Chapter 3 of Computer Organization and Architecture by Patterson and Hennessy, often referred to as the "Computer Organization and Design" (COD) book, focuses on Arithmetic for Computers. This chapter delves into the fundamental operations of arithmetic that are performed by computer hardware, including integer and floating-point arithmetic, and explores how these operations are implemented in digital systems. It bridges the gap between mathematical concepts and their practical implementation in computer hardware, providing a detailed understanding of how arithmetic operations are executed at the hardware level.
The chapter begins with a discussion of integer arithmetic, which forms the basis of most computations in a computer. It explains how binary addition, subtraction, multiplication, and division are performed using logic gates and circuits. The authors introduce the concept of the ALU (Arithmetic Logic Unit), a critical component of the CPU that performs these arithmetic and logical operations. They explain how binary addition is carried out using half-adders and full-adders, and how subtraction is implemented using two's complement representation, a method that simplifies the design of subtraction circuits by allowing it to be performed using addition.
The chapter then moves on to multiplication and division, which are more complex operations. It describes algorithms such as the shift-and-add method for multiplication and the restoring division algorithm for division. These algorithms are implemented using a combination of shifting, addition, and subtraction operations, and the authors provide detailed examples to illustrate how they work. They also discuss the trade-offs between hardware complexity and performance, highlighting how modern processors optimize these operations using techniques like Booth's algorithm for multiplication.
A significant portion of the chapter is dedicated to floating-point arithmetic, which is essential for representing and manipulating real numbers in computers. The authors explain the IEEE 754 floating-point standard, which defines the representation of floating-point numbers, including single-precision (32-bit) and double-precision (64-bit) formats. They discuss the components of a floating-point number: the sign bit, exponent, and mantissa (or significand), and how these components are used to represent a wide range of values with varying precision.
The chapter also covers the challenges of floating-point arithmetic, such as rounding errors, overflow, and underflow, and explains how these issues are managed in hardware and software. The authors provide examples of floating-point addition, subtraction, multiplication, and division, demonstrating how these operations are performed step-by-step. They also discuss the importance of precision and accuracy in scientific and engineering applications, where floating-point arithmetic is extensively used.
To reinforce the concepts, the chapter includes practical