I'm trying to parallelize a Monte Carlo backtracking search algorithm. The trick is that my algorithm is expressed in a State monad, because I need to hold a StdGen as well as keep several records of computations and metrics. So I know that if I'm going to run a State computation in several parallel lines of execution, I need to conceive of a way to split the state and later recombine it. Here is a simple example I came up with. I have no idea if I'm doing this in a good way, so any comments are welcome. http://lpaste.net/356879 D
For a splittable PRNG, check out tf-random. LY On 07/11/2017 09:11 PM, Dennis Raddle wrote:
I'm trying to parallelize a Monte Carlo backtracking search algorithm. The trick is that my algorithm is expressed in a State monad, because I need to hold a StdGen as well as keep several records of computations and metrics.
So I know that if I'm going to run a State computation in several parallel lines of execution, I need to conceive of a way to split the state and later recombine it.
Here is a simple example I came up with. I have no idea if I'm doing this in a good way, so any comments are welcome.
D
_______________________________________________ Haskell-Cafe mailing list To (un)subscribe, modify options or view archives go to: http://mail.haskell.org/cgi-bin/mailman/listinfo/haskell-cafe Only members subscribed via the mailman list are allowed to post.
I recently made a SplitMix implentation: http://hackage.haskell.org/package/splitmix When generating `Word64`s it's noticeable faster than `tf-random` (and `mwc-random` and obviously `random). I didn't benchmark `Double` generation, as `tf-random` own `Random` class doesn't support it [1], and using `random`'s class would be very unfair. I haven't announced it (well, mentioned on Twitter), but please give it a try! - Oleg -[1] http://hackage.haskell.org/package/tf-random-0.5/docs/System-Random-TF-Insta... On 12.07.2017 04:21, Li-yao Xia wrote:
For a splittable PRNG, check out tf-random.
LY
On 07/11/2017 09:11 PM, Dennis Raddle wrote:
I'm trying to parallelize a Monte Carlo backtracking search algorithm. The trick is that my algorithm is expressed in a State monad, because I need to hold a StdGen as well as keep several records of computations and metrics.
So I know that if I'm going to run a State computation in several parallel lines of execution, I need to conceive of a way to split the state and later recombine it.
Here is a simple example I came up with. I have no idea if I'm doing this in a good way, so any comments are welcome.
D
_______________________________________________ Haskell-Cafe mailing list To (un)subscribe, modify options or view archives go to: http://mail.haskell.org/cgi-bin/mailman/listinfo/haskell-cafe Only members subscribed via the mailman list are allowed to post.
_______________________________________________ Haskell-Cafe mailing list To (un)subscribe, modify options or view archives go to: http://mail.haskell.org/cgi-bin/mailman/listinfo/haskell-cafe Only members subscribed via the mailman list are allowed to post.
participants (3)
-
Dennis Raddle -
Li-yao Xia -
Oleg Grenrus