TL;DR: A class of division methods best suited for use in digital computers with facilities for floating point arithmetic by considering the nature of each quotient digit as generated during the division process is described.
Abstract: This paper describes a class of division methods best suited for use in digital computers with facilities for floating point arithmetic. The division methods may be contrasted with conventional division procedures by considering the nature of each quotient digit as generated during the division process. In restoring division, each quotient digit has one of the values 0,1, . . . , r ?1, for an arbitrary integer radix r. In nonrestoring division, each quotient digit has one of the values ?(r?1),. . ., ?1, +1, . . ., +(r?1). For the division methods described here, each quotient digit has one of the values ?n, ?(n?1), . . ., ?1, 0, 1, . . . n?1, n, where n is an integer such that ?(r ?1)?n?r?1. A method for serial conversion of the quotient digits to conventional (restoring) form is given. Examples of new division procedures for radix 4 and radix 10 are given.
TL;DR: The author's research focused on the development of a number representation system that allowed for the addition and subtraction of numbers up to and including the number of bits in a discrete-time system.
Abstract: Preface. About the Authors. 1. Introduction. 1.1 Number Representation. 1.2 Algorithms. 1.3 Hardware Platforms. 1.4 Hardware-Software Partitioning. 1.5 Software Generation. 1.6 Synthesis. 1.7 A First Example. 1.7.1 Specification. 1.7.2 Number Representation. 1.7.3 Algorithms. 1.7.4 Hardware Platform. 1.7.5 Hardware-Software Partitioning. 1.7.6 Program Generation. 1.7.7 Synthesis. 1.7.8 Prototype. 1.8 Bibliography. 2. Mathematical Background. 2.1 Number Theory. 2.1.1 Basic Definitions. 2.1.2 Euclidean Algorithms. 2.1.3 Congruences. 2.2 Algebra. 2.2.1 Groups. 2.2.2 Rings. 2.2.3 Fields. 2.2.4 Polynomial Rings. 2.2.5 Congruences of Polynomial. 2.3 Function Approximation. 2.4 Bibliography. 3. Number Representation. 3.1 Natural Numbers. 3.1.1 Weighted Systems. 3.1.2 Residue Number System. 3.2 Integers. 3.2.1 Sign-Magnitude Representation. 3.2.2 Excess-E Representation. 3.2.3 B's Complement Representation. 3.2.4 Booth's Encoding. 3.3 Real Numbers. 3.4 Bibliography. 4. Arithmetic Operations: Addition and Subtraction. 4.1 Addition of Natural Numbers. 4.1.1 Basic Algorithm. 4.1.2 Faster Algorithms. 4.1.3 Long-Operand Addition. 4.1.4 Multioperand Addition. 4.1.5 Long-Multioperand Addition. 4.2 Subtraction of Natural Numbers. 4.3 Integers. 4.3.1 B's Complement Addition. 4.3.2 B's Complement Sign Change. 4.3.3 B's Complement Subtraction. 4.3.4 B's Complement Overflow Detection. 4.3.5 Excess-E Addition and Subtraction. 4.3.6 Sign-Magnitude Addition and Subtraction. 4.4 Bibliography. 5. Arithmetic Operations: Multiplication. 5.1 Natural Numbers Multiplication. 5.1.1 Introduction. 5.1.2 Shift and Add Algorithms. 5.1.2.1 Shift and Add 1. 5.1.2.2 Shift and Add 2. 5.1.2.3 Extended Shift and Add Algorithm: XY t C t D. 5.1.2.4 Cellular Shift and Add. 5.1.3 Long-Operand Algorithm. 5.2 Integers. 5.2.1 B's Complement Multiplication. 5.2.1.1 Mod Bntm B's Complement Multiplication. 