On 01/15/2013 12:51 AM, Martin Drautzburg wrote:

What would be a good way to represent a Network anyways? I believe the classic
approach is a list of nodes and a list vertices. In the simulation I will
frequently have to find the process of an input or output and to find the
input connected to an output. The node/vertices implementation seems to
require scanning lists, which could be slow once I have thousands of
processes.

Other than that any pointers to how to construct networks (which go beyond
mere graphs) would be much appreciated.

Hello Martin,
I guess the exact way depends on what precisely you want to achieve. I'm thinking about two options, hope others will suggest more. Either you try to model it in a pure setting or you go into IO.

In a former case you may try to make use of lazy streams, say function of type
f :: [a] -> [b] -> [c]
is basically your's processing unit which takes two inputs and produces one output.
For example, this is an integrator:

f1 xs ys = zipWith (+) xs ys
summer xs = let ret = f1 xs ys
                ys = 0 : ret
            in ret

Here you depend on mutually recursive bindings in order to form the loops, so you can't make a dynamic structures this way, I believe.

Speaking about IO, you may either go the classic boring way by collecting all the outputs in some mutable data structure and updating them in a loop, or you may try to have some fun with GHC's green threads:

import Control.Monad
import Control.Concurrent
import Control.Concurrent.MVar

mkBinaryF f i1 i2 = do
  ret <- newEmptyMVar

  let worker = do
        v1 <- i1
        v2 <- i2
        res <- f v1 v2
        putMVar ret res
  forkIO $ forever worker
  return (takeMVar ret)

main = do
  inp2 <- newMVar 0
  out <- mkBinaryF (\x y -> return $ x + y) (getLine >>= return . read) (takeMVar inp2)

  forever $ do
    v <- out
    putStrLn $ "out: " ++ show v
    putMVar inp2 v

For a more theoretically backed approach I suggest you to look at CSP. http://www.cs.kent.ac.uk/projects/ofa/chp/

Best wishes,
Dmitry

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