Physics 331 Introduction to Numerical Techniques in Physics


 Warren Bailey
 10 months ago
 Views:
Transcription
1 Physics 331 Introduction to Numerical Techniques in Physics Instructor: Joaquín Drut Lecture 2
2 Any logistics questions?
3 Today: Number representation Sources of error Note: typo in HW! Two parts c. Call them c1 and c2.
4 Representing numbers on a computer
5 Numbers Our understanding of nature has led us to a description in terms of real and complex numbers... What makes real numbers so special? What are their defining properties?
6 Numbers Our understanding of nature has led us to a description in terms of real and complex numbers... What makes real numbers so special? What are their defining properties? Reals form a field (6 axioms about + and. )
7 Numbers Our understanding of nature has led us to a description in terms of real and complex numbers... What makes real numbers so special? What are their defining properties? Reals form a field (6 axioms about + and. ) Reals are ordered (3 axioms allowing to define > and < )
8 Numbers Our understanding of nature has led us to a description in terms of real and complex numbers... What makes real numbers so special? What are their defining properties? Reals form a field (6 axioms about + and. ) Reals are ordered (3 axioms allowing to define > and < ) Reals are complete (every convergent sequence has a real limit)
9 Numbers Our understanding of nature has led us to a description in terms of real and complex numbers... What makes real numbers so special? What are their defining properties? Reals form a field (6 axioms about + and. ) Reals are ordered (3 axioms allowing to define > and < ) Reals are complete (every convergent sequence has a real limit) Real numbers contain rational as well as irrational numbers. This is a problem! Why?
10 Numbers Our understanding of nature has led us to a description in terms of real and complex numbers... What makes real numbers so special? What are their defining properties? Reals form a field (6 axioms about + and. ) Reals are ordered (3 axioms allowing to define > and < ) Reals are complete (every convergent sequence has a real limit) Real numbers contain rational as well as irrational numbers. This is a problem! Why? How many rationals are there? How many irrationals?
11 Numbers Our understanding of nature has led us to a description in terms of real and complex numbers but computers use a discrete and finite set of numbers. You can already imagine that the range and precision of numbers we can represent will somehow be limited. An engineering decision had to be made regarding how to manage such limitations. But there is more to consider
12 Digital computers In digital computers, everything is ultimately reduced to on and off, or 0 and 1. Numbers on such a computer are encoded in base 2: Base 10 Base bits
13 Decimal and binary representations The decimal representation of numbers is so common that we often forget why we count the way we do. (Why?)
14 Decimal and binary representations The decimal representation of numbers is so common that we often forget why we count the way we do. Decimal Take the number 23, What does this mean in the decimal representation?
15 Decimal and binary representations The decimal representation of numbers is so common that we often forget why we count the way we do. Decimal Take the number 23, What does this mean in the decimal representation? 23, x x x x x x x x 103
16 Decimal and binary representations Binary We only have 1 and 0, and then we move on to the next digit! You may have something like What does this mean?
17 Decimal and binary representations Binary We only have 1 and 0, and then we move on to the next digit! You may have something like What does this mean? Exercise: What number is this in decimal representation? Take 2 minutes and try to figure it out!
18 Decimal and binary representations Binary We only have 1 and 0, and then we move on to the next digit! You may have something like What does this mean? Exercise: What number is this in decimal representation? Take 2 minutes and try to figure it out! Exercise: What number is 21 in binary representation? Take 2 minutes and try to figure it out!
19 On a computer, numbers are represented in terms of bits, but that s not all there is to it
20 Floating point representations Decimal floating point representation (a.k.a. scientific notation) d.ddddddd x 10 p d: 0,1,..,9 mantissa think precision exponent think order of magnitude Example f =
21 Floating point representations Decimal floating point representation (a.k.a. scientific notation) d.ddddddd x 10 p d: 0,1,..,9 mantissa think precision exponent think order of magnitude In general To find the first digit d (from the left), and thus the mantissa as well, divide by the highest power of 10 that is less than the number you want to represent. That power is the exponent p.
22 Floating point representations Binary floating point representation (a.k.a. most of you have never seen this before) 1.bbbbbbb x 2 bbb b: 0,1 mantissa exponent
23 Floating point representations IEEE standard: f = s M B e E There is also quadruple precision! SP sign exponent mantissa
24 Floating point representations IEEE standard: f = s M B e E Overflow 0 Underflow Overflow Note:  There is a largest positive number! Overflow  There is a smallest positive number! Underflow  Only a finite number of exact values!  Interval between numbers depends on exponent!
25 Examples f = f = s M B e E
26 Examples f = f = s M B e E f =
27 Examples f = f = s M B e E f = f =
28 Floating point representations IEEE standard: f = s M B e E There is also quadruple precision! SP sign exponent mantissa What range of values can we represent for the exponent with 8 bits?
29 The exponent e : true exponent f = s M B e E E : bias (127 in SP; 1023 in DP)
30 Sources of error
31 Sources of error when programming... Syntax errors (aka compile errors: code does not even compile) Runtime errors (e.g. segfault; code compiles but fails when running) Numerical errors (more on this soon!) Physics errors (not a programming error: the code does what you want and it does it right... you just have the physics wrong!)
32 Sources of error when programming... Syntax errors (aka compile errors: code does not even compile) Runtime errors (e.g. segfault; code compiles but fails when running) Numerical errors (more on this soon!) Physics errors (not a programming error: the code does what you want and it does it right... you just have the physics wrong!) We will put aside discussions of the model/approach used to represent the physics. These could give... Systematic errors (controlled approximations; e.g. finite volume, finite mesh) Uncontrolled errors (the model may involve an approximation )
33 Sources of numerical error... Roundoff errors (computers have finite precision) Roundoff errors will propagate in iterative methods and potentially produce instabilities and give useless results.
34 Sources of numerical error... Roundoff errors (computers have finite precision) Roundoff errors will propagate in iterative methods and potentially produce instabilities and give useless results. Statistical error (e.g. if your method uses random numbers, like in MC) You just need more statistics  it s almost like a systematic error... but it can be much harder to deal with!
35 Statistical error / signaltonoise problem. Example cosi loghxl x 0 x M x >
36 Statistical error / signaltonoise problem. Example cosi loghxl x 0 x M x >
37 Sources of numerical error... Roundoff errors (computers have finite precision) Roundoff errors will propagate in iterative methods and potentially produce instabilities and give useless results. Statistical error (e.g. if your method uses random numbers, like in MC) You just need more statistics  it s almost like a systematic error... but it can be much harder to deal with!
38 Sources of numerical error... Roundoff errors (computers have finite precision) Roundoff errors will propagate in iterative methods and potentially produce instabilities and give useless results. Statistical error (e.g. if your method uses random numbers, like in MC) You just need more statistics  it s almost like a systematic error... but it can be much harder to deal with! Truncation errors (caused by the numerical method) How do you estimate the value of complicated functions, series expansions, integrals, derivatives...? Should be a systematic error, i.e. something we can treat. Why?
39 Total error Total error = True solution  Numerical solution Total relative error = True solution  Numerical solution True solution Usually we do not know the true solution; that is what we are looking for! The numerical solution can be systematically improved. Ideally the only error left is just the roundoff error. We will always be limited by this!
Floating Point Arithmetic
Floating Point Arithmetic CS 365 FloatingPoint What can be represented in N bits? Unsigned 0 to 2 N 2s Complement 2 N1 to 2 N11 But, what about? very large numbers? 9,349,398,989,787,762,244,859,087,678
More informationScientific Computing. Error Analysis
ECE257 Numerical Methods and Scientific Computing Error Analysis Today s s class: Introduction to error analysis Approximations RoundOff Errors Introduction Error is the difference between the exact solution
More informationIEEE754 floatingpoint
IEEE754 floatingpoint Real and floatingpoint numbers Real numbers R form a continuum  Rational numbers are a subset of the reals  Some numbers are irrational, e.g. π Floatingpoint numbers are an
More informationFloating Point Representation. CS Summer 2008 Jonathan Kaldor
Floating Point Representation CS3220  Summer 2008 Jonathan Kaldor Floating Point Numbers Infinite supply of real numbers Requires infinite space to represent certain numbers We need to be able to represent
More informationData Representation Floating Point
Data Representation Floating Point CSCI 2400 / ECE 3217: Computer Architecture Instructor: David Ferry Slides adapted from Bryant & O Hallaron s slides via Jason Fritts Today: Floating Point Background:
More informationFloating Point Representation in Computers
Floating Point Representation in Computers Floating Point Numbers  What are they? Floating Point Representation Floating Point Operations Where Things can go wrong What are Floating Point Numbers? Any
More information2 Computation with FloatingPoint Numbers
2 Computation with FloatingPoint Numbers 2.1 FloatingPoint Representation The notion of real numbers in mathematics is convenient for hand computations and formula manipulations. However, real numbers
More informationNumber Systems. Binary Numbers. Appendix. Decimal notation represents numbers as powers of 10, for example