5.2.1.2 Signed Shift and Add. 5.2.1.3 Postcorrection B's Complement Multiplication. 5.2.2 Postcorrection 2's Complement Multiplication. 5.2.3 Booth Multiplication for Binary Numbers. 5.2.3.1 Booth-r Algorithms. 5.2.3.2 Per Gelosia Signed-Digit Algorithm. 5.2.4 Booth Multiplication for Base-B Numbers (Booth-r Algorithm in Base B). 5.3 Squaring. 5.3.1 Base-B Squaring. 5.3.1.1 Cellular Carry-Save Squaring Algorithm. 5.3.2 Base-2 Squaring. 5.4 Bibliography. 6 Arithmetic Operations: Division. 6.1 Natural Numbers. 6.2 Integers. 6.2.1 General Algorithm. 6.2.2 Restoring Division Algorithm. 6.2.3 Base-2 Nonrestoring Division Algorithm. 6.2.4 SRT Radix-2 Division. 6.2.5 SRT Radix-2 Division with Stored-Carry Encoding. 6.2.6 P-D Diagram. 6.2.7 SRT-4 Division. 6.2.8 Base-B Nonrestoring Division Algorithm. 6.3 Convergence (Functional Iteration) Algorithms. 6.3.1 Introduction. 6.3.2 Newton-Raphson Iteration Technique. 6.3.3 MacLaurin Expansion-Goldschmidt's Algorithm. 6.4 Bibliography. 7. Other Arithmetic Operations. 7.1 Base Conversion. 7.2 Residue Number System Conversion. 7.2.1 Introduction. 7.2.2 Base-B to RNS Conversion. 7.2.3 RNS to Base-B Conversion. 7.3 Logarithmic, Exponential, and Trigonometric Functions. 7.3.1 Taylor-MacLaurin Series. 7.3.2 Polynomial Approximation. 7.3.3 Logarithm and Exponential Functions Approximation by Convergence Methods. 7.3.3.1 Logarithm Function Approximation by Multiplicative Normalization. 7.3.3.2 Exponential Function Approximation by Additive Normalization. 7.3.4 Trigonometric Functions-CORDIC Algorithms. 7.4 Square Rooting. 7.4.1 Digit Recurrence Algorithm-Base-B Integers. 7.4.2 Restoring Binary Shift-and-Subtract Square Rooting Algorithm. 7.4.3 Nonrestoring Binary Add-and-Subtract Square Rooting Algorithm. 7.4.4 Convergence Method-Newton-Raphson. 7.5 Bibliography. 8. Finite Field Operations. 8.1 Operations in Zm. 8.1.1 Addition. 8.1.2 Subtraction. 8.1.3 Multiplication. 8.1.3.1 Multiply and Reduce. 8.1.3.2 Modified Shift-and-Add Algorithm. 8.1.3.3 Montgomery Multiplication. 8.1.3.4 Specific Ring. 8.1.4 Exponentiation. 8.2 Operations in GF(p). 8.3 Operations in Zp[x]/f (x). 8.3.1 Addition and Subtraction. 8.3.2 Multiplication. 8.4 Operations in GF(pn). 8.5 Bibliography. Appendix 8.1 Computation of fki. 9 Hardware Platforms. 9.1 Design Methods for Electronic Systems. 9.1.1 Basic Blocks of Integrated Systems. 9.1.2 Recurring Topics in Electronic Design. 9.1.2.1 Design Challenge: Optimizing Design Metrics. 9.1.2.2 Cost in Integrated Circuits. 9.1.2.3 Moore's Law. 9.1.2.4 Time-to-Market. 9.1.2.5 Performance Metric. 9.1.2.6 The Power Dimension. 9.2 Instruction Set Processors. 9.2.1 Microprocessors. 9.2.2 Microcontrollers. 9.2.3 Embedded Processors Everywhere. 9.2.4 Digital Signal Processors. 9.2.5 Application-Specific Instruction Set Processors. 9.2.6 Programming Instruction Set Processors. 9.3 ASIC Designs. 9.3.1 Full-Custom ASIC. 9.3.2 Semicustom ASIC. 9.3.2.1 Gate-Array ASIC. 9.3.2.2 Standard-Cell-Based ASIC. 9.3.3 Design Flow in ASIC. 9.4 Programmable Logic. 9.4.1 Programmable Logic Devices (PLDs). 9.4.2 Field Programmable Gate Array (FPGA). 9.4.2.1 Why FPGA? A Short Historical Survey. 9.4.2.2 Basic FPGA Concepts. 9.4.3 XilinxTM Specifics. 9.4.3.1 Configurable Logic Blocks (CLBs). 