Learning Objectives
5 objectives- Understand fundamental concepts of computer architecture and organization, including hardware/software roles and the von Neumann architecture.
- Describe the structure and function of the CPU, including its components and instruction execution cycle.
- Explain the memory hierarchy and its impact on system performance, including caching and memory management principles.
- Analyze input/output systems and data transfer mechanisms, including interrupt handling and performance optimization.
- Explore advanced topics such as pipelining, parallel processing, multiprocessor systems, performance evaluation, and emerging trends in computer architecture.
Content Outline
PreviewUnit 608: Computer Architecture and Organization
1. Introduction to Computer Architecture and Organization
1.1 Basic Concepts
- Definition of computer architecture vs computer organization
- Role of hardware and software in computing systems
1.2 Von Neumann Architecture
- Components: memory, CPU, input/output
- Stored program concept
- Data and instruction flow
1.3 Relationship Between Hardware and Software
- Machine language and assembly language
- Hardware abstraction layers
- Impact on system design and performance
2. Central Processing Unit (CPU)
2.1 CPU Structure
- Control Unit (CU)
- Arithmetic Logic Unit (ALU)
- Registers: general purpose and special purpose
2.2 Instruction Cycle
- Fetch, decode, execute, and store
- Role of program counter and instruction register
2.3 Execution of Instructions
- Types of instructions: data transfer, arithmetic, control
- Micro-operations and timing
3. Memory Hierarchy
3.1 Primary Memory
- RAM: volatile memory characteristics
- ROM and its uses
3.2 Cache Memory
- Purpose and importance
- Cache levels (L1, L2, L3)
- Cache mapping techniques: direct, associative, set associative
3.3 Secondary Storage
- Hard disk drives (HDD)
- Solid-state drives (SSD)
- Other storage types
3.4 Memory Management and Caching Principles
- Locality of reference
- Cache replacement policies
- Virtual memory basics
4. Input and Output (I/O) Systems
4.1 I/O Devices and Interfaces
- Types of input/output devices
- Communication interfaces and protocols
4.2 Data Transfer Mechanisms
- Programmed I/O
- Interrupt-driven I/O
- Direct Memory Access (DMA)
4.3 Interrupt Handling
- Interrupt types and priorities
- Interrupt vector and service routines
4.4 I/O Performance Optimization
- Buffering and spooling
- Device scheduling
5. Instruction Set Architecture (ISA)
5.1 Design and Characteristics
- Definition and role of ISA
- RISC vs CISC architectures
5.2 Instruction Formats
- Fixed and variable length
- Fields: opcode, operands, addressing modes
5.3 Addressing Modes
- Immediate, direct, indirect, register, indexed
5.4 Types of Instructions
- Data transfer, arithmetic/logic, control flow, system
5.5 Relationship Between ISA and CPU Design
- Impact on hardware complexity
- Influence on compiler design
6. Pipelining and Parallel Processing
6.1 Pipelining Concepts
- Pipeline stages: fetch, decode, execute, memory access, write-back
- Pipeline hazards: structural, data, control
- Techniques for hazard mitigation
6.2 Parallelism Types
- SIMD (Single Instruction Multiple Data)
- MIMD (Multiple Instruction Multiple Data)
6.3 Benefits and Challenges
- Throughput improvement
- Complexity and synchronization issues
7. Multiprocessor Systems
7.1 Symmetric Multiprocessing (SMP)
- Architecture and characteristics
7.2 Distributed Memory Systems
- Concept and examples
- Communication between processors
7.3 Shared Memory Systems
- Memory coherence and consistency
7.4 Interconnection Networks
- Bus, crossbar, mesh networks
- Network topologies and performance
8. Performance Evaluation and Benchmarking
8.1 Performance Metrics
- Throughput, latency, CPI (cycles per instruction)
8.2 Benchmarking Methodologies
- Standard benchmarks (SPEC, LINPACK)
- Synthetic vs real-world benchmarks
8.3 Factors Affecting Performance
- CPU speed, memory hierarchy, I/O bandwidth
8.4 Techniques for Performance Improvement
- Hardware optimizations
- Software and compiler optimizations
9. Emerging Trends in Computer Architecture
9.1 Quantum Computing
- Basic principles
- Potential impact on computing
9.2 Neuromorphic Computing
- Brain-inspired architectures
- Applications and challenges
9.3 Energy-Efficient Designs
- Low-power architectures
- Dynamic voltage and frequency scaling
9.4 Impact of Emerging Technologies
- Integration with AI and machine learning
- Future directions in architecture design
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