1.2.2

GPUs & Their Uses

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GPUs & Their Uses

A graphical processing unit (GPU) is now an essential feature in a gaming PC. They help display the output from your computer, but can be used for a whole lot more.

GPUs

GPUs

  • GPU stands for graphical processing unit.
  • A GPU is designed and made for processing graphical output from your computer system.
    • A GPU can be integrated into your computer’s motherboard
    • A GPU can also be a dedicated graphics card that plugs into the motherboard.
CPUs vs GPUs

CPUs vs GPUs

  • A CPU processes tasks in a serial order (one after another).
  • A GPU has lots of smaller cores that are very efficient at processing large amounts of visual data in smaller chunks simultaneously (in parallel).
Uses of GPUs

Uses of GPUs

  • A GPU is usually used to process the graphical information for a computer to output what the user is doing.
  • A GPU is also very useful for mining blockchain cryptocurrencies such as Bitcoin.
  • They are also often used in supercomputers as a parallel processor where a lot of data needs to be processed simultaneously.
    • These supercomputers could be for scientific use and engineering use.
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1

Components of a Computer

1.1

Structure & Function of the Processor

1.1.1Von Neumann Architecture1.1.2Registers1.1.3Buses1.1.4Fetch, Decode, Execute Cycle1.1.5Factors Affecting CPU Performance1.1.6Pipelining1.1.7CPU Architecture
1.2

Types of Processors

1.2.1CISC & RISC1.2.2GPUs & Their Uses1.2.3Multicore & Parallel Systems
1.3

Input, Output & Storage

1.3.1Elements of Computer Systems1.3.2Types of Computer Systems1.3.3How Magnetic Storage Works1.3.4Properties of Magnetic Storage1.3.5Examples of Magnetic Storage1.3.6How Optical Storage Works1.3.7Properties of Optical Storage1.3.8Examples of Optical Storage1.3.9Types of Optical Disc1.3.10Random Access Memory1.3.11Read Only Memory1.3.12Uses of Flash Memory1.3.13Properties of Flash Memory1.3.14What to do When We Run Out of Memory1.3.15How Virtual Memory Works
2

Software & Software Development

2.1

Systems Software

2.1.1Operating Systems2.1.2Managing Memory2.1.3Paging2.1.4Segmentation2.1.5Device Management & Drivers2.1.6Interrupts2.1.7Interrupt Service Routine (ISR)2.1.8Scheduling2.1.9Types of Scheduling2.1.10Types of Operating System2.1.11BIOS2.1.12Virtual Machines
2.2

Applications Generation

2.2.1Applications Software2.2.2Utilities2.2.3Encryption Software2.2.4Defragmentation Software2.2.5Data Compression Software2.2.6Backup Software2.2.7Open Source Software2.2.8Proprietary Software2.2.9Licensing Issues2.2.10Compilers2.2.11Interpreters2.2.12Assemblers2.2.13Compiling a Program2.2.14Lexical Analysis2.2.15Compilation Stages2.2.16Linkers, Loaders & Libraries
2.3

Software Development

2.3.1Algorithmic Thinking2.3.2Waterfall Lifecycle2.3.3Waterfall Lifecycle - Strengths & Weaknesses2.3.4Agile Methodology2.3.5Agile Methodology - Strengths & Weaknesses2.3.6Extreme Programming2.3.7Extreme Programming - Strengths & Weaknesses2.3.8Spiral Methodology2.3.9Spiral Methodology - Strengths & Weaknesses2.3.10Rapid Application Development2.3.11RAD - Strengths & Weaknesse
2.4

Types of Programming Language

2.4.1High Level Programming Languages2.4.2Low Level Programming Languages2.4.3Programming Paradigms2.4.4Procedural Programming Languages2.4.5Assembly2.4.6Machine Code2.4.7Modes of Addressing Memory2.4.8Object-Oriented Languages2.4.9Classes2.4.10Objects2.4.11Encapsulation2.4.12Polymorphism
3

Exchanging Data

3.1

Compression, Encryption & Hashing

3.1.1Compression3.1.2Run Length Encoding3.1.3Dictionary Coding3.1.4Encryption3.1.5Symmetric Encyrption3.1.6Hashing
3.2

Databases

3.2.1Records3.2.2Databases3.2.3Relational Databases3.2.4Entity Relationship Modelling3.2.5Managing Databases3.2.6Normalisation3.2.7SQL3.2.8Principles of Data Storage3.2.9Atomicity, Consistency, Isolation & Durability
3.3

