Parallel Implementation

In this stage, you are required to write code to evolve Game of Life using multiple worker goroutines on a single machine.

The following pages are some suggested steps to help you get started, you are not required to follow them.

Your implementation will be marked against the success criteria outlined here.

Step 2

Parallelise your Game of Life so that it uses worker threads to calculate the new state of the board.

You should implement a distributor that tasks different worker threads to operate on different parts of the image in parallel.

The number of worker threads you should create is specified in gol.Params.Threads.

You are free to design your system as you see fit, however, we encourage you to primarily use channels.

Tips on improving the performance - worker pool

Unlike the Median Filter in Lab 1, the Game of Life involves rapid, repeated iterations, which requires frequent goroutine creation and destruction.

While goroutines are lightweight, frequent creation and destruction can still incur significant overhead. Hence, our core approach is to reuse goroutines, avoiding recreation in each iteration. We can abstract the design of the worker pool into four components: distributor, workers (goroutine), tasks (input) and results (output).

Workers are initialised ahead of computation and run continuously, processing tasks from the task channel and sending results back to the result channel. The distributor is responsible for assigning tasks to workers and collecting results for each iteration.

It is important to manage the lifecycle of the workers properly; when the distributor exits, ensure the workers are gracefully terminated.

It is recommended to back up your various implementations; this will be helpful for analysing how well you did in the later stages.

Test

To test your implementation, type the following in the terminal. You can use tracing to verify the correct number of workers was used this time.

go test -v -run TestGol