Arithmetic Logic Unit (ALU) Design - Computer Architecture
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Arithmetic Logic Unit (ALU) Design

Arithmetic Logic Unit (ALU) Design

The chapter provides an in-depth exploration of the design and function of the Arithmetic Logic Unit (ALU), which is crucial for the computations in a CPU. It details key operations of the ALU including basic arithmetic and logical operations, intricacies of integer multiplication and division, and floating-point number representation. Additionally, the chapter analyzes the IEEE 754 standard, emphasizing its impact on numerical accuracy and the design of arithmetic circuits.

33 sections

Sections

Navigate through the learning materials and practice exercises.

  1. 4
    Arithmetic Logic Unit (Alu) Design

    This section explores the design and functionality of the Arithmetic Logic...

  2. 4.1
    General Alu Design Principles

    This section introduces the fundamental design principles of Arithmetic...

  3. 4.1.1
    Alu Function: Performing Arithmetic And Logical Operations

    This section describes the functions of the ALU in executing arithmetic and...

  4. 4.1.1.1
    Arithmetic Operations

    This section discusses basic arithmetic operations performed by the...

  5. 4.1.1.2
    Logical Operations

    This section introduces logical operations in the context of Arithmetic...

  6. 4.1.2
    Inputs And Outputs Of An Alu

    This section discusses the essential inputs and outputs of the Arithmetic...

  7. 4.1.3
    Basic Logic Gates As Building Blocks: And, Or, Not, Xor

    This section describes the essential logic gates that form the foundation of...

  8. 4.1.4
    Full Adder And Ripple-Carry Adder: Basic Arithmetic Circuits

    This section covers the fundamental components of binary addition, including...

  9. 4.1.5
    Look-Ahead Carry Adder: Improving Adder Speed

    The Look-Ahead Carry Adder (LCA) improves the speed of binary addition by...

  10. 4.1.6
    Multi-Bit Alus: Combining Basic Units To Handle Wider Data Paths

    Multi-bit ALUs are constructed by arranging multiple single-bit ALU slices...

  11. 4.2
    Integer Multiplication Design

    This section covers the hardware implementation and principles of integer...

  12. 4.2.1
    Basic Principles Of Multiplication: Repeated Addition

    This section explains how integer multiplication is fundamentally based on...

  13. 4.2.2
    Hardware Implementation Of Unsigned Multiplication

    This section discusses the hardware implementation techniques for unsigned...

  14. 4.2.2.1
    Array Multiplier (Combinational/parallel Implementation)

    An array multiplier is a combinational circuit that computes the product of...

  15. 4.2.2.2
    Sequential Multiplier (Iterative/sequential Implementation)

    The Sequential Multiplier iteratively computes products using registers and...

  16. 4.2.3
    Booth's Algorithm: Efficient Multiplication For Signed (Two's Complement) Numbers

    Booth's algorithm offers an efficient method for multiplying signed binary...

  17. 4.3
    Integer Division Design

    Integer division is the process of repeatedly subtracting the divisor from...

  18. 4.3.1
    Basic Principles Of Division: Repeated Subtraction

    This section explains the foundational principle of division in binary,...

  19. 4.3.2
    Hardware Implementation Of Unsigned Division

    This section discusses the hardware implementation of unsigned division in...

  20. 4.3.2.1
    Restoring Division Algorithm

    The Restoring Division Algorithm is a method for executing binary division...

  21. 4.3.2.2
    Non-Restoring Division Algorithm (More Efficient)

    The Non-Restoring Division Algorithm enhances division efficiency by...

  22. 4.3.3
    Signed Division Considerations: Handling Signs Of Dividend, Divisor, Quotient, And Remainder

    This section explains the handling of signs in the division process for...

  23. 4.4
    Floating Point Arithmetic

    Floating point arithmetic allows for precise representation of a wide range...

  24. 4.4.1
    Motivation For Floating Point Numbers: Representing Very Large, Very Small, And Fractional Numbers

    Floating-point numbers allow for precise representation of very large, very...

  25. 4.4.2
    Structure Of A Floating Point Number: Sign, Exponent, Mantissa (Significand)

    This section discusses the components that make up a binary floating-point...

  26. 4.4.3
    Normalization: Standardizing The Mantissa

    Normalization in floating-point representation ensures a unique and...

  27. 4.4.4
    Bias In Exponent: Representing Both Positive And Negative Exponents

    This section explains the concept of bias in the exponent field of...

  28. 4.5
    Ieee 754 Floating Point Formats

    The IEEE 754 standard defines the representation and arithmetic operations...

  29. 4.5.1
    Single-Precision (32-Bit) Format

    The single-precision format, as defined by the IEEE 754 standard, utilizes...

  30. 4.5.2
    Double-Precision (64-Bit) Format

    This section discusses the IEEE 754 standard for double-precision...

  31. 4.5.3
    Floating Point Arithmetic Operations

    This section explores floating-point arithmetic operations, highlighting...

  32. 4.5.4
    Rounding Modes

    Rounding modes in the IEEE 754 standard provide methods to manage precision...

  33. 4.5.5
    Impact Of Floating Point Arithmetic On Numerical Accuracy And Precision

    Floating-point arithmetic is essential for representing a wide array of...

What we have learnt

  • The ALU is a combinational circuit performing arithmetic and logical operations essential for CPU functionality.
  • Understanding the hardware implementation of addition, subtraction, multiplication, and division is critical for efficient ALU design.
  • Floating-point representation allows computers to handle very large, very small, and fractional numbers, adhering to the IEEE 754 standard for consistent results.

Key Concepts

-- Arithmetic Logic Unit (ALU)
The core computational engine of a CPU that performs arithmetic and logical operations.
-- IEEE 754
A standard for floating-point computation that ensures consistent representation and behavior across different computing systems.
-- Bias in Exponent
A method of storing exponent values in floating-point representation that offsets the true exponent to allow for a range of positive values.
-- Normalization
A process in floating-point arithmetic that ensures a unique binary representation for numbers by shifting the mantissa.

Additional Learning Materials

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