Process networks in CHP do not have to be static. In fact, some of the more interesting examples are dynamic. To illustrate a dynamic process pipeline I will use the example task of generating prime numbers.

One way to find prime numbers is as follows. Start with an empty list of primes, and the integer 2. Check if the integer is divisible by any of the numbers in the list of primes. If yes, discard it. If no, add it to the list. Then try the next integer (i.e. add one), and continue indefinitely. A very simple, if inefficient algorithm. (This is not the Sieve of Eratosthenes — see this paper.)

Let’s see how we can turn this algorithm into a CHP program. Every time we find a prime, we want to add it to our list of numbers to filter out in future. We can implement this list as a concurrent process pipeline — each process in the pipeline will be responsible for filtering out numbers divisible by a single prime. Such a process is quite straightforward:

filterDiv :: Integer -> Chanin Integer -> Chanout Integer -> CHP () filterDiv n input output = forever $ do x <- readChannel input when (x `mod` n /= 0) $ writeChannel output x

Every time we find a prime, we need to add a new filterDiv process on to the end of our pipeline. This may sound difficult, but can be easily expressed with some concurrent recursion:

end :: Chanin Integer -> Chanout Integer -> CHP () end input output = do x <- readChannel input writeChannel output x (filterDiv x |->| end) input output

This process sits at the end of our pipeline and reads in a single value. Since our pipeline is filtering out all non-primes, any number that this “end” process receives must be prime. In response to receiving a prime, it sends it on (to whatever process is waiting beyond the prime pipeline to receive the primes). It then becomes the parallel composition of a new filterDiv process, connected to a new end process (the |->| operator expresses this composition). Thus every time a new prime comes out of the end of the pipeline, the pipeline grows by one more process. After the 100th prime, the pipeline will consist of 100 filterDiv processes executing concurrently, and one “end” process.

To complete our pipeline, we need a process at the beginning of the pipeline, supplying an ever-increasing stream of numbers on its output channel, starting at 2:

genStream :: Chanout Integer -> CHP () genStream output = mapM_ (writeChannel output) [2..]

We can now write a primes process that generates a list of prime numbers. Using another helpful operator from the CHP library, this is easy:

primes :: Chanout Integer -> CHP () primes = genStream ->| end

Observe that there is no mention of filterDiv. The pipeline starts out with the stream generator and an end process. All the filterDiv processes are added once the primes start coming out of the pipeline, beginning with 2, as shown in the diagram below:

Note also that the interface of primes is simply Chanout Integer -> CHP (); all the internal details of the expanding concurrent pipeline are hidden from the outside, leaving only an opaque box:

To make a complete program, we can compose this in parallel with a process responsible for printing the primes:

main :: IO () main = runCHP_ $ do c <- oneToOneChannel primes (writer c) <||> (forever $ readChannel (reader c) >>= (liftIO . putStrLn . show))

The expanding pipeline is not restricted to conceptual examples such as generating the primes, and the powerful idea of a process becoming the parallel composition of sub-processes is not restricted to pipelines — two things that I hope to explore in future.