Concurrency &. Parallelism

For the case of multi threaded programs we often use these terms, concurrency and parallelism.

Multiple tasks are in progress at the same time refers to concurrency. An application may process one task at at time (sequentially) or work on multiple tasks at the same time (concurrently).

Each task is broken in to sub tasks which can be processed in parallel. It is related to how an application handles each individual task. An application may process the task serially from start to end, or split the task up into subtasks which can be completed in parallel.

• An application can be concurrent, but not parallel. This means that it processes more than one task at the same time, but the tasks are not broken down into subtasks.
• An application can also be parallel but not concurrent. This means that the application only works on one task at a time, and this task is broken down into subtasks which can be processed in parallel.
• Additionally, an application can be neither concurrent nor parallel. This means that it works on only one task at a time, and the task is never broken down into subtasks for parallel execution.
• Finally, an application can also be both concurrent and parallel, in that it both works on multiple tasks at the same time, and also breaks each task down into subtasks for parallel execution. However, some of the benefits of concurrency and parallelism may be lost in this scenario, as the CPUs in the computer are already kept reasonably busy with either concurrency or parallelism alone. Combining it may lead to only a small performance gain or even performance loss. We should analyze and measure deeply before we adopt a concurrent parallel model blindly.