Appendix F Number Systems Binary Numbers Decimal notation represents numbers as powers of 10, for example 1729 1 103 7 102 2 101 9 100 decimal = + + + There is no particular reason for the choice of 10,
More informationChapter 03: Computer Arithmetic. Lesson 09: Arithmetic using floating point numbers
Chapter 03: Computer Arithmetic Lesson 09: Arithmetic using floating point numbers Objective To understand arithmetic operations in case of floating point numbers 2 Multiplication of Floating Point Numbers
More informationCS321. Introduction to Numerical Methods
CS31 Introduction to Numerical Methods Lecture 1 Number Representations and Errors Professor Jun Zhang Department of Computer Science University of Kentucky Lexington, KY 40506 0633 August 5, 017 Number
More information3.5 Floating Point: Overview
3.5 Floating Point: Overview Floating point (FP) numbers Scientific notation Decimal scientific notation Binary scientific notation IEEE 754 FP Standard Floating point representation inside a computer
More information1.2 Roundoff Errors and Computer Arithmetic
1.2 Roundoff Errors and Computer Arithmetic 1 In a computer model, a memory storage unit word is used to store a number. A word has only a finite number of bits. These facts imply: 1. Only a small set
More informationFloating Point Numbers
Floating Point Numbers Summer 8 Fractional numbers Fractional numbers fixed point Floating point numbers the IEEE 7 floating point standard Floating point operations Rounding modes CMPE Summer 8 Slides
More informationFloatingPoint Data Representation and Manipulation 198:231 Introduction to Computer Organization Lecture 3
FloatingPoint Data Representation and Manipulation 198:231 Introduction to Computer Organization Instructor: Nicole Hynes nicole.hynes@rutgers.edu 1 Fixed Point Numbers Fixed point number: integer part
More informationCS101 Lecture 04: Binary Arithmetic
CS101 Lecture 04: Binary Arithmetic Binary Number Addition Two s complement encoding Briefly: real number representation Aaron Stevens (azs@bu.edu) 25 January 2013 What You ll Learn Today Counting in binary
More informationFloating Point. The World is Not Just Integers. Programming languages support numbers with fraction
1 Floating Point The World is Not Just Integers Programming languages support numbers with fraction Called floatingpoint numbers Examples: 3.14159265 (π) 2.71828 (e) 0.000000001 or 1.0 10 9 (seconds in
More informationClasses of Real Numbers 1/2. The Real Line
Classes of Real Numbers All real numbers can be represented by a line: 1/2 π 1 0 1 2 3 4 real numbers The Real Line { integers rational numbers nonintegral fractions irrational numbers Rational numbers
More informationFloatingPoint Numbers in Digital Computers
POLYTECHNIC UNIVERSITY Department of Computer and Information Science FloatingPoint Numbers in Digital Computers K. Ming Leung Abstract: We explain how floatingpoint numbers are represented and stored
More informationFloating point. Today! IEEE Floating Point Standard! Rounding! Floating Point Operations! Mathematical properties. Next time. !
Floating point Today! IEEE Floating Point Standard! Rounding! Floating Point Operations! Mathematical properties Next time! The machine model Chris Riesbeck, Fall 2011 Checkpoint IEEE Floating point Floating
More informationFloatingpoint representation
Lecture 34: Floatingpoint representation and arithmetic Floatingpoint representation The notion of real numbers in mathematics is convenient for hand computations and formula manipulations. However,
More informationComputational Methods. Sources of Errors
Computational Methods Sources of Errors Manfred Huber 2011 1 Numerical Analysis / Scientific Computing Many problems in Science and Engineering can not be solved analytically on a computer Numeric solutions
More informationHomework 1 graded and returned in class today. Solutions posted online. Request regrades by next class period. Question 10 treated as extra credit
Announcements Homework 1 graded and returned in class today. Solutions posted online. Request regrades by next class period. Question 10 treated as extra credit Quiz 2 Monday on Number System Conversions
More informationSigned umbers. Sign/Magnitude otation
Signed umbers So far we have discussed unsigned number representations. In particular, we have looked at the binary number system and shorthand methods in representing binary codes. With m binary digits,
More information15213 Recitation 2: Floating Point
15213 Recitation 2: Floating Point 1 Introduction This handout will introduce and test your knowledge of the floating point representation of real numbers, as defined by the IEEE standard. This information
More informationModule 2: Computer Arithmetic
Module 2: Computer Arithmetic 1 B O O K : C O M P U T E R O R G A N I Z A T I O N A N D D E S I G N, 3 E D, D A V I D L. P A T T E R S O N A N D J O H N L. H A N N E S S Y, M O R G A N K A U F M A N N
More informationFloating Point Numbers. Lecture 9 CAP
Floating Point Numbers Lecture 9 CAP 3103 06162014 Review of Numbers Computers are made to deal with numbers What can we represent in N bits? 2 N things, and no more! They could be Unsigned integers:
More informationDeclaration. Fundamental Data Types. Modifying the Basic Types. Basic Data Types. All variables must be declared before being used.
