What are the different parallel techniques in computing?

What are the different parallel techniques in computing?

There are several parallel techniques in computing, including data parallelism, task parallelism, and pipeline parallelism. Would you like to know more about each?

Yes, please explain data parallelism.

Data parallelism involves distributing data across multiple processors, where each processor performs the same operation on different pieces of data simultaneously. This is often used in applications like image processing.

What about task parallelism?

Task parallelism focuses on distributing different tasks across multiple processors. Each processor may perform a different operation, which is useful in scenarios where tasks can be executed independently.

Can you give an example of pipeline parallelism?

Sure! Pipeline parallelism is like an assembly line where different stages of a process are handled by different processors. For example, in video processing, one processor might decode the video, while another encodes it.