Putting the fun in functional programming since 2005!
Friday, 4 May 2012
What's wrong with using async for parallel programming?
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.
For example, the following F# code maps a function over an array in parallel using the Task Parallel Library in .NET 4:
Array.Parallel.map f xs
Async cannot be used to write cache oblivious code and, consequently, async-based parallel programs are likely to 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.