I have been learning F# recently, being particularly interested in its ease of exploiting data parallelism. The data |> Array.map |> Async.Parallel |> Async.RunSy
I always figured it's what TPL, PLinq etc... give you over and above what Async does. (Cancellation mechanisms is the one that comes to mind.) This question has some better answers.
This article hints at a slight performance advantage to TPL, but probably not enough to be significant.
I wrote an article that re-implements one C# TPL sample using both Task
and Async
, which also has some comments on the difference between the two. You can find it here and there is also a more advanced async-based version.
Here is a quote from the first article that compares the two options:
The choice between the two possible implementations depends on many factors. Asynchronous workflows were designed specifically for F#, so they more naturally fit with the language. They offer better performance for I/O bound tasks and provide more convenient exception handling. Moreover, the sequential syntax is quite convenient. On the other hand, tasks are optimized for CPU bound calculations and make it easier to access the result of calculation from other places of the application without explicit caching.
So why shouldn't I use async to execute parallel data processes?
If you have a tiny number of completely independent non-async
tasks and lots of cores then there is nothing wrong with using async to achieve parallelism. However, if your tasks are dependent in any way or you have more tasks than cores or you push the use of async
too far into the code then you will be leaving a lot of performance on the table and could do a lot better by choosing a more appropriate foundation for parallel programming.
Note that your example can be written even more elegantly using the TPL from F# though:
Array.Parallel.map f xs
What am I going to lose by writing parallel async code instead of using PLINQ or TPL?
You lose the ability to write cache oblivious code and, consequently, will suffer from lots of cache misses and, therefore, all cores stalling waiting for shared memory which means poor scalability on a multicore.
The TPL is built upon the idea that child tasks should execute on the same core as their parent with a high probability and, therefore, will benefit from reusing the same data because it will be hot in the local CPU cache. There is no such assurance with async.