Real-life applications of concurrent reduction operators
The communicative and associative nature of the way reduction operators process their data enables the subtasks of an operator to be processed independently, and is thus highly connected to concurrency and parallelism. Consequently, various topics in concurrent programming could be related to reduction operators, and by applying the same principles of reduction operators, problems regarding those topics could be made more intuitive and efficient.
As we have seen, add and multiply operators are reduction operators. More generally, number-crunching problems that usually involve communicative and associative operators are prime candidates for applying concurrency and parallelism. This is actually a true case for the famous, and arguably one of the most used modules in Python—NumPy, whose code is implemented to be as parallelizable as possible.
Furthermore, applying the logic operators AND, OR, or XOR to an array of Boolean values works...
