Definition
Parallel processing is a computing method that uses multiple processors to simultaneously manage separate parts of a single task.
It divides large tasks into smaller sub-tasks, decreasing a program’s running time. Any system with multiple central processing units (CPUs), including multi-core processors, can execute parallel processing.
Parallel Processing Benefits
- Quicker processing times. Parallel processing enables systems to execute numerous sub-tasks simultaneously, decreasing the time needed to complete a task.
- Increased throughput. Parallel processing helps to improve the computing system’s overall throughput.
- Cost-effectiveness. Multiple processors are more cost-effective than a single high-performance processor.
- Scalability. Parallel processing is easily scalable (up or down) depending on the task requirements.
- Better fault tolerance. This means that parallel processing can continue to operate even if one processor or computing unit malfunctions.
How Does Parallel Processing Work
- Dividing the tasks: A single task is broken into smaller sub-tasks that can be executed simultaneously.
- Assigning resources: Each task is allocated to a specific processor or spread across different processors to improve performance.
- Synchronization: The processors execute the subtasks simultaneously once the resources are allocated. The output of each subtask is synchronized to ensure the final result is complete and accurate. Synchronization methods such as barriers, locks, and semaphores are applicable.
- Merging results: After completing each sub-task, the results are combined to generate the final output.