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E-raamat: Computer Arithmetic and Validity: Theory, Implementation, and Applications illustrated edition [De Gruyter e-raamatud]

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With the intention of improving the accuracy of numerical computing and controlling the quality of the computed results (also known as "validity"), Kulisch (mathematics, U. Karlsruhe) explains how to use advanced computer arithmetic. He explains first concepts concisely, then covers ringoids and vectoids and defines computer arithmetic and interval arithmetic. He covers implementations of arithmetic on computers (floating-point arithmetic and its implementation on a computer, hardware support for interval arithmetic and scalar products and complete arithmetic) and principles of verified computing including sample applications, including the extended interval Newton methods, verified solutions of systems of linear equations and multiple precision arithmetics. Useful for high-level undergraduates and also as a professional reference. Annotation ©2008 Book News, Inc., Portland, OR (booknews.com)
Preface xi
Introduction 1
I Theory of Computer Arithmetic 11
1 First Concepts
12
1.1 Ordered Sets
12
1.2 Complete Lattices and Complete Subnets
17
1.3 Screens and Roundings
23
1.4 Arithmetic Operations and Roundings
34
2 Ringoids and Vectoids
42
2.1 Ringoids
42
2.2 Vectoids
53
3 Definition of Computer Arithmetic
60
3.1 Introduction
60
3.2 Preliminaries
62
3.3 The Traditional Definition of Computer Arithmetic
67
3.4 Definition of Computer Arithmetic by Semimorphisms
69
3.5 A Remark About Roundings
75
3.6 Uniqueness of the Minus Operator
77
3.7 Rounding Near Zero
79
4 Interval Arithmetic
84
4.1 Interval Sets and Arithmetic
84
4.2 Interval Arithmetic Over a Linearly Ordered Set
94
4.3 Interval Matrices
98
4.4 Interval Vectors
103
4.5 Interval Arithmetic on a Screen
106
4.6 Interval Matrices and Interval Vectors on a Screen
114
4.7 Complex Interval Arithmetic
122
4.8 Complex Interval Matrices and Interval Vectors
129
4.9 Extended Interval Arithmetic
134
4.10 Exception-free Arithmetic for Extended Intervals
140
4.11 Extended Interval Arithmetic on the Computer
145
4.12 Implementation of Extended Interval Arithmetic
149
4.13 Comparison Relations and Lattice Operations
150
4.14 Algorithmic Implementation of Interval Multiplication and Division
151
II Implementation of Arithmetic on Computers 153
5 Floating-Point Arithmetic
154
5.1 Definition and Properties of the Real Numbers
154
5.2 Floating-Point Numbers and Roundings
160
5.3 Floating-Point Operations
168
5.4 Subnormal Floating-Point Numbers
177
5.5 On the IEEE Floating-Point Arithmetic Standard
178
6 Implementation of Floating-Point Arithmetic on a Computer
187
6.1 A Brief Review on the Realization of Integer Arithmetic
188
6.2 Introductory Remarks About the Level 1 Operations
196
6.3 Addition and Subtraction
201
6.4 Normalization
206
6.5 Multiplication
207
6.6 Division
208
6.7 Rounding
209
6.8 A Universal Rounding Unit
211
6.9 Overflow and Underflow Treatment
213
6.10 Algorithms Using the Short Accumulator
215
6.11 The Level 2 Operations
222
7 Hardware Support for Interval Arithmetic
233
7.1 Introduction
233
7.2 An Instruction Set for Interval Arithmetic
234
7.2.1 Algebraic Operations
234
7.2.2 Comments on the Algebraic Operations
235
7.2.3 Comparisons and Lattice Operations
236
7.2.4 Comments on Comparisons and Lattice Operations
236
7.3 General Circuitry for Interval Operations and Comparisons
236
7.3.1 Algebraic Operations
236
7.3.2 Comparisons and Result-Selection
240
7.3.3 Alternative Circuitry for Interval Operations and Comparisons
241
7.3.4 Hardware Support for Interval Arithmetic on X86-Processors
243
7.3.5 Accurate Evaluation of Interval Scalar Products
244
8 Scalar Products and Complete Arithmetic
245
8.1 Introduction and Motivation
246
8.2 Historic Remarks
247
8.3 The Ubiquity of the Scalar Product in Numerical Analysis
252
8.4 Implementation Principles
256
8.4.1 Long Adder and Long Shift
257
8.4.2 Short Adder with Local Memory on the Arithmetic Unit
258
8.4.3 Remarks
259
8.4.4 Fast Carry Resolution
261
8.5 Scalar Product Computation Units (SPUs)
263
8.5.1 SPU for Computers with a 32 Bit Data Bus
263
8.5.2 A Coprocessor Chip for the Exact Scalar Product
266
8.5.3 SPU for Computers with a 64 Bit Data Bus
270
8.6 Comments
272
8.6.1 Rounding
272
8.6.2 How Much Local Memory Should be Provided on an SPU?
274
8.7 The Data Format Complete and Complete Arithmetic
275
8.7.1 Low Level Instructions for Complete Arithmetic
277
8.7.2 Complete Arithmetic in High Level Programming Languages
279
8.8 Top Speed Scalar Product Units
282
8.8.1 SPU with Long Adder for 64 Bit Data Word
282
8.8.2 SPU with Long Adder for 32 Bit Data Word
287
8.8.3 A FPGA Coprocessor for the Exact Scalar Product
290
8.8.4 SPU with Short Adder and Complete Register
291
8.8.5 Carry-Free Accumulation of Products in Redundant Arithmetic
297
8.9 Hardware Complete Register Window
297
III Principles of Verified Computing 301
9 Sample Applications
302
9.1 Basic Properties of Interval Mathematics
304
9.1.1 Interval Arithmetic, a Powerful Calculus to Deal with Inequalities
304
9.1.2 Interval Arithmetic as Executable Set Operations
305
9.1.3 Enclosing the Range of Function Values
311
9.1.4 Nonzero Property of a Function, Global Optimization
314
9.2 Differentiation Arithmetic, Enclosures of Derivatives
316
9.3 The Interval Newton Method
324
9.4 The Extended Interval Newton Method
327
9.5 Verified Solution of Systems of Linear Equations
329
9.6 Accurate Evaluation of Arithmetic Expressions
336
9.6.1 Complete Expressions
336
9.6.2 Accurate Evaluation of Polynomials
337
9.6.3 Arithmetic Expressions
341
9.7 Multiple Precision Arithmetics
343
9.7.1 Multiple Precision Floating-Point Arithmetic
344
9.7.2 Multiple Precision Interval Arithmetic
347
9.7.3 Applications
352
9.7.4 Adding an Exponent Part as a Scaling Factor to Complete Arithmetic
354
A Frequently Used Symbols 356
B On Homomorphism 358
Bibliography 359
List of Figures 395
List of Tables 399
Index 401
Ulrich Kulisch, University Karlsruhe.