The promises of functional programming.


This week’s entry is about an article by Konrad Hinsen called “The Promises of Functional Programming”. I really liked reading this particular article because I’m currently working on parallel programming and found what Hinsen had to say about that interesting, but more on that later.

Hinsen also makes note of the way functional programming works just like math, where you have a function that given the same input will give the same output. I’m finding this kind of programming really cool (maybe because it’s way more related to my field where there are lots of applied maths), at first it felt weird programming without all the variables, but after I got the hang of it, I think having functions without side effects is way more practical.

What I still can’t get my head around is what everyone says about the functions being data, I don’t see how that can be relevant, but I hope in time I’ll see what all that is about.

Now, about the parallel programing. When I first got into parallel programming (using OpenMP on Ubuntu), I found programmers are having a hard time when trying to parallelize certain programs, and that it’s impossible to have a program that is 100% parallelized. And the hardest thing of all is to have a program automatically parallelized that maintains a higher efficiency than the serialized version of the program.

And just one of the worst problems I’ve had is dealing with the variables. Sometimes a thread will mess with a variable and every thread will make its operations on the messed up variable, turning the whole program useless. That’s why you have to be extra careful with the variables you make private.

With pure functions you don’t have to worry about this, thanks to them not having any side effects. I think this could be the way to optimize parallel programming.

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