Overhead from calling.
Now go to Google or >>sqt

This is a huge topic

Get a fucking book

need a good language tbqh

let rec fib x = if x <= 2 then 1 else fib(x-1) + fib(x-2)

let fibs =
    Async.Parallel [ for i in 0..40 -> async { return fib(i) } ]
    |> Async.RunSynchronously

The above code sample shows the elements of the Parallel CPU Asyncs pattern:

(a) “async { … }” is used to specify a number of CPU tasks
(b) These are composed in parallel using the fork-join combinator Async.Parallel

In this case the composition is executed using Async.RunSynchronously, which starts an instance of the async and synchronously waits for the overall result.

File: parallelconcurrenthaskell.jpg (795 KB, 2100x2756) Image search: [Google]

795 KB, 2100x2756

Not using enough Haskell

>>54834420
1) data dependencies
2) depending on the amount and type of data to be processed, the act of distributing data among workers may cause overheads that wipe out the gains.
3) scheduling