Declaration Fundamental Data Types All variables must be declared before being used. Tells compiler to set aside an appropriate amount of space in memory to hold a value. Enables the compiler to perform
More information4.1 QUANTIZATION NOISE
DIGITAL SIGNAL PROCESSING UNIT IV FINITE WORD LENGTH EFFECTS Contents : 4.1 Quantization Noise 4.2 Fixed Point and Floating Point Number Representation 4.3 Truncation and Rounding 4.4 Quantization Noise
More informationInf2C  Computer Systems Lecture 2 Data Representation
Inf2C  Computer Systems Lecture 2 Data Representation Boris Grot School of Informatics University of Edinburgh Last lecture Moore s law Types of computer systems Computer components Computer system stack
More informationRepresenting and Manipulating Floating Points
Representing and Manipulating Floating Points JinSoo Kim (jinsookim@skku.edu) Computer Systems Laboratory Sungkyunkwan University http://csl.skku.edu The Problem How to represent fractional values with
More informationOn a 64bit CPU. Size/Range vary by CPU model and Word size.
On a 64bit CPU. Size/Range vary by CPU model and Word size. unsigned short x; //range 0 to 65553 signed short x; //range ± 32767 short x; //assumed signed There are (usually) no unsigned floats or doubles.
More informationComputers and programming languages introduction
Computers and programming languages introduction Eugeniy E. Mikhailov The College of William & Mary Lecture 01 Eugeniy Mikhailov (W&M) Practical Computing Lecture 01 1 / 19 Class goals and structure Primary
More informationLecture Notes: FloatingPoint Numbers
Lecture Notes: FloatingPoint Numbers CS227Scientific Computing September 8, 2010 What this Lecture is About How computers represent numbers How this affects the accuracy of computation Positional Number
More informationComputer Numbers and their Precision, I Number Storage
Computer Numbers and their Precision, I Number Storage Learning goal: To understand how the ways computers store numbers lead to limited precision and how that introduces errors into calculations. Learning
More informationIT 1204 Section 2.0. Data Representation and Arithmetic. 2009, University of Colombo School of Computing 1
IT 1204 Section 2.0 Data Representation and Arithmetic 2009, University of Colombo School of Computing 1 What is Analog and Digital The interpretation of an analog signal would correspond to a signal whose
More informationIndependent Representation
Independent Representation 1 Integer magnitude + 1 2 3 4 5 6 7 8 9 0 Float sign sign of exponent mantissa On standard 32 bit machines: INT_MAX = 2147483647 which gives 10 digits of precision, (i.e. the
More informationIEEE Standard 754 Floating Point Numbers
IEEE Standard 754 Floating Point Numbers Steve Hollasch / Last update 2005Feb24 IEEE Standard 754 floating point is the most common representation today for real numbers on computers, including Intelbased
More informationCS429: Computer Organization and Architecture
CS429: Computer Organization and Architecture Dr. Bill Young Department of Computer Sciences University of Texas at Austin Last updated: September 18, 2017 at 12:48 CS429 Slideset 4: 1 Topics of this Slideset
More informationCS 265. Computer Architecture. Wei Lu, Ph.D., P.Eng.
