### Unit 4: Computer Arithmetic

In this unit, you will build upon your knowledge of computer instructions and digital logic design to discuss the role of computer arithmetic in hardware design. We will also discuss the designs of adders, multipliers, and dividers. You will learn that there are two types of arithmetic operations performed by computers: integer and floating point. Finally, we will discuss the basics of floating point representation for carrying out operations with real numbers.

**Completing this unit should take you approximately 11 hours.**

Upon successful completion of this unit, you will be able to:

- discuss computer arithmetic hardware blocks and floating point representation;
- explain the representation of information, in particular integers and floating point numbers in a computer register or memory word;
- explain how arithmetic computations, addition, multiplication, subtraction, and division are performed on the data stored in a computer word;
- explain how to design simple hardware components, such as a half adder and full adder, perform this task, and in turn, use these components to perform subtraction and multiplication; and
- discuss the relationship of software and the hardware it controls.

### 4.1: Number Representation

Read sections 3.1 and 3.2 on pages 88–94 on representation of integers and real numbers. Earlier, you read about number systems and the representation of numbers used for computing. This will give you a chance to review that material.

Computer architecture comprises components which perform the functions of storage of data, transfer of data from one component to another, computations, and interfacing to devices external to the computer. Data is stored in terms of units, called words. A word is made up of a number of bits, typically, depending on the computer, 32 bits or 64 bits. Words keep getting longer, with larger numbers of bits. Instructions are also stored in words. Before, you saw examples of how instructions are stored in a word or words. Now, you will see how numbers are stored in words.

Read this article on the representation of real numbers.

### 4.2: Addition and Subtraction Hardware

Study slides 1–29 to learn how addition is implemented and carried out at the gate level. Nowadays, computers are architected using larger components. For example, to perform addition and subtraction, computer architects utilize ALUs, arithmetic logic units. You can design a computer without knowing the details of an ALU or of an adder, similar to using a calculator to find the square root of a number without knowing how to manually compute the square root (or in computer science terminology, without knowing the algorithm that the calculator performs to find the square root). However, we want you to have the strongest foundation in your study of computer architecture. Hence, study the assigned slides for Chapter 5. If you feel very ambitious, optionally you can study Chapters 6–8, which expand on basic addition.

Knowing the underlying algorithm for larger components, you will be able to better use them in constructing larger components, for example, using half adders to construct a full adder. A half adder takes 2 bits as input and outputs a sum and a carry bit; a full adder takes 2 operand bits and a carry bit as input, and outputs a sum bit and a carry bit. To add two floating point numbers, one or both need to be put in a form such that they have the same exponent. Then, the mantissas are added. Lastly, the result is normalized. We will cover floating point addition later. Subtraction is not discussed explicitly, because it is done via addition by reversing the sign of the number to be subtracted (subtrahend) and adding the result to the number subtracted from (minuend). You have to be careful when subtracting floating point numbers, because of the possible large round off error in the result.

### 4.3: Multiplication

Study slides 1–26. In particular, focus on section 9.1 to learn how multiplication is performed using basic steps that are carried out by elemental logic components, such as an adder and shifter. Two numbers are loaded into registers (fast word storage) and multiplication is carried out by repeated addition and shifting (moving the bits in a register to the right or left). The presentation first shows how multiplication is done for unsigned integers and then how signed numbers are handled.

When you read the slides, follow along by using a pad of paper and multiply two small binary numbers. k is the position of the binary digit; from right to left, k takes on 0, 1, 2, etc. j is the partial product; j goes from 1, 2, 3, etc. However, for consistency the 0th partial product is defined to be 0. Chapters 10–12 are optional; these chapters discuss ways of speeding up multiplication.

To multiply two floating point numbers, add the exponents, multiply the mantissas, normalize the mantissa of the product, and adjust the exponent accordingly. Floating point multiplication will be covered later.

### 4.4: Floating Point Arithmetic

Read section 3.3 on pages 94–100 and section 3.4 on pages 100–102. Section 3.3 provides an additional explanation of error analysis when numbers are represented using a fixed number of digits.

This issue mostly arises when using floating point numbers. Real numbers are represented using a fixed number of bits. The number of bits is the precision of the representation. The accuracy of the representation is described in terms of the difference between the actual number and its representation using a fixed number of bits. This difference is the error of the representation. The accuracy becomes more significant, because computations can cause the error to get so large that the result is meaningless and potentially even high risk depending on the application. Section 3.4 explains how programming languages approach number representation.

### 4.5: Division

Study slides 1–34. In particular, focus on section 13.1, which explains the basics of division using subtraction and shifting. Chapters 14–16 are optional; they cover ways of speeding up division.

### 4.6: Case Study: Floating Point Arithmetic in an x86 Processor

Read this article to learn about minimizing roundoff and overflow in floating point arithmetic using extended precision.

### Unit 4 Assessment

Take this assessment to see how well you understood this unit.

- This assessment
**does not count towards your grade**. It is just for practice! - You will see the correct answers when you submit your answers. Use this to help you study for the final exam!
- You can take this assessment as many times as you want, whenever you want.

- This assessment