Parallel Computing (Cambridge International A-Level Computer Science)

Exam board Cambridge International · A-LevelUpdated 2025-05-14

Massively parallel computers are systems made up of thousands of processors working simultaneously to solve a single large problem
Each processor executes part of a program, and results are combined to produce the final output
They are designed to tackle complex, large-scale tasks in fields like
- Scientific research
- Weather simulation
- Cryptography
- AI

Feature	Description
Thousands of processors	Many processors are connected and work together to execute different parts of the same task
Shared or distributed memory	Each processor may have its own memory or access shared memory resources
High-speed interconnects	Processors are linked via fast communication pathways to share results
Data parallelism	Many data items can be processed at once — often using SIMD or MIMD
Task parallelism	Different processors may perform different tasks on different data sets
Specialised software	Requires software written to distribute the work efficiently across processors
Tightly coupled	Processors depend on one another and work collaboratively as a single system

Massively parallel computers	Cluster computers
Thousands of processors form a single tightly integrated system	Multiple independent systems networked together
Processors communicate continuously via shared architecture	Communication occurs via network, often loosely coupled
Acts like one machine with distributed processing	A group of co-operating systems (can be SIMD-based)
Higher performance, used for supercomputing tasks	More general-purpose or batch processing systems

Massively parallel systems often use:
- SIMD: Apply one instruction to many data points simultaneously
- MIMD: Run different instructions on different data, fully independently

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Feature

Description

Thousands of processors

Many processors are connected and work together to execute different parts of the same task

Shared or distributed memory

Each processor may have its own memory or access shared memory resources

High-speed interconnects

Processors are linked via fast communication pathways to share results

Data parallelism

Many data items can be processed at once — often using SIMD or MIMD

Task parallelism

Different processors may perform different tasks on different data sets

Specialised software

Requires software written to distribute the work efficiently across processors

Tightly coupled

Processors depend on one another and work collaboratively as a single system

Massively parallel computers

Cluster computers

Thousands of processors form a single tightly integrated system

Multiple independent systems networked together

Processors communicate continuously via shared architecture

Communication occurs via network, often loosely coupled

Acts like one machine with distributed processing

A group of co-operating systems (can be SIMD-based)

Higher performance, used for supercomputing tasks

More general-purpose or batch processing systems