CS 265 Computer Architecture Wei Lu, Ph.D., P.Eng. 1 Part 1: Data Representation Our goal: revisit and reestablish fundamental of mathematics for the computer architecture course Overview: what are bits
More informationIEEE Floating Point Numbers Overview
COMP 40: Machine Structure and Assembly Language Programming (Fall 2015) IEEE Floating Point Numbers Overview Noah Mendelsohn Tufts University Email: noah@cs.tufts.edu Web: http://www.cs.tufts.edu/~noah
More informationFloatingpoint numbers. Phys 420/580 Lecture 6
Floatingpoint numbers Phys 420/580 Lecture 6 Random walk CA Activate a single cell at site i = 0 For all subsequent times steps, let the active site wander to i := i ± 1 with equal probability Random
More informationFloating point. Today. IEEE Floating Point Standard Rounding Floating Point Operations Mathematical properties Next time.
Floating point Today IEEE Floating Point Standard Rounding Floating Point Operations Mathematical properties Next time The machine model Fabián E. Bustamante, Spring 2010 IEEE Floating point Floating point
More informationFloatingpoint Arithmetic. where you sum up the integer to the left of the decimal point and the fraction to the right.
Floatingpoint Arithmetic Reading: pp. 312328 FloatingPoint Representation Nonscientific floating point numbers: A noninteger can be represented as: 2 4 2 3 2 2 2 1 2 0.21 22 23 24 where you sum
More informationFloating Point Puzzles The course that gives CMU its Zip! Floating Point Jan 22, IEEE Floating Point. Fractional Binary Numbers.
class04.ppt 15213 The course that gives CMU its Zip! Topics Floating Point Jan 22, 2004 IEEE Floating Point Standard Rounding Floating Point Operations Mathematical properties Floating Point Puzzles For
More informationSystem Programming CISC 360. Floating Point September 16, 2008
System Programming CISC 360 Floating Point September 16, 2008 Topics IEEE Floating Point Standard Rounding Floating Point Operations Mathematical properties Powerpoint Lecture Notes for Computer Systems:
More informationThe Design and Implementation of a Rigorous. A Rigorous High Precision Floating Point Arithmetic. for Taylor Models
The and of a Rigorous High Precision Floating Point Arithmetic for Taylor Models Department of Physics, Michigan State University East Lansing, MI, 48824 4th International Workshop on Taylor Methods Boca
More informationSection 1.4 Mathematics on the Computer: Floating Point Arithmetic
Section 1.4 Mathematics on the Computer: Floating Point Arithmetic Key terms Floating point arithmetic IEE Standard Mantissa Exponent Roundoff error Pitfalls of floating point arithmetic Structuring computations
More informationECE 2020B Fundamentals of Digital Design Spring problems, 6 pages Exam Two 26 February 2014
Instructions: This is a closed book, closed note exam. Calculators are not permitted. If you have a question, raise your hand and I will come to you. Please work the exam in pencil and do not separate
More informationCharacters, Strings, and Floats
Characters, Strings, and Floats CS 350: Computer Organization & Assembler Language Programming 9/6: pp.8,9; 9/28: Activity Q.6 A. Why? We need to represent textual characters in addition to numbers. Floatingpoint
More informationTable : IEEE Single Format ± a a 2 a 3 :::a 8 b b 2 b 3 :::b 23 If exponent bitstring a :::a 8 is Then numerical value represented is ( ) 2 = (
Floating Point Numbers in Java by Michael L. Overton Virtually all modern computers follow the IEEE 2 floating point standard in their representation of floating point numbers. The Java programming language
More informationComputer Systems C S Cynthia Lee
Computer Systems C S 1 0 7 Cynthia Lee 2 Today s Topics LECTURE: Floating point! Real Numbers and Approximation MATH TIME! Some preliminary observations on approximation We know that some noninteger numbers
More informationSystems I. Floating Point. Topics IEEE Floating Point Standard Rounding Floating Point Operations Mathematical properties
Systems I Floating Point Topics IEEE Floating Point Standard Rounding Floating Point Operations Mathematical properties IEEE Floating Point IEEE Standard 754 Established in 1985 as uniform standard for
More informationGiving credit where credit is due
CSCE 230J Computer Organization Floating Point Dr. Steve Goddard goddard@cse.unl.edu http://cse.unl.edu/~goddard/courses/csce230j Giving credit where credit is due Most of slides for this lecture are based
More informationCS101 Introduction to computing Floating Point Numbers
CS101 Introduction to computing Floating Point Numbers A. Sahu and S. V.Rao Dept of Comp. Sc. & Engg. Indian Institute of Technology Guwahati 1 Outline Need to floating point number Number representation
More informationNumeric Variable Storage Pattern
Numeric Variable Storage Pattern Sreekanth Middela Srinivas Vanam Rahul Baddula Percept Pharma Services, Bridgewater, NJ ABSTRACT This paper presents the Storage pattern of Numeric Variables within the
More informationIntegers and Floating Point
CMPE12 More about Numbers Integers and Floating Point (Rest of Textbook Chapter 2 plus more)" Review: Unsigned Integer A string of 0s and 1s that represent a positive integer." String is X n1, X n2,
More informationNumber Systems and Computer Arithmetic
Number Systems and Computer Arithmetic Counting to four billion two fingers at a time What do all those bits mean now? bits (011011011100010...01) instruction Rformat Iformat... integer data number text
More informationCS61C L10 MIPS Instruction Representation II, Floating Point I (6)
CS61C L1 MIPS Instruction Representation II, Floating Point I (1) inst.eecs.berkeley.edu/~cs61c CS61C : Machine Structures Lecture #1 Instruction Representation II, Floating Point I 2513 There is one
More informationThe type of all data used in a C (or C++) program must be specified
The type of all data used in a C (or C++) program must be specified A data type is a description of the data being represented That is, a set of possible values and a set of operations on those values
More informationComputer Arithmetic Ch 8
Computer Arithmetic Ch 8 ALU Integer Representation Integer Arithmetic FloatingPoint Representation FloatingPoint Arithmetic 1 Arithmetic Logical Unit (ALU) (2) Does all work in CPU (aritmeettislooginen
More informationFloating Point Considerations
Chapter 6 Floating Point Considerations In the early days of computing, floating point arithmetic capability was found only in mainframes and supercomputers. Although many microprocessors designed in the
More informationChapter 2 Float Point Arithmetic. Real Numbers in Decimal Notation. Real Numbers in Decimal Notation
Chapter 2 Float Point Arithmetic Topics IEEE Floating Point Standard Fractional Binary Numbers Rounding Floating Point Operations Mathematical properties Real Numbers in Decimal Notation Representation
More informationComputer Architecture Review. Jo, Heeseung
Computer Architecture Review Jo, Heeseung Computer Abstractions and Technology Jo, Heeseung Below Your Program Application software Written in highlevel language System software Compiler: translates HLL
More informationFloating Point Numbers
Floating Point Floating Point Numbers Mathematical background: tional binary numbers Representation on computers: IEEE floating point standard Rounding, addition, multiplication Kai Shen 1 2 Fractional
More informationWhat Every Programmer Should Know About FloatingPoint Arithmetic
What Every Programmer Should Know About FloatingPoint Arithmetic Last updated: October 15, 2015 Contents 1 Why don t my numbers add up? 3 2 Basic Answers 3 2.1 Why don t my numbers, like 0.1 + 0.2 add
More informationFloating Point. EE 109 Unit 20. Floating Point Representation. Fixed Point
2.1 Floating Point 2.2 EE 19 Unit 2 IEEE 754 Floating Point Representation Floating Point Arithmetic Used to represent very numbers (fractions) and very numbers Avogadro s Number: +6.247 * 1 23 Planck
More informationTruncation Errors. Applied Numerical Methods with MATLAB for Engineers and Scientists, 2nd ed., Steven C. Chapra, McGraw Hill, 2008, Ch. 4.
Chapter 4: Roundoff and Truncation Errors Applied Numerical Methods with MATLAB for Engineers and Scientists, 2nd ed., Steven C. Chapra, McGraw Hill, 2008, Ch. 4. 1 Outline Errors Accuracy and Precision
More informationMidterm Exam Answers Instructor: Randy Shepherd CSCIUA.0201 Spring 2017
Section 1: Multiple choice (select any that apply)  20 points 01. Representing 10 using the 4 byte unsigned integer encoding and using 4 byte two s complements encoding yields the same bit pattern. (a)
More informationMost nonzero floatingpoint numbers are normalized. This means they can be expressed as. x = ±(1 + f) 2 e. 0 f < 1
FloatingPoint Arithmetic Numerical Analysis uses floatingpoint arithmetic, but it is just one tool in numerical computation. There is an impression that floating point arithmetic is unpredictable and
More informationAMTH142 Lecture 10. Scilab Graphs Floating Point Arithmetic
AMTH142 Lecture 1 Scilab Graphs Floating Point Arithmetic April 2, 27 Contents 1.1 Graphs in Scilab......................... 2 1.1.1 Simple Graphs...................... 2 1.1.2 Line Styles........................
