Definitions
- Referring to the process of dividing a task into smaller sub-tasks that can be executed simultaneously. - Talking about the technique of running multiple processes or threads on different processors or cores to speed up computation. - Describing the method of breaking down a large problem into smaller parts and solving them at the same time.
- Referring to the ability of a system to handle multiple tasks or processes at the same time. - Talking about the technique of executing multiple tasks or processes simultaneously. - Describing the situation where two or more tasks are in progress at the same time.
List of Similarities
- 1Both involve the execution of multiple tasks or processes.
- 2Both aim to improve the efficiency of computation.
- 3Both require careful management of resources.
- 4Both can be used to speed up the execution of programs.
- 5Both are important techniques in modern computing.
What is the difference?
- 1Scope: Parallelisation refers to breaking down a single task into smaller sub-tasks, while concurrency refers to handling multiple tasks or processes at the same time.
- 2Approach: Parallelisation involves dividing a task into smaller parts that can be executed simultaneously, while concurrency involves executing multiple tasks or processes simultaneously.
- 3Resource management: Parallelisation requires careful management of resources such as memory and processors, while concurrency requires careful management of resources such as threads and synchronization.
- 4Complexity: Parallelisation can be more complex than concurrency because it involves breaking down a task into smaller parts and coordinating their execution, while concurrency involves managing multiple tasks or processes that may have different priorities.
- 5Performance: Parallelisation can achieve higher performance gains than concurrency in some cases, but it depends on the nature of the task and the available resources.
Remember this!
Parallelisation and concurrency are both techniques used to improve the efficiency of computation by executing multiple tasks or processes simultaneously. However, parallelisation involves breaking down a single task into smaller sub-tasks that can be executed simultaneously, while concurrency involves handling multiple tasks or processes at the same time. Both require careful management of resources and can be complex, but parallelisation can achieve higher performance gains in some cases.
