On 04/05/2010, at 09:21, Christian Höner zu Siederdissen wrote: > Hi, > > on that topic, consider this (rather trivial) array: > > a = array (1,10) [ (i,f i) | i <-[1..10]] where > f 1 = 1 > f 2 = 1 > f i = a!(i-1) + a!(i-2) > > (aah, school ;) > > Right now, I am abusing vector in ST by doing this: > > a <- new > a' <- freeze a > forM_ [3..10] $ \i -> do > write a (a'!(i-1) + a!(i-2)) > > Let's say I wanted to do something like this in dph (or repa), does that > work? We are actually using this for RNA folding algorithms that are at > least O(n^3) time. For some of the more advanced stuff, it would be > really nice if we could "just" parallelize.
Do you really just need a prefix sum? These are easily parallelisable if the operator is associative. For instance, you could implement the Fibonacci sequence as: mapP fst $ scanP (\(a,b) _ -> (a+b,a)) (1,0) $ replicateP n (0,0) and DPH would parallelise it. That's how I would write the above with vector as well. > To summarise: I need arrays that allow in-place updates. In-place updates + parallelism = bad! That's oversimplifying, of course. But the transformations underlying DPH, for instance, simply don't work in the presence of side effects. > Otherwise, most libraries that do heavy stuff (O(n^3) or worse) are > using vector right now. On a single core, it performs really great -- > even compared to C-code that has been optimized a lot. That's great to know! Do you (or anyone else) by any chance have any benchmarks you could share? At the moment, I'm only benchmarking vector with a couple of rather simplistic algorithms which is a bit of a problem. Roman _______________________________________________ Glasgow-haskell-users mailing list Glasgow-haskell-users@haskell.org http://www.haskell.org/mailman/listinfo/glasgow-haskell-users