Networks

3.3.1The Benefits of Networks3.3.2Network Performance3.3.3Types of Networks3.3.4Network Protocols3.3.5Transmission Protocols3.3.6What is the Internet?3.3.7Uniform Resource Locators3.3.8Domain Name Service3.3.9Web Hosting3.3.10Layering Concepts3.3.11TCP &. OSI Models3.3.12The Advantages of Layering3.3.13What's in a Packet?3.3.14How do Packets get Routed?3.3.15Did my Data Arrive Safely?3.3.16Network Hardware3.3.17Transmission Media3.3.18Firewalls3.3.19Proxies3.3.20Client-Server Model3.3.21Advantages of the Client Server Model3.3.22Disadvantages of the Client Server Model3.3.23Peer-to-Peer Model3.3.24Advantages of the Peer-to-Peer Model3.3.25Disadvantages of the Peer-to-Peer Model
3.4

Web Technologies

3.4.1HTML3.4.2CSS3.4.3JavaScript3.4.4Search Engine Indexing3.4.5PageRank Algorithm3.4.6Server & Client-Side Processing
4

Data Types, Data Structures & Algorithms

4.1

Data Types

4.1.1Data Types4.1.2Casting4.1.3Arrays4.1.42D Arrays4.1.5Strings4.1.6Binary4.1.7Sign & Magnitude4.1.8Binary Addition4.1.9Binary Shifts4.1.10Hexadecimal4.1.11Using Hexadecimal4.1.12Converting Binary & Hexadecimal4.1.13Converting Denary & Hexadecimal4.1.14Floating Points in Binary4.1.15Normalisation of Floating Points4.1.16Floating Point Addition4.1.17Floating Point Subtraction4.1.18Bitwise Manipulation - Shifts4.1.19Bitwise Manipulation - Masks4.1.20Character Sets4.1.21ASCII4.1.22Unicode
4.2

Data Structures

4.2.13D Arrays4.2.2Linked List4.2.3Queues4.2.4Graphs4.2.5Hash Tables4.2.6Stacks4.2.7Trees4.2.8Binary Search Trees
4.3

Boolean Algebra

4.3.1Binary Systems4.3.2Logic Circuits4.3.3Boolean Operators4.3.4Evaluating Expressions4.3.5Boolean Logic4.3.6Karnaugh Maps4.3.7Boolean Identities4.3.8Boolean Rules4.3.9Flip Flops4.3.10Adder Circuits
5

Legal, Moral, Cultural & Ethical Issues

5.1

Computing Related Legislation

5.1.1Data Protection Act (1998)5.1.2Computer Misuse Act (1990)5.1.3Copyright Designs & Patents Act (1988)5.1.4Creative Commons Licensing5.1.5Regulation of Investigatory Powers Act (2000)
5.2

Moral & Ethical Issues

5.2.1Online Activity Tracking5.2.2Censorship5.2.3Positive Cultural Impacts5.2.4Negative Cultural Impacts5.2.5E-Waste5.2.6Energy Consumption5.2.7Positive Environmental Impact5.2.8Layout, Colour Paradigms & Character Sets5.2.9Computers in the Workplace5.2.10Automated Decision-Making5.2.11Artificial Intelligence5.2.12Monitoring Behaviour5.2.13Analysing Personal Information5.2.14Piracy & Offensive Communication
6

Elements of Computational Thinking

6.1

Thinking Abstractly

6.1.1Abstraction
6.2

Thinking Ahead

6.2.1Inputs & Outputs
6.3

Thinking Procedurally

6.3.1Decomposition
6.4

Thinking Logically

6.4.1Pseudocode6.4.2Flow Diagrams
6.5

Thinking Concurrently

6.5.1Concurrent Processing
7

Problem Solving & Programming

7.1

Programming Techniques

7.1.1Variables & Constants7.1.2Comments7.1.3Inputs & Outputs7.1.4Subroutines7.1.5Scope
7.2

Programming Construction

7.2.1Integrated Development Environments7.2.2The Purpose of Testing7.2.3Types of Testing7.2.4Test Plans
8

Algorithms

8.1

Algorithms

8.1.1Interpreting Algorithms8.1.2Correcting Algorithms8.1.3Completing Algorithms8.1.4Sort Algorithms8.1.5Bubble Sort8.1.6Insertion Sort8.1.7Merge Sort8.1.8Search Algorithms8.1.9Linear Search8.1.10Binary Search8.1.11Quick Sort Algorithm8.1.12A* Algorithm

Practice questions on GPUs & Their Uses

Can you answer these? Test yourself with free interactive practice on Seneca — used by over 10 million students.

  1. 1
    What does GPU stand for?Fill in the list
  2. 2
    Why are CPUs less efficient at processing large amounts of data?Multiple choice
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CISC & RISC

Multicore & Parallel Systems