If you can't make a language fast, make it parallel
blog.cyll.org
blog.cyll.org
Others like Clojure and Scala have more support at the standard library level.
Clojure has deep language support for concurrency - from syntactical constructs to it's core performant immutable data structures.
The only exception is the deref reader macro "@", since Clojure doesn't allow user-defined reader macros by default.
This is not true at present. The core data structures, and the STM machinery are implemented in java, not as macros.
I don't understand how. The only difference I see is whether the interprocess communication parts are coded into the language itself or whether they're coded into a library. It could theoretically make the problem more difficult to put it in the language itself. Instead of only affecting the programs that use that library, now your concurrency features could potentially affect any program written in your language.
Could you give me an example of a concurrency feature that really, truly benefits from being in the language and not the standard library? I simply can't think of any examples.
Isn't that a bit of a loaded question? In some academic sense, an ideal programming system might have a kernel language that is probably rather small and certainly clean, flexible and extensible in its feature set, and then almost everything else built on top of that kernel in libraries. In practical programming systems, the perfect kernel has proven rather elusive, though.
It's rather like the question of whether a standard library should be small, clean and extensible or comprehensive with a good-enough version of everything. Many of us might be inclined toward the former approach from an academic/theoretical/intuitive point of view, but in practice, just about every widely used programming language from the past two decades has come with a batteries-included library. While those libraries are often criticised for various technical weaknesses, and many of those weaknesses are never addressed because it's too much work, these systems are still good enough for most users out of the box.
Erlang has that, because it has its datatypes and a defined serialization for them and there is nothing in the language that is not those datatypes. It also doesn't permit you to layer any type-level assertions about those types into a user type. In fact, Erlang basically has no concept of user types. (Records are syntax sugar around the built-in tuple.) Since the Erlang data types are so weak, an automated serialization can be built that requires no work to use. But that doesn't come without cost
If you don't start with that, you have to use some sort of introspection to examine data types, and you probably don't have a good story for what to do if two ends have totally different ideas about those datatypes, or how to upgrade running processes where you literally want to change the datatype without shutting the process down. The stronger your type system, the harder that gets. The easier it is, the weaker your type system must be. Erlang's capabilities don't come for free, they exist because they wrote their (non-)type system so that their data structures never have any guarantees in them that don't trivially travel across the network. This has its own issues; Erlang has just about the weakest types you can have without actually having arbitrary casts, and that has consequences too.
There are a handful of characteristics in a language, like its type system, that have radical impacts throughout the language and no amount of library jiggery-pokery can completely paper over. Another example not entirely relevant to cross-process concurrency (but not entirely irrelevant) is immutability; no amount of library work can turn a mutable language into an immutable language.
I've been attempting to work with GWT and the serialization issues are entertaining (did you implement IsSerializable? is there a no-arg constructor? Do all of the classes your class depend on have the same? Did you remember to recompile the GWT/JS code to update the serialization white list? etc.).
It makes me appreciate more playing with Erlang a while back and shooting data around being so simple.
We've gotten comfortable enough with our concurrency model, that we felt it deserved to be in the language.
As an aside, some features that benefit parallelism can be tricky to add retroactively, although possible (like an N:M threading model).
Does Spin address this issue?
On p.173 Joe writes:
When we say things such as this:
Pid = register(...),
on_exit(Pid, fun(X) -> ..),
there is a possibility the process dies in the gap between these two statements.
Regarding process death, we allow multiple inter-process relationships to be specified at spawn time. Hence any number of processes may be configured to observe a newly-spawned process before it has even started. Additionally, all children are linked to (die with) their parent, which both eliminates the risk of orphaned processes and has other benefits.So in Spin you wouldn't be tempted to write something like above (probably not Erlang either?).
A bit further discussion: http://news.ycombinator.com/item?id=939364
And a whole pile of others.
Did you use a parallel programming language?
Not to detract from anything you said (which I agree with), but when Guy Steele gave a guest lecture at my university on Fortress a few months ago, he said that the work splitting algorithm still needed work, in particular the part that decided the right amount of granularity for the given task (i.e. when to stop splitting the task into smaller subtasks).
1. built-in distribution (i.e. Erlang distributed RPC)
2. bit-syntax
3. light-weight processes
4. pattern-matching
For example - there does not exist a practical language (or design) where you can implement the LZ compression (ZLIB, others) in parallel, so that it gives the same results as the sequential "c" version.
It's just that certain algorithms, hence protocols, data structures, standards are not suited for parallel processing that well.
Okay, in the first case, maybe you can split the incoming data by 128kb and process each other individually ... but that's not the same - you can't reuse the LZ window.
Really the problem is the 13 dwarfs that university folks have identified - 13 stereotypical problems that relate to 99% of what's being done with a programming language - some of the dwarfs are just speedy parallel gnomes, some of them are old slow stubborn, like Gimli from LOTR.
http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-18...
Hasn't there been a few parallel implementations of bzip2?
http://bzip2smp.sourceforge.net/
I understand that parallelism isn't suited for a lot of algorithms but from what I can tell, there's been heaps of successful work in compression. Could you give us some more information?
It would really help me out - I'm doing an undergraduate class where I have to manually make an open-source project parallel. I've been looking into compression algorithms because I thought they were well suited. Please help me out if I'm going down the wrong path!
The trick is to start at the largest chunk possible and go down until you find where they have left in some, uh, non-dependencies - like bzip2 which has independent x*100KB blocks, and video which (usually) has independent frames. You should be able to get 2-4 separate tasks out of that, which is good enough for CPUs.
Sure, but for problems that can be parallelized you want a language to be able to express that parallelism. That may sound obvious, but many popular languages cannot do it. Let's not just give up on parallelism because it can't be used everywhere.
Let's not underestimate the help that a language can provide; writing interpreters for languages is almost trivial on a lisp because you can reuse pretty much every piece of machinery on a lisp for your ends. Similarly, there is an entire class of problems that is nearly trivial on prolog that is pretty difficult to get right on other languages simply because prolog makes it easy to express rules and specifications that need to be met. Just look at an implementation of a sudoku solver in prolog and compare it with some other language.
I feel that a language designed with concurrency in mind would make it much simpler to write an entire class of problems. These languages are just gaining traction, so we are yet to see bigger and more significant examples. However, the "ants.clj" demo that Rich Hickey has written in Clojure, and some of the erlang demos in Joe Armstrong's book have made me a believer.
I'm sharing one of the lessons we learned building our own programming language. I love how many language designers there are on HN!
We're working on an invite system, so everyone can benefit from Skynet! Skynet is better when you use it with others, so the invites will work for groups of friends.