Control.Parallel.Strategies.parMap CPU usage

[Simon Marlow]

Christian Hoener zu Siederdissen wrote:

> when using parMap (or parList and demanding) I see a curious pattern in 
> CPU usage.
> Running "parMap rnf fib [1..100]" gives the following pattern of used CPUs:
> 4,3,2,1,4,3,2,1,...

How did you find out which CPU is being used?

> The fib function requires roughly two times the time if we go from 
> fib(n) to fib(n+1), meaning that calculating the next element in the 
> list always takes longer than the current. What I would like is a 
> version of parMap that directly takes a free CPU and lets it calculate 
> the next result, giving the usage pattern 4,4,4,4,...

In GHC you don't have any control over which CPU is used to execute a 
spark.  We use dynamic load-balancing, which means the work distribution is 
essentially random, and will change from run to run.

If you want more explicit control over your work distribution, try using 
GHC.Conc.forkOnIO.

Also note that the implementation of much of this stuff is changing 
rapidly, so you might want to try a recent snapshot.  Take a look at our 
paper, if you haven't already:

http://www.haskell.org/~simonmar/papers/multicore-ghc.pdf

Cheers,
	Simon