Binary Numbers Bob Brown Information Technology Department Southern Polytechnic State University
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Representing Information in English Until 1598
In the twenty-first century, digital computers are everywhere. You al- most certainly have one with you now, although you may call it a “phone.” You are more likely to be reading this book on a digital device than on paper. We do so many things with our digital devices that we may forget the original purpose: computation. When Dr. Howard Figure 1-1 Aiken was in charge of the huge, Howard Aiken, center, and Grace Murray Hopper, mechanical Harvard Mark I calcu- on Aiken’s left, with other members of the Bureau of Ordnance Computation Project, in front of the lator during World War II, he Harvard Mark I computer at Harvard University, wasn’t happy unless the machine 1944. was “making numbers,” that is, U.S. Department of Defense completing the numerical calculations needed for the war effort. We still use computers for purely computational tasks, to make numbers. It may be less ob- vious, but the other things for which we use computers today are, underneath, also computational tasks. To make that phone call, your phone, really a com- puter, converts an electrical signal that’s an analog of your voice to numbers, encodes and compresses them, and passes them onward to a cellular radio which it itself is controlled by numbers. Numbers are fundamental to our digital devices, and so to understand those digital devices, we have to understand the numbers that flow through them. 1.1 Numbers as Abstractions It is easy to suppose that as soon as humans began to accumulate possessions, they wanted to count them and make a record of the count. -
ACP Course07
Applied Computer Programming Representation of Numbers. Bitwise Operators Course 07 Lect.eng. Adriana ALBU, PhD Politehnica University Timisoara Internal representation • All data, of any type, processed by a computer must have the same fundamental representation • In order to work correctly with these data, a programmer should understand: – the representation of numbers and their memory storage – the fundamental manner a computer operates with numbers (bitwise operations) Representation of numbers Binary Octal Hexadecimal Representation of numbers • Most of our programs don’t need concern regarding operations at the bit level • We’re free to think in bytes, or integers and doubles, or even higher level data types composed of a combination of these • But there are times when we'd like to be able to go to the level of an individual bit Representation of numbers • Any value (variable or constant) that is processed by our programs needs a memory space and it has a memory representation (sequence of bits) • Bit – unit of data storage – may have one of two values: 0 or 1 – usually is not individually addressable • Byte – unit of addressable data – in all usual computer architectures it contains 8 bits (CHAR_BIT from limits.h specifies its dimension) Representation of numbers • The byte is the lowest level at which we can access data; there's no "bit" type, and we can't ask for an individual bit • In fact, we can't even perform operations on a single bit – every bitwise operator will be applied to, at a minimum, an entire byte at a time • This -
On Two Conversion Methods of Decimal-To-Binary
On Two Conversion Methods of Decimal-to-Binary Zhengjun Cao Department of Mathematics, Shanghai University, Shanghai, China. [email protected] Abstract Decimal-to-binary conversion is important to modern binary computers. The classical method to solve this problem is based on division operation. In this paper, we investigate a decimal-to-binary conversion method based on addition operation. The method is very easily implemented by software. The cost analysis shows that the latter is more preferable than the classical method. Thus the current Input/Output translation hardware to convert between the internal digit pairs and the external standard BCD codes can be reasonably removed. Keywords. Decimal-to-binary conversion; division operation; addition operation. 1 Introduction IF OUR ANCESTORS had invented arithmetic by counting with their two fists or their eight fingers, instead of their ten “digits”, we would never have to worry about writing binary-decimal conversion routines. — Donald E. Knuth arXiv:1308.0555v1 [cs.OH] 1 Aug 2013 We know a digit a ∈ {0, 1, · · · , 9} received from a numeric key on a keyboard (see Picture 1) is represented as a string of 4 bits. The mechanism is usually referred to as Binary Coded Decimal (BCD for short). For instance, the digit 9 is represented as 1001 . When we input the integer 79 using numeric keys ‘7’ and ‘9’, it is first represented as two strings 0111 1001 . We here omit the other leftmost bits in each byte which represent numeric type or sign. The two strings then will be converted into the resulting binary representation 1001111 . In 1988. -
