer Science Crves and Srfaces CS 57 Interactive Compter Graphics Prof. David E. Breen Department of Compter Science E. Angel and D. Shreiner: Interactive Compter Graphics 6E Addison-Wesley 22 Objectives Introdce types

More information

Real-time mean-shift based tracker for thermal vision systems

Real-time mean-shift based tracker for thermal vision systems 9 th International Conference on Qantitative InfraRed Thermography Jly -5, 008, Krakow - Poland Real-time mean-shift based tracker for thermal vision systems G. Bieszczad* T. Sosnowski** * Military University

More information

C Puzzles The course that gives CMU its Zip! Integer Arithmetic Operations Jan. 25, Unsigned Addition. Visualizing Integer Addition

C Puzzles The course that gives CMU its Zip! Integer Arithmetic Operations Jan. 25, Unsigned Addition. Visualizing Integer Addition 1513 The corse that gies CMU its Zip! Integer Arithmetic Operations Jan. 5, 1 Topics Basic operations Addition, negation, mltiplication Programming Implications Conseqences of oerflow Using shifts to perform

More information

Bits, Bytes, and Integer

Bits, Bytes, and Integer 19.3 Compter Architectre Spring 1 Bits, Bytes, and Integers Nmber Representations Bits, Bytes, and Integer Representing information as bits Bit-level maniplations Integers Representation: nsigned and signed

More information

Computer User s Guide 4.0

Computer User s Guide 4.0 Compter User s Gide 4.0 2001 Glenn A. Miller, All rights reserved 2 The SASSI Compter User s Gide 4.0 Table of Contents Chapter 1 Introdction...3 Chapter 2 Installation and Start Up...5 System Reqirements

More information

Statistical Methods in functional MRI. Standard Analysis. Data Processing Pipeline. Multiple Comparisons Problem. Multiple Comparisons Problem

Statistical Methods in functional MRI. Standard Analysis. Data Processing Pipeline. Multiple Comparisons Problem. Multiple Comparisons Problem Statistical Methods in fnctional MRI Lectre 7: Mltiple Comparisons 04/3/13 Martin Lindqist Department of Biostatistics Johns Hopkins University Data Processing Pipeline Standard Analysis Data Acqisition

More information

Program address space

Program address space Program address space What does the OS loader do? Creates new process Sets p address space/segments Read exectable ile, load instrctions, init global data Mapped rom ile into green segments Libraries loaded

More information

Use Trigonometry with Right Triangles

Use Trigonometry with Right Triangles . a., a.4, 2A.2.A; G.5.D TEKS Use Trigonometr with Right Triangles Before Yo sed the Pthagorean theorem to find lengths. Now Yo will se trigonometric fnctions to find lengths. Wh? So o can measre distances

More information