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switch to parallel coding

Solutons:


I think the most important requirement is a good language that has native constructs that support parallelism or one that can automatically generate parallel code. There are quite a few languages that fit that description, but none of them is popular enough to really be considered for mainstream use. That, in turn is caused by several things:

  1. By their very nature, these languages are very different from today’s imperative languages, and are therefor harder to learn (or at least seem that way).
  2. They often lack good tools and libraries, making them unusable for any “real” project.

Of course, if it were more popular more people would be willing to learn it and there would be more support, so it’s a kind of cycle that’s pretty hard to break out of. I guess all we can do is hope. 🙂

An example of a language designed with heavy parallelization in mind is Erlang – and it’s actually used in commercial projects.

What we need are natural abstractions for highly-concurrent algorithms. Actors (think: Erlang) go a long way in this direction, but they aren’t a one-size-fits-all solution. Some more specific abstractions like fork/join or map/reduce can be even easier to apply to common problems.

The trick with all of these concurrency abstractions is they require functional-style programming. Concurrency doesn’t mesh well with shared mutable state. As they say, “Locks considered harmful”. Since most developers come from a strictly imperative background, switching to a shared-nothing continuation passing approach is often extremely challenging.

Incidentally, with respect to concurrency abstractions, Clojure has some very interesting features in this direction. Not only does it have sort-of actors, but it also defines a transactional memory model (think: databases) along with a global, atomic references mechanism. These two features allow concurrent operations to share “mutable” state without ever having to worry about locking or race conditions.

In the end, it comes down to education. Much of the needed theoretical work into concurrency abstractions has already been done, we just need to accept it. Unfortunately, as Erlang and Haskell prove, sometimes the best ideas remain relegated to an extremely fringe demographic. Hopefully efforts like Scala and Clojure will succeed in bringing the more advanced abstractions into the mainstream by sneaking them onto an existing, well-supported platform (the JVM).

Unfortunately for massive concurrent programming – unless there is a breakthrough in compilers to help, we will be throwing out a lot of what we know about algorithms (I think Don Knuth even said that). Read about Erlang for a glimpse of this possible future.

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