[Haskell-cafe] Re: Can you do everything without shared-memory concurrency?

Bruce Eckel wrote:

So this is the kind of problem I keep running into. There will seem to be consensus that you can do everything with isolated processes message passing (and note here that I include Actors in this scenario even if their mechanism is more complex). And then someone will pipe up and say "well, of course, you have to have threads" and the argument is usually "for efficiency."

I make two observations here which I'd like comments on:

1) What good is more efficiency if the majority of programmers can never get it right? My position: if a programmer has to explicitly synchronize anywhere in the program, they'll get it wrong. This of course is a point of contention; I've met a number of people who say "well, I know you don't believe it, but *I* can write successful threaded programs." I used to think that, too. But now I think it's just a learning phase, and you aren't a reliable thread programmer until you say "it's impossible to get right" (yes, a conundrum).

(welcome Bruce!) Let's back up a bit. If the goal is just to make something go faster, then threads are definitely not the first tool the programmer should be looking at, and neither is message passing or STM. The reason is that threads and mutable state inherently introduce non-determinism, and when you're just trying to make something go faster non-determinism is almost certainly unnecessary (there are problems where non-determinism helps, but usually not). In Haskell, for example, we have par/seq and Strategies which are completely determinstic, don't require threads or mutable state, and are trivial to use correctly. Now, getting good speedup is still far from trivial, but that's something we're actively working on. Still, people are often able to get a speedup just by using a parMap or something. Soon we'll have Data Parallel Haskell too, which also targets the need for deterministic parallelism. We make a clean distinction between Concurrency and Parallelism. Concurrency is a _programming paradigm_, wherein threads are used typically for dealing with multiple asynchronous events fromm the environment, or for structuring your program as a collection of interacting agents. Parallelism, on the other hand, is just about making your programs go faster. You shouldn't need threads to do parallelism, because there are no asynchronous stimuli to respond to. It just so happens that it's possible to run a concurrent program in parallel on a multiprocessor, but that's just a bonus. I guess the main point I'm making is that to make your program go faster, you shouldn't have to make it concurrent. Concurrent programs are hard to get right, parallel programs needn't be. Cheers, Simon

2) What if you have lots of processors? Does that change the picture any? That is, if you use isolated processes with message passing and you have as many processors as you want, do you still think you need shared-memory threading?

A comment on the issue of serialization -- note that any time you need to protect shared memory, you use some form of serialization. Even optimistic methods guarantee serialization, even if it happens after the memory is corrupted, by backing up to the uncorrupted state. The effect is the same; only one thread can access the shared state at a time.

On Tue, Sep 9, 2008 at 4:03 AM, Sebastian Sylvan mailto:sebastian.sylvan@gmail.com> wrote:

On Mon, Sep 8, 2008 at 8:33 PM, Bruce Eckel mailto:bruceteckel@gmail.com> wrote:

As some of you on this list may know, I have struggled to understand concurrency, on and off for many years, but primarily in the C++ and Java domains. As time has passed and experience has stacked up, I have become more convinced that while the world runs in parallel, we think sequentially and so shared-memory concurrency is impossible for programmers to get right -- not only are we unable to think in such a way to solve the problem, the unnatural domain-cutting that happens in shared-memory concurrency always trips you up, especially when the scale increases.

I think that the inclusion of threads and locks in Java was just a knee-jerk response to solving the concurrency problem. Indeed, there were subtle threading bugs in the system until Java 5. I personally find the Actor model to be most attractive when talking about threading and objects, but I don't yet know where the limitations of Actors are.

However, I keep running across comments where people claim they "must" have shared memory concurrency. It's very hard for me to tell whether this is just because the person knows threads or if there is truth to it.

For correctness, maybe not, for efficiency, yes definitely!

Imagine a program where you have a huge set of data that needs to be modified (in some sense) over time by thousands of agents. E.g. a game simulation. Now, also imagine that every agent could *potentially* modify every single piece of data, but that every agent *typically* only touches two or three varibles here and there. I.e. the collisions between the potential read/write sets is 100%, while the collisions for the actual read/write sets is very very low.

How would you do this with threads and message passing? Well you could have one big thread owning all of your data that takes "update" messages, and then "updates" the world for you (immutably if you wish, by just replacing its "world" variable with a new one containing your update), but now you've effectively serialized all your interactions with the "world", so you're not really concurrent anymore!

So you could decompose the world into multiple threads using some application-specific logical sudivision, but then you're effectively just treating each thread as a mutable variable with an implicit lock (with the risks of deadlock that comes with it - remember we don't know the read/write set in advance - it could be the entire world - so we can't just order our updates in some global way here), so you're really just doing shared mutable state again, and gain little from having threads "simulate" your mutable cells...

What you really need for this is some way for each agent to update this shared state *in parallel*, without having to block all other agents pessimistically, but instead only block other agents if there was an *actual* conflict. STM seems to be the only real hope for that sort of thing right now. IMO my list of preferred methods goes like this: 1. Purely functional data parallelism 2. Purely functional task parallelism (using e.g. strategies) 3. Message passing with no (or very minimal) shared state (simulated using threads as "data servers" or otherwise) (3.5. Join patterns? Don't have enough experience with this, but seems sort of nice?) 4. Shared state concurrency using STM 5. Shared state concurrency using locks 6. Lockless programming.

So while I wouldn't resort to any shared state concurrency unless there are good reasons for why the other methods don't work well (performance is a good reason!), there are still situations where you need it, and a general purpose language had better supply a way of accessing those kinds of facilities.

-- Sebastian Sylvan +44(0)7857-300802 UIN: 44640862

-- Bruce Eckel

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