What are the main differences between the concepts of parallel and concurrent task processing?

Parallel processing is the execution of multiple tasks simultaneously, using multiple processors or cores. For example, if you have 4 cores, you can run 4 threads at the same time, each performing its own task.

Concurrent processing is organizing work so that multiple tasks can progress simultaneously, but not necessarily execute at the same time. This is often achieved by context switching between tasks on a single processor, creating the illusion of simultaneity.

Example: in Python, you can implement concurrent execution using the threading module, and parallel execution with multiprocessing if the tasks are CPU-bound.

Key difference:

• Parallelism requires hardware support (multiple cores).
• Concurrency is about program structure and task management, and can work on a single core.