More informationIEEE Standard for FloatingPoint Arithmetic: 754
IEEE Standard for FloatingPoint Arithmetic: 754 G.E. Antoniou G.E. Antoniou () IEEE Standard for FloatingPoint Arithmetic: 754 1 / 34 Floating Point Standard: IEEE 754 1985/2008 Established in 1985 (2008)
More informationCS61C : Machine Structures
inst.eecs.berkeley.edu/~cs61c CS61C : Machine Structures Lecture #10 Instruction Representation II, Floating Point I 20051003 Lecturer PSOE, new dad Dan Garcia www.cs.berkeley.edu/~ddgarcia #9 bears
More informationecture 25 Floating Point Friedland and Weaver Computer Science 61C Spring 2017 March 17th, 2017
ecture 25 Computer Science 61C Spring 2017 March 17th, 2017 Floating Point 1 NewSchool Machine Structures (It s a bit more complicated!) Software Hardware Parallel Requests Assigned to computer e.g.,
More informationDigital Computers and Machine Representation of Data
Digital Computers and Machine Representation of Data K. Cooper 1 1 Department of Mathematics Washington State University 2013 Computers Machine computation requires a few ingredients: 1 A means of representing
More informationNumerical Precision. Or, why my numbers aren t numbering right. 1 of 15
Numerical Precision Or, why my numbers aren t numbering right 1 of 15 What s the deal? Maybe you ve seen this #include int main() { float val = 3.6f; printf( %.20f \n, val); Print a float with
More informationChapter 2 Bits, Data Types, and Operations
Chapter 2 Bits, Data Types, and Operations How do we represent data in a computer? At the lowest level, a computer is an electronic machine. works by controlling the flow of electrons Easy to recognize
More informationBinary Addition & Subtraction. Unsigned and Sign & Magnitude numbers
Binary Addition & Subtraction Unsigned and Sign & Magnitude numbers Addition and subtraction of unsigned or sign & magnitude binary numbers by hand proceeds exactly as with decimal numbers. (In fact this
More informationData Representation and Introduction to Visualization
Data Representation and Introduction to Visualization Massimo Ricotti ricotti@astro.umd.edu University of Maryland Data Representation and Introduction to Visualization p.1/18 VISUALIZATION Visualization
More information4 Operations On Data 4.1. Foundations of Computer Science Cengage Learning
4 Operations On Data 4.1 Foundations of Computer Science Cengage Learning Objectives After studying this chapter, the student should be able to: List the three categories of operations performed on data.
More informationFloating Point. CSC207 Fall 2017
Floating Point CSC207 Fall 2017 Ariane 5 Rocket Launch Ariane 5 rocket explosion In 1996, the European Space Agency s Ariane 5 rocket exploded 40 seconds after launch. During conversion of a 64bit to
More informationFloatingPoint Arithmetic
FloatingPoint Arithmetic if ((A + A)  A == A) { SelfDestruct() } Reading: Study Chapter 3. L12 Multiplication 1 Approximating Real Numbers on Computers Thus far, we ve entirely ignored one of the most
More informationNumerical Methods in Physics. Lecture 1 Intro & IEEE Variable Types and Arithmetic
Variable types Numerical Methods in Physics Lecture 1 Intro & IEEE Variable Types and Arithmetic Pat Scott Department of Physics, Imperial College November 1, 2016 Slides available from http://astro.ic.ac.uk/pscott/
More information4 Operations On Data 4.1. Foundations of Computer Science Cengage Learning
4 Operations On Data 4.1 Foundations of Computer Science Cengage Learning Objectives After studying this chapter, the student should be able to: List the three categories of operations performed on data.
