Concurrency and parallelism are two related but distinct concepts in the context of computer programming. They both involve executing multiple tasks, but they do so in different ways and for different purposes.
Concurrency refers to the ability of a system to handle multiple tasks or processes at the same time, even if those tasks aren't executing simultaneously. Concurrency is about managing the execution order of tasks to make efficient use of resources, such as CPU time. In a concurrent system, tasks can be interleaved and executed in an overlapping manner.
Concurrency is often used to improve the responsiveness of applications by allowing them to handle multiple tasks concurrently without blocking. It's particularly important in situations where tasks might spend a significant amount of time waiting for external resources (e.g., I/O operations like network requests, file reads/writes). By interleaving tasks, the system can make progress on other tasks while waiting for I/O to complete.
Parallelism, on the other hand, involves executing multiple tasks simultaneously by utilizing multiple processors or cores. Parallelism is about true simultaneous execution of tasks, where each task runs in its own processing unit. Parallel execution is suitable for tasks that are CPU-bound, meaning they require a lot of computational processing.
Parallelism is more about exploiting hardware resources to achieve faster computation. It's commonly used in scientific computing, data analysis, and other tasks that involve heavy calculations.
Imagine you're cooking a meal in a kitchen:
