Granularity (parallel computing)

Granularity in parallel computing means breaking down a task into smaller parts so that they can be done at the same time by different parts of a computer. It's like taking a big Lego tower and separating it into smaller pieces that can be built separately and put together at the end.

When you have a big task to do, it can be more efficient to do it all at once on multiple parts of a computer instead of doing it sequentially on one part. It’s like having multiple people work on a big project together to get it done faster.

But, you need to make sure the task is broken down into the right sized pieces, or granularity. If the pieces are too big, then only one part of the computer can work on it at a time, which defeats the purpose of parallel computing. If the pieces are too small, then there will be too much overhead in coordinating all the different parts working on different pieces, which slows down the overall processing time.

Therefore, the right granularity means finding the right balance of splitting the task into small enough pieces to take advantage of parallelism but large enough to minimize coordination overhead.