More informationDr. Chuck Cartledge. 3 June 2015
Miscellanea 8224 Revisited Break 1.5 1.6 Conclusion References Backup slides CSC205 Computer Organization Lecture #002 Section 1.5 Dr. Chuck Cartledge 3 June 2015 1/30 Table of contents I 5 1.6 1 Miscellanea
More informationFloating Point. What can be represented in N bits? 0 to 2N1. 9,349,398,989,787,762,244,859,087, x 1067
MIPS Floating Point Operations Cptr280 Dr Curtis Nelson Floating Point What can be represented in N bits? Unsigned 2 s Complement 0 to 2N12N1 to 2N11 But, what about Very large numbers? 9,349,398,989,787,762,244,859,087,678
More informationThe Size of the Cantor Set
The Size of the Cantor Set Washington University Math Circle November 6, 2016 In mathematics, a set is a collection of things called elements. For example, {1, 2, 3, 4}, {a,b,c,...,z}, and {cat, dog, chicken}
More informationComputational Mathematics: Models, Methods and Analysis. Zhilin Li
Computational Mathematics: Models, Methods and Analysis Zhilin Li Chapter 1 Introduction Why is this course important (motivations)? What is the role of this class in the problem solving process using
More information1. NUMBER SYSTEMS USED IN COMPUTING: THE BINARY NUMBER SYSTEM
1. NUMBER SYSTEMS USED IN COMPUTING: THE BINARY NUMBER SYSTEM 1.1 Introduction Given that digital logic and memory devices are based on two electrical states (on and off), it is natural to use a number
More informationCHAPTER 5 Computer Arithmetic and RoundOff Errors
CHAPTER 5 Computer Arithmetic and RoundOff Errors In the two previous chapters we have seen how numbers can be represented in the binary numeral system and how this is the basis for representing numbers
More informationChapter 3. Fundamental Data Types
Chapter 3. Fundamental Data Types ByoungTak Zhang TA: Hanock Kwak Biointelligence Laboratory School of Computer Science and Engineering Seoul National Univertisy http://bi.snu.ac.kr Variable Declaration
More informationCoprocessor Math Processor. Richa Upadhyay Prabhu. NMIMS s MPSTME February 9, 2016
8087 Math Processor Richa Upadhyay Prabhu NMIMS s MPSTME richa.upadhyay@nmims.edu February 9, 2016 Introduction Need of Math Processor: In application where fast calculation is required Also where there
More informationIn this article, we present and analyze
[exploratory DSP] Manuel Richey and Hossein Saiedian Compressed Two s Complement Data s Provide Greater Dynamic Range and Improved Noise Performance In this article, we present and analyze a new family
More informationVHDL IMPLEMENTATION OF IEEE 754 FLOATING POINT UNIT
VHDL IMPLEMENTATION OF IEEE 754 FLOATING POINT UNIT Ms. Anjana Sasidharan Student, Vivekanandha College of Engineering for Women, Namakkal, Tamilnadu, India. Abstract IEEE754 specifies interchange and
More informationThe Sign consists of a single bit. If this bit is '1', then the number is negative. If this bit is '0', then the number is positive.
IEEE 754 Standard  Overview Frozen Content Modified by on 13Sep2017 Before discussing the actual WB_FPU  Wishbone Floating Point Unit peripheral in detail, it is worth spending some time to look at
More informationAdministrivia. CMSC 216 Introduction to Computer Systems Lecture 24 Data Representation and Libraries. Representing characters DATA REPRESENTATION
Administrivia CMSC 216 Introduction to Computer Systems Lecture 24 Data Representation and Libraries Jan Plane & Alan Sussman {jplane, als}@cs.umd.edu Project 6 due next Friday, 12/10 public tests posted
More informationQUIZ ch.1. 1 st generation 2 nd generation 3 rd generation 4 th generation 5 th generation Rock s Law Moore s Law
QUIZ ch.1 1 st generation 2 nd generation 3 rd generation 4 th generation 5 th generation Rock s Law Moore s Law Integrated circuits Density of silicon chips doubles every 1.5 yrs. Multicore CPU Transistors
More informationCO Computer Architecture and Programming Languages CAPL. Lecture 15
CO20320241 Computer Architecture and Programming Languages CAPL Lecture 15 Dr. Kinga Lipskoch Fall 2017 How to Compute a Binary Float Decimal fraction: 8.703125 Integral part: 8 1000 Fraction part: 0.703125
More informationArithmetic. Chapter 3 Computer Organization and Design
Arithmetic Chapter 3 Computer Organization and Design Addition Addition is similar to decimals 0000 0111 + 0000 0101 = 0000 1100 Subtraction (negate) 0000 0111 + 1111 1011 = 0000 0010 Over(under)flow For
More informationPractical Numerical Methods in Physics and Astronomy. Lecture 1 Intro & IEEE Variable Types and Arithmetic
Practical Numerical Methods in Physics and Astronomy Lecture 1 Intro & IEEE Variable Types and Arithmetic Pat Scott Department of Physics, McGill University January 16, 2013 Slides available from http://www.physics.mcgill.ca/
More information