Actors on the JVM

The [[Actor Model]] is an interesting alternative to the standard threading model used in languages like Java. Its been around for a while, but Erlang has recently brought it into the mainstream. Roughly speaking, an actor corresponds to a Thread, except that actors do not share state. Actors communicate by sending messages, and [[Synchronization (computer science)|Synchronisation]] is implicit because an actor can only process one message at a time. Thus, a message is queued until the actor is free and can process it.

There are several examples of actors being implemented on top of the JVM, including Kilim (see also [1][2][3]) and Erjang (see also [1][2][3]). These systems implement actors on top of JVM threads in a many-to-one fashion, where several actors can map onto a single thread at any given moment. This requires the ability to interrupt a thread at certain points, in order to allocate it to another actor — in otherwords, time-slicing several actors across a thread. Unfortunately, the JVM does not provide any explicit mechanism for restarting threads at different bytecode locations, or for saving their state — that is, it does not provide support for arbitrary [[Continuation|continuations]].

To work around the limitations of the JVM, systems like Kilim and Erjang intersperse special “pause” points throughout methods executed by actors. A pause point is essentially a point where the executing thread checks whether or not it’s time to switch to a different actor: if so, the thread “backs out” of the current method by unwinding the stack, saving all necessary state (essentially, the contents of local variables) as it goes. Once this is completed, the thread chooses another actor to execute, and “unpauses” it by winding its saved state back onto the stack.

The following recursive method illustrates the main ideas:

int height(Node n) {
 int left = height(n.left());
 int right = height(n.right());

 if(left < right) { return right; }
 else { return left; }

A system like Kilm will rewrite this method to insert pause points, producing something (very roughly) as follows:

Object height(Node n, StackFrame stack) {
 Frame frame = null;
 int pc = 0;
 if(!stack.isEmpty()) {
  frame = stack.pop();
  pc = frame.pc();
 switch(pc) {
 case 0:
   Object tmp = height(n.left(),stack);
   if(tmp instanceof StackFrame) {
    stack.put(new StackFrame(0));
    return stack;
 case 1:
   int left = (Integer) frame.get(0);
   Object tmp = height(n.right(),stack);
   if(tmp instanceof StackFrame) {
    stack.put(new StackFrame(1,left));
    return stack;
 case 2:
   int right = (Integer) frame.get(1);
   if(left < right) { return right; }
   else { return left; }

Overall, it’s pretty messy! In practice, there’s quite a bit more to it, including several optimisation opportunities. But, hopefully, you get the picture — we’re essentially dividing the method up into points that we can quickly restore from.

There are quite a few questions left here. In particular, where do we put the pause points? Kilim, for example, always puts them at calls sites to other methods (in fact, it uses a special annotation to indicate which methods are @pausable). This approach means, for example, that a loop could contain no pause points and, hence, must run to completion without being interrupted (and, as with [[nonpremptive multitasking]], if that loop does not terminate then neither will the actor). This seems less than ideal, but at the same time there doesn’t seem to be a better alternative.


Putting aside the question of where to locate pause points, there’s another issue which has been vexing me for a while:  how do we gain from this form of concurrency? It seems to me there are two possibilities:

  • I/O Bound. If we have a situation where threads are often blocked on I/O, then getting them to continue executing other actors at these times would be beneficial. The problem is that it seems unclear to me how this could be implemented because, once a thread has blocked inside an I/O method, then it’s really stuck.  Perhaps, by using non-blocking I/O, this could be achieved.  Or, possibly, by creating one or more I/O threads which are actually responsible for reading/writing I/O and, hence, could be allowed to block.  The downside being that, if we had only one I/O thread, then this would sequentialise all I/O operations; alternatively, having many I/O threads would unnecessarily burden the system.
  • Lock Contention. Alternatively, if we have a situation where there is a lot of contention over some shared resource (i.e. where threads are often blocked waiting on a lock), then getting them to execute on behalf of other actors at these times could also be beneficial.  This seems more doable to me, as it just requires the lightweight thread scheduler to get access at the point of a message send.  Then, if the receiver is currently blocked processing some other message, the scheduler can direct the executing thread to pause the current actor (i.e. the sender).

My conclusion from thinking about this, is that there’s little or no advantage from blocking actors unless they either: explicitly invoke an I/O operation, or send a message which cannot immediately be processed.  So, it’s not really multi-tasking in the way that I think about multi-threading — it’s quite different, and much more specific.

Comments welcome!

5 comments to Actors on the JVM

  • Chris Lewis

    You might be interested in Akka for Scala, which tries to implement actors on the JVM. Clojure also does it, using Java’s Future class thingers.

    I’ve been playing with Erlang for the last couple of weeks, and its fairly clear that the popular JVM languages just aren’t designed to work like Erlang. Only Erlang works like Erlang: spawn thousands of processes to do your computational bidding, monitor them, then return their results. It requires a different programming paradigm. Clojure and Scala/Akka do let you do this, but you’d have to be careful not to introduce things that will break that paradigm; Erlang’s syntax is so limited it won’t let you do silly things (although I suspect it won’t let you do many powerful things either).

    Once I’m done with Erlang, I’ll go and try out Akka to see how well that works. I’ve not been able to find good speed tests that compare the two.

  • Hey Chris!

    Akka … interesting, I had heard of it before, but I forgot about it! I’ve got a student doing some work on implementing actors on the JVM (for whiley), so I’ll put him onto that.

    So, what about Erjang then … have you tried that? I’m interested in how it performs on realistic benchmarks …

    Why the interest in Actor systems anyhow? I thought that would be a little off-topic for you …

  • Lawrence Kesteloot


    I think the cost of switching a real O/S thread is less than the cost of these green threads, based on your explanation. The only time you’d really want to avoid real threads is when you have many thousands of them, such as when you hold on to long-poll HTTP connections, in which case you just want to put the TCP connections into some kind of data structure anyway. So I don’t really see the point of these, even for the two cases you mention.

  • Chris Lewis

    No idea re: Erjang. I did some quick Akka testing on my Mac earlier. Spawned 100 000 actors, send them two sync’d messages and two async’d messages. It completed in ~30 seconds, which I think it pretty good!

    The Actor model is not necessarily my wheelhouse, no, but the fault-tolerant stuff is. Here’s a stupid example I coded up: , which roughly follows

    If you look at line 62, I intentionally send a message that kills the process (look for the OH GOD exception in the output log). Akka then restarts the process and the other messages are processed. It’s really cool.

  • Hi Lawerence,

    Well, one of the problems with native threads is that you are typically limited in how many you can create. The problem here is that, when using the Actor model, you essentially replace all objects with Actors … meaning you can end up with potentially quite a lot (i.e. millions) of Actors.

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