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.
To summarise: I need arrays that allow in-place updates.
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.
Thanks and "Viele Gruesse",
Christian
* Duncan Coutts
On Fri, 2010-04-30 at 10:25 -0400, Tyson Whitehead wrote:
On April 30, 2010 06:32:55 Duncan Coutts wrote:
In the last few years GHC has gained impressive support for parallel programming on commodity multi-core systems. In addition to traditional threads and shared variables, it supports pure parallelism, software transactional memory (STM), and data parallelism. With much of this research and development complete, and more on the way, the next stage is to get the technology into more widespread use.
Does this mean DPH is ready for abuse?
This project is about pushing the practical use of the parallel techniques that are already mature, rather than about pushing research projects along further.
So this project is not really about DPH. On the other hand it's possible someone might be able to make more immediate use of the dense, regular parallel arrays which has been a recent spinoff of the DPH project. They have the advantage of being considerably easier to implement, but much less expressive than the full sparse, nested parallel arrays.
Duncan
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