Parallelism
Definition
Parallelism distributes simultaneous computations across multiple processing units.
The simultaneous execution of multiple computations on multiple processing units.
Simply explained
Multiple processors or cores handle different parts of a task at the same time.
Why it matters in practice
The term contributes to secure, maintainable, and high-performance web applications as well as resilient technical decisions.
Example from business
Independent data partitions are processed simultaneously on multiple cores.
Limits and pitfalls
- Equating parallelism with concurrency or ignoring communication and synchronization costs.
Origin & history
Parallelism is a fundamental principle of multicore, GPU, and distributed systems.
Use in mid-sized companies
- Possible application: Independent data partitions are processed simultaneously on multiple cores.
Frequently asked questions
What does Parallelism mean?
The simultaneous execution of multiple computations on multiple processing units. What mistakes should be avoided? Equating parallelism with concurrency or ignoring communication and synchronization costs.
Sources
Source checked on 10.10.2026. Editorial application examples are hypothetical; no proof of real customer results.
Editorially reviewed on: