Multithreaded Prexonite

Yesterday, I watched the Google TechTalk presentation of the programming language Go (see Even though I don’t believe Go will become very popular, there was one aspect of the language that “inspired” me. One of Go’s major advantages is the fact that concurrency (and coordination thereof) is built deep into the language. Every function has the potential to become what they call a “goroutine” that works in parallel to all the other code. Communication and coordination is achieved through an equally simple system of synchronous channels (a buffer of size 0).

The code samples all looked so incredibly simple to me that I thought: I can do that too. I started by writing a case study (a code sample) and a sketched implementation of the synchronization mechanisms. It all looked nice on paper (in the Prexonite Script editor) but there was one major problem: None of the Prexonite execution engines is really capable of running on multiple threads. Even though the CIL compiled functions behave nicely, they don’t cover the whole language. Coroutines and other dynamic features are just too important to be ignored.

Fortunately the design of the interpreter is centered around one abstract class: the StackContext. StackContexts come in a variety of forms and provide complete access to the current state of the interpeter. For the most part, these objects are passed around in the call hierarchy. And that’s good, because functions/methods that call each other are in the same thread. So stack contexts stay thread local. At least the ones obtained via method arguments. But there is also another way to get your hands onto stack contexts and that’s the interpreters stack itself.

Of course a multithreaded Prexonite will have multiple stacks but just providing those isn’t enough. I had to ensure that direct queries to/manipulation of the stack are only directed at the stack of the currently executing thread. Since stack contexts are sometimes “captured” by other objects (coroutines for instance), they can on occasion slip into other threads and wreak havoc with the stack of their original thread.

The only solution I saw, was to use thread local storage via unnamed data slots. This has disadvantages, of course:

  • data slots are rather slow (not Reflection slow, but also not virtual call fast)
  • it is difficult to manipulate a different stack if you want to


  • it works!
//name~String, source~Channel
function work(name, source)
    println("\tWhat did $name say again?");
    var a = source.receive;
    println("\t$name said \"$(a)\"");
    return name: a;

function main()
    var source = chan; //Creates a new channel
    println("Get to Work!");
    //`call\async` invokes `work` in the backgrouund
    //`resp` is a channel that will receive the return value of `work`
    var resp = call\async(->work,["Chris",source ]);
    println("Oh, I forgot to tell you this: Chris said Hello!");
    source .send("Hello!"); //supply the missing value
    println("I'm waiting for you to finish...");
    var res = resp.receive;
    println("So your answer is $res then...");
    return 0;

results (sometimes) in

Get to Work!
        What did Chris say again?
Oh, I forgot to tell you this: Chris said Hello!
I'm waiting for you to finish...
        Chris said "Hello!"
So your answer is Chris: Hello! then...

Lists, coroutines and all other kinds of sequences appear very often in Prexonite. It is only logical to combine multithreading with the IEnumerable interface. The result is the `async_seq` command that takes an existing sequence and pushes its computation into a background thread.

The following example applies the two fantasy-functions `sumtorial` and `divtorial` to the numbers 1 through 100. The ordinary `seq` version uses can only use one processor core, while `async_seq` pushes the computation of `sumtorial` into the background and onto the second core. Even though the management overhead is gigantic, a performance improvement can be measured (a modest factor of ~X1.3).

function sumtorial(n) =
    if(n <= 1) 1
    else       n+sumtorial(n-1);
function divtorial(n) =
    if(n <= 1) 1
    else       n/divtorial(n-n/38-1);

function main()
    var n = 100;
    var seq = 
        >> map(->sumtorial)
        >> map(->divtorial);
    println("\t",seq >> sum);

    var par = 
        >> map(->sumtorial)
        >> async_seq
        >> map(->divtorial);
    println("\t",par >> sum);

Multithreaded Prexonite currently lives in its own SVN branch as I am still experimenting with concrete implementations. A very nice improvement would be the move away from CLR threads as they don’t scale well. Communicating sequential processes spend a lot of time waiting for messages, something that does not require its own thread. Go can use 100’000 goroutines and more. I don’t even want to try this with CLR threads…

Discussion Area - Leave a Comment