9.4.3.2 Input/Output Blocks (IOBs). 9.4.3.3 RAM Blocks. 9.4.3.4 Programmable Routing. 9.4.3.5 Arithmetic Resources in Xilinx FPGAs. 9.4.4 FPGA Generic Design Flow. 9.5 Hardware Description Languages (HDLs). 9.5.1 Today's and Tomorrow's HDLs. 9.6 Further Readings. 9.7 Bibliography. 10. Circuit Synthesis: General Principles. 10.1 Resources. 10.2 Precedence Relation and Scheduling. 10.3 Pipeline. 10.4 Self-Timed Circuits. 10.5 Bibliography. 11 Adders and Subtractors. 11.1 Natural Numbers. 11.1.1 Basic Adder (Ripple-Carry Adder). 11.1.2 Carry-Chain Adder. 11.1.3 Carry-Skip Adder. 11.1.4 Optimization of Carry-Skip Adders. 11.1.5 Base-Bs Adder. 11.1.6 Carry-Select Adder. 11.1.7 Optimization of Carry-Select Adders. 11.1.8 Carry-Lookahead Adders (CLAs). 11.1.9 Prefix Adders. 11.1.10 FPGA Implementation of Adders. 11.1.10.1 Carry-Chain Adders. 11.1.10.2 Carry-Skip Adders. 11.1.10.3 Experimental Results. 11.1.11 Long-Operand Adders. 11.1.12 Multioperand Adders. 11.1.12.1 Sequential Multioperand Adders. 11.1.12.2 Combinational Multioperand Adders. 11.1.12.3 Carry-Save Adders. 11.1.12.4 Parallel Counters. 11.1.13 Subtractors and Adder-Subtractors. 11.1.14 Termination Detection. 11.1.15 FPGA Implementation of the Termination Detection. 11.2 Integers. 11.2.1 B's Complement Adders and Subtractors. 11.2.2 Excess-E Adders and Subtractors. 11.2.3 Sign-Magnitude Adders and Subtractors. 11.3 Bibliography. 12 Multipliers. 12.1 Natural Numbers. 12.1.1 Basic Multiplier. 12.1.2 Sequential Multipliers. 12.1.3 Cellular Multiplier Arrays. 12.1.3.1 Ripple-Carry Multiplier. 12.1.3.2 Carry-Save Multiplier. 12.1.3.3 Figures of Merit. 12.1.4 Multipliers Based on Dissymmetric Br Bs Cells. 12.1.5 Multipliers Based on Multioperand Adders. 12.1.6 Per Gelosia Multiplication Arrays. 12.1.6.1 Introduction. 12.1.6.2 Adding Tree for Base-B Partial Products. 12.1.7 FPGA Implementation of Multipliers. 12.2 Integers. 12.2.1 B's Complement Multipliers. 12.2.2 Booth Multipliers. 12.2.2.1 Booth-1 Multiplier. 12.2.2.2 Booth-2 Multiplier. 12.2.2.3 Signed-Digit Multiplier. 12.2.3 FPGA Implementation of the Booth-1 Multiplier. 12.3 Bibliography. 13. Dividers. 13.1 Natural Numbers. 13.2 Integers. 13.2.1 Base-2 Nonrestoring Divider. 13.2.2 Base-B Nonrestoring Divider. 13.2.3 SRT Dividers. 13.2.3.1 SRT-2 Divider. 13.2.3.2 SRT-2 Divider with Carry-Save Computation of the Remainder. 13.2.3.3 FPGA Implementation of the Carry-Save SRT-2 Divider. 13.2.4 SRT-4 Divider. 13.2.5 Convergence Dividers. 13.2.5.1 Newton-Raphson Divider. 13.2.5.2 Goldschmidt Divider. 13.2.5.3 Comparative Data Between Newton-Raphson (NR) and Goldschmidt (G) Implementations. 13.3 Bibliography. 14 Other Arithmetic Operators. 14.1 Base Conversion. 14.1.1 General Base Conversion. 14.1.2 BCD to Binary Converter. 14.1.2.1 Nonrestoring 2p Subtracting Implementation. 14.1.2.2 Shift-and-Add BCD to Binary Converter. 14.1.3 Binary to BCD Converter. 14.1.4 Base-B to RNS Converter. 14.1.5 CRT RNS to Base-B Converter. 14.1.6 RNS to Mixed-Radix System Converter. 14.2 Polynomial Computation Circuits. 14.3 Logarithm Operator. 14.4 Exponential Operator. 14.5 Sine and Cosine Operators. 14.6 Square Rooters. 14.6.1 Restoring Shift-and-Subtract Square Rooter (Naturals). 