Multicore & Parallel Cores

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

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

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

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.

Multicore and Parallel Systems

CPU technology has moved on drastically and most now feature multiple cores. Some specialist computers use parallel processors instead.

Multicore

Most computers (and smartphones) now use multicore systems.
Multicore systems are CPU chips that have multiple cores inside a single physical chip.
These multicore systems allow multitasking more easily as processing workload can be shared across the cores.

Optimisation

Individual pieces of software also need to be optimised to take full advantage of multicore systems.
- Google Chrome is considered to be optimised for multicore systems.

Parallel

A parallel CPU is one that has lots of CPU cores (like a multicore CPU).
These cores all complete the same instructions on slightly different sets of data.
Parallel CPUs are made for processing large amounts of data very quickly.
- A GPU is a type of parallel processor.

1Components of a Computer

1.1Structure & Function of the Processor

1.1.1Structure of the CPU

1.1.2Fetch, Decode, Execute Cycle

1.1.3Factors Affecting CPU Performance

1.1.4CPU Architecture

1.2Types of Processors

1.2.1CISC & RISC

1.2.2Multicore & Parallel Cores

1.3Input, Output & Storage

1.3.1Computer Systems

1.3.2Magnetic Storage

1.3.3Optical Storage

1.3.4Types of Optical Storage

1.3.5Types of Memory

1.3.6Flash Memory

1.3.7Virtual Memory

2Software & Software Development

3Exchanging Data

4Data Types, Data Structures & Algorithms

4.1Data Types

4.1.1Data Types

4.1.2Arrays & Strings

4.1.3Representing Numbers

4.1.4Binary Arithmetic

4.1.5Hexadecimal

4.1.6Converting Binary Numbers

4.1.7Floating Points in Binary

4.1.8Floating Point Arithmetic

4.1.9Bitwise Manipulation

4.1.10Character Sets

4.2Data Structures

4.2.1Arrays, Linked Lists & Queues

4.2.2Graphs, Hash Tables & Stacks

4.2.3Trees

4.3Boolean Algebra

4.3.1Computational Logic

4.3.2Boolean Logic

4.3.3Karnaugh Maps

4.3.4Boolean Identities

4.3.5Flip Flops & Adder Circuits

5Legal, Moral, Cultural & Ethical Issues

5.1Computing Related Legislation

5.1.1Data Protection Act (1998)

5.1.2Computer Misuse Act (1990)

5.1.3Copyright Designs and Patents Act (1988)

5.1.4Regulation of Investigatory Powers Act (2000)

5.2Moral & Ethical Issues

5.2.1Online Activity Tracking

5.2.2Censorship

5.2.3Cultural Issues

5.2.4Environmental Issues

5.2.5Layout, Colour Paradigms & Character Sets

6Elements of Computational Thinking

6.1Thinking Abstractly

6.1.1Abstraction

6.2Thinking Procedurally

6.2.1Decomposition

6.3Thinking Logically

6.3.1Pseudocode & Flow Diagrams

7Problem Solving & Programming

7.1Programming Techniques

7.1.1Programming Fundamentals

7.1.2Modularity

7.2Programming Construction

7.2.1Integrated Development Environments

7.2.2Testing

8Algorithms

8.1Algorithms

8.1.1Interpreting, Correcting & Completing Algorithm

8.1.2Sort Algorithms

8.1.3Insertion & Merge Sort

8.1.4Search Algorithms

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