Multi–Precision Math
Multi–Precision Math Tom St Denis Algonquin College Mads Rasmussen Open Communications Security Greg Rose QUALCOMM Australia August 29, 2017 This text has been placed in the public domain. This text corresponds to the v0.39 release of the LibTomMath project. This text is formatted to the international B5 paper size of 176mm wide by 250mm tall using the LATEX book macro package and the Perl booker package. Contents 1 Introduction 1 1.1 MultiplePrecisionArithmetic . 1 1.1.1 WhatisMultiplePrecisionArithmetic? . 1 1.1.2 The Need for Multiple Precision Arithmetic . 1 1.1.3 BenefitsofMultiplePrecisionArithmetic . 3 1.2 PurposeofThisText......................... 4 1.3 DiscussionandNotation . 5 1.3.1 Notation............................ 5 1.3.2 PrecisionNotation . 5 1.3.3 AlgorithmInputsandOutputs . 6 1.3.4 MathematicalExpressions . 6 1.3.5 WorkEffort.......................... 7 1.4 Exercises ............................... 7 1.5 IntroductiontoLibTomMath . 9 1.5.1 WhatisLibTomMath?. 9 1.5.2 GoalsofLibTomMath . 9 1.6 ChoiceofLibTomMath . 10 1.6.1 CodeBase........................... 10 1.6.2 APISimplicity ........................ 11 1.6.3 Optimizations......................... 11 1.6.4 PortabilityandStability . 11 1.6.5 Choice............................. 12 2 Getting Started 13 2.1 LibraryBasics ............................ 13 2.2 WhatisaMultiplePrecisionInteger? . 14 2.2.1 The mp intStructure .................... 15 iii 2.3 ArgumentPassing .......................... 17 2.4 ReturnValues............................. 18 2.5 InitializationandClearing . 19 2.5.1 Initializing an mp int .................... 19 2.5.2 Clearing an mp int...................... 22 2.6 MaintenanceAlgorithms . 24 2.6.1 Augmenting an mp int’sPrecision . 24 2.6.2 Initializing Variable Precision mp ints ........... 27 2.6.3 Multiple Integer Initializations and Clearings . 29 2.6.4 ClampingExcessDigits . 31 3 Basic Operations 35 3.1 Introduction............................. -
Multi–Precision Math
Multi–Precision Math Tom St Denis Algonquin College Mads Rasmussen Open Communications Security Greg Rose QUALCOMM Australia March 10, 2007 This text has been placed in the public domain. This text corresponds to the v0.39 release of the LibTomMath project. Tom St Denis 111 Banning Rd Ottawa, Ontario K2L 1C3 Canada Phone: 1-613-836-3160 Email: [email protected] This text is formatted to the international B5 paper size of 176mm wide by 250mm tall using the LATEX book macro package and the Perl booker package. Contents 1 Introduction 1 1.1 Multiple Precision Arithmetic . 1 1.1.1 What is Multiple Precision Arithmetic? . 1 1.1.2 The Need for Multiple Precision Arithmetic . 1 1.1.3 Benefits of Multiple Precision Arithmetic . 3 1.2 PurposeofThisText......................... 4 1.3 DiscussionandNotation . 5 1.3.1 Notation............................ 5 1.3.2 PrecisionNotation . 5 1.3.3 Algorithm Inputs and Outputs . 6 1.3.4 MathematicalExpressions. 6 1.3.5 WorkEffort.......................... 7 1.4 Exercises ............................... 7 1.5 IntroductiontoLibTomMath . 9 1.5.1 WhatisLibTomMath?. 9 1.5.2 GoalsofLibTomMath . 9 1.6 ChoiceofLibTomMath .. .. .. .. .. .. .. .. .. .. 10 1.6.1 CodeBase........................... 10 1.6.2 APISimplicity ........................ 11 1.6.3 Optimizations.. .. .. .. .. .. .. .. .. .. .. 11 1.6.4 Portability and Stability . 11 1.6.5 Choice............................. 12 2 Getting Started 13 2.1 LibraryBasics ............................ 13 2.2 WhatisaMultiplePrecisionInteger? . 14 2.2.1 The mp intStructure .................... 15 iii 2.3 ArgumentPassing .......................... 17 2.4 ReturnValues............................. 18 2.5 InitializationandClearing . 19 2.5.1 Initializing an mp int .................... 19 2.5.2 Clearing an mp int...................... 21 2.6 MaintenanceAlgorithms .