14.6.2 Nonrestoring Shift-and-Subtract Square Rooter (Naturals). 14.6.3 Newton-Raphson Square Rooter (Naturals). 14.7 Bibliography. 15. Circuits for Finite Field Operations. 15.1 Operations in Zm. 15.1.1 Adders and Subtractors. 15.1.2 Multiplication. 15.1.2.1 Multiply and Reduce. 15.1.2.2 Shift and Add. 15.1.2.3 Montgomery Multiplication. 15.1.2.4 Modulo (Bk2c) Reduction. 15.1.2.5 Exponentiation. 15.2 Inversion in GF(p). 15.3 Operations in Zp[x]/f (x). 15.4 Inversion in GF(pn). 15.5 Bibliography. 16. Floating-Point Unit. 16.1 Floating-Point System Definition. 16.2 Arithmetic Operations. 16.2.1 Addition of Positive Numbers. 16.2.2 Difference of Positive Numbers. 16.2.3 Addition and Subtraction. 16.2.4 Multiplication. 16.2.5 Division. 16.2.6 Square Root. 16.3 Rounding Schemes. 16.4 Guard Digits. 16.5 Adder-Subtractor. 16.5.1 Alignment. 16.5.2 Additions. 16.5.3 Normalization. 16.5.4 Rounding. 16.6 Multiplier. 16.7 Divider. 16.8 Square Root. 16.9 Comments. 16.10 Bibliography. Index.
TL;DR: In order to avoid the time delays associated with linearly convergent division based on subtraction, other iterative schemes can be used based on series expansion of the reciprocal, multiplicative sequence, or additive sequence convergent to the quotient.
Abstract: In order to avoid the time delays associated with linearly convergent division based on subtraction, other iterative schemes can be used. These are based on 1) series expansion of the reciprocal, 2) multiplicative sequence, or 3) additive sequence convergent to the quotient. These latter techniques are based on finding the root of an arbitrary function at either the quotient or reciprocal value. A Newton-Raphson iteration or root finding iteration can be used.
TL;DR: In this paper, a mixed method is proposed which combines the factor division algorithm with the eigen spectrum analysis for deriving reduced order models of high-order linear time invariant systems.
TL;DR: An algorithm for GF(2/sup m/) multiplication/division is presented and a new, more generalized definition of duality is proposed and the bit-serial Berlekamp multiplier is derived and shown to be a specific case of a more general class of multipliers.
Abstract: In this paper an algorithm for GF(2/sup m/) multiplication/division is presented and a new, more generalized definition of duality is proposed. From these the bit-serial Berlekamp multiplier is derived and shown to be a specific case of a more general class of multipliers. Furthermore, it is shown that hardware efficient, bit-parallel dual basis multipliers can also be designed. These multipliers have a regular structure, are easily extended to different GF(2/sup m/) and hence suitable for VLSI implementations. As in the bit-serial case these bit-parallel multipliers can also be hardwired to carry out constant multiplication. These constant multipliers have reduced hardware requirements and are also simple to design. In addition, the multiplication/division algorithm also allows a bit-serial systolic finite field divider to be designed. This divider is modular, independent of the defining irreducible polynomial for the field, easily expanded to different GF(2/sup m/) and its longest delay path is independent of m.