Computer Science: Input/Output Management and Storage Devices

Study Notes

Input/Output (I/O) devices allow users to interact with the computer
Types of I/O devices:
- Input devices: keyboard, mouse, scanner, microphone
- Output devices: monitor, printer, speaker, plotter
I/O management involves:
- Managing data transfer between devices and CPU
- Handling I/O requests and interrupts
- Managing I/O operations concurrently

Types of storage devices:
- Primary storage (main memory):
  - RAM (Random Access Memory)
  - Cache memory
- Secondary storage:
  - Hard Disk Drive (HDD)
  - Solid State Drive (SSD)
  - Optical storage (CD, DVD, Blu-ray)
  - Flash storage (USB drives, memory cards)
Storage devices characteristics:
- Capacity: amount of data that can be stored
- Access time: time taken to access data
- Data transfer rate: speed of data transfer

An Operating System (OS) manages computer hardware and software resources
OS functions:
- Process management: creating, running, and terminating processes
- Memory management: allocating and deallocating memory
- File management: creating, deleting, and managing files
- I/O management: managing input/output operations
- Security: controlling access to computer resources
Types of OS:
- Single-user, single-tasking OS
- Multi-user, single-tasking OS
- Multi-user, multi-tasking OS
- Real-time OS

CPU (Central Processing Unit) architecture:
- Fetch-decode-execute cycle: retrieves, decodes, and executes instructions
- Components:
  - Control Unit: manages instruction flow
  - Arithmetic Logic Unit (ALU): performs arithmetic and logical operations
  - Registers: small amount of on-chip memory
- Instruction Set Architecture (ISA): defines instructions and their formats
CPU types:
- CISC (Complex Instruction Set Computing): executes complex instructions
- RISC (Reduced Instruction Set Computing): executes simple instructions

Algorithm: a step-by-step procedure to solve a problem
Algorithm design principles:
- Correctness: produces correct results
- Efficiency: minimizes time and space complexity
- Scalability: adapts to large input sizes
- Simplicity: easy to understand and implement
Algorithm design techniques:
- Divide and Conquer: breaks down problems into smaller sub-problems
- Dynamic Programming: stores solutions to sub-problems
- Greedy Algorithm: makes optimal choices at each step
- Backtracking: tries different solutions until one works

Input devices allow users to interact with the computer, including keyboard, mouse, scanner, and microphone
Output devices display or produce the results of computer processing, including monitor, printer, speaker, and plotter
I/O management involves managing data transfer between devices and CPU, handling I/O requests and interrupts, and managing I/O operations concurrently

Primary storage (main memory) includes RAM (Random Access Memory) and cache memory, which temporarily hold data and program instructions
Secondary storage devices, such as Hard Disk Drive (HDD), Solid State Drive (SSD), Optical storage (CD, DVD, Blu-ray), and Flash storage (USB drives, memory cards), hold data when the computer is powered off
Storage devices are characterized by capacity, access time, and data transfer rate

An Operating System (OS) manages computer hardware and software resources, including process management, memory management, file management, I/O management, and security
Types of OS include single-user, single-tasking OS, multi-user, single-tasking OS, multi-user, multi-tasking OS, and real-time OS

CPU (Central Processing Unit) architecture involves the fetch-decode-execute cycle, which retrieves, decodes, and executes instructions
CPU components include the Control Unit, Arithmetic Logic Unit (ALU), and Registers
The Instruction Set Architecture (ISA) defines instructions and their formats, and CPU types include CISC (Complex Instruction Set Computing) and RISC (Reduced Instruction Set Computing)

An algorithm is a step-by-step procedure to solve a problem, and should be correct, efficient, scalable, and simple
Algorithm design techniques include Divide and Conquer, Dynamic Programming, Greedy Algorithm, and Backtracking
These techniques are used to develop algorithms that produce correct results, minimize time and space complexity, adapt to large input sizes, and are easy to understand and implement