Computer Science Computer Science Fundamentals Computer Organization and Architecture
Computer Organization and Architecture
Computer Organization and Architecture is a fundamental area of computer science that details the internal structure and operational behavior of a computer system, effectively bridging the gap between hardware and software. Computer *architecture* defines the system from a programmer's perspective, specifying the instruction set (ISA), data types, and memory addressing modes—essentially, *what* the computer does. Computer *organization*, in contrast, focuses on the implementation of that architecture, detailing *how* the components like the CPU, memory hierarchy (including caches), and I/O systems are interconnected and managed to achieve the specified functionality and performance goals.
1.1.
Defining Computer Architecture and Organization
1.1.1.
Computer Architecture Fundamentals
1.1.2.
Computer Organization Fundamentals
1.1.3.
Distinction Between Architecture and Organization
1.1.4.
Levels of Abstraction in Computer Systems
1.1.4.1. Application Level
1.1.4.2. High-Level Language Level
1.1.4.3. Assembly Language Level
1.1.4.4. Machine Language Level
1.1.4.5. Microarchitecture Level
1.1.4.6. Digital Logic Level
1.2.
Historical Evolution of Computers
1.2.1.
First Generation: Vacuum Tubes (1940s-1950s)
1.2.1.1. Vacuum Tube Technology
1.2.1.2. Characteristics and Limitations
1.2.2.
Second Generation: Transistors (1950s-1960s)
1.2.2.1. Transistor Technology
1.2.2.2. Advantages Over Vacuum Tubes
1.2.3.
Third Generation: Integrated Circuits (1960s-1970s)
1.2.3.1. Small-Scale Integration (SSI)
1.2.3.2. Medium-Scale Integration (MSI)
1.2.4.
Fourth Generation: Microprocessors (1970s-1990s)
1.2.4.3. Personal Computer Revolution
1.2.5.
Fifth Generation and Beyond (1990s-Present)
1.2.5.1. Very Large Scale Integration (VLSI)
1.2.5.2. Ultra Large Scale Integration (ULSI)
1.2.5.3. Multi-core Processors
1.2.5.4. System-on-Chip (SoC)
1.3.
The Von Neumann Architecture
1.3.1.
Stored-Program Concept
1.3.1.1. Program Storage in Memory
1.3.1.2. Data Storage in Memory
1.3.1.3. Sequential Instruction Execution
1.3.2.
Key Components
1.3.2.1. Central Processing Unit (CPU)
1.3.2.3. Input/Output System
1.3.3.
Von Neumann Bottleneck
1.3.3.1. Memory Access Limitations
1.3.3.2. Solutions and Workarounds
1.4.
Alternative Computer Architectures
1.4.1. Harvard Architecture
1.4.2. Modified Harvard Architecture
1.4.3. Dataflow Architecture
1.5.
Measuring and Evaluating Performance
1.5.1.
Performance Metrics
1.5.2.
Clock Speed and Instruction Execution
1.5.2.3. Cycles Per Instruction (CPI)
1.5.2.4. Instruction Count
1.5.3.
Performance Equations
1.5.3.2. MIPS (Million Instructions Per Second)
1.5.3.3. MFLOPS (Million Floating-Point Operations Per Second)
1.5.3.4. Limitations of MIPS and MFLOPS
1.5.4.
Benchmarking
1.5.4.1. Synthetic Benchmarks
1.5.4.2. Application Benchmarks
1.5.4.4. Benchmark Selection Criteria
1.5.5.
Amdahl's Law
1.5.5.1. Mathematical Formula
1.5.5.2. Interpretation and Implications
1.5.5.3. Limitations of Parallel Processing