Channels are like background plumbing for parallel computing in Julia. They are the reservoirs from which the individual processes access their data.
The requirements are similar to the previous sections. This is mostly a theoretical section, so you just need to run your experiments on your own. For that, you need to run your Julia REPL in a multiprocessing mode.
Channels are shared queues with a fixed length. They are common data reservoirs for the processes which are running.
The channels are like common data resources, which multiple readers or workers can access. They can access the data through the fetch() function, which we already discussed in the previous sections.
The workers can also write to the channel through the put!() function. This means that the workers can add more data to the resource, which can be accessed by all the workers running a particular computation.
Closing a channel after use is a good practice to avoid data corruption and unnecessary...
