There's some cool Julia features in the NEWS files I thought I'd highlight. Very brief stuff but good to note.

The Memory type for arrays

You can read more about the design of this feature here. It's a really good design doc and I'd recommend taking a look. I've summarized it here, but please check it out for a much more thoughtful treatment. Thanks to Oscar Smith for the work.

Array types are powerful + general, but have a few shortcomings:

The Memory type is out, which is a low-level type that is intended to address some of this stuff. Some performance improvements:

The system image is a little larger.

Lockable for carrying locks with resources

A common pattern when working with multithreaded code is to use a lock to protect a value from multiple threads accessing it at the same time. For example, you might do something like

x = [1,2,3]
lck = Threads.SpinLock()

Threads.@threads for i in 1:100
    position = i % 3 + 1
    lock(lck) do
        x[position] += 1
    end
end

The above code is safe because the lock function ensures that only one thread can access the x array at a time – no data races.

Lockable is a super convenient feature where you can attach a lock to a resource, so you don't have to worry about managing the lock yourself. Here's an example:

z = Lockable([1,2,3], Threads.SpinLock())
Threads.@threads for i in 1:100
    position = i % 3 + 1
    lock(z) do x
        x[position] += 1
    end
end

Notice that now we're just using lock on the raw resource z and the lock is managed for us. This is a nice feature because it makes the code cleaner and easier to read.

The public keyword

The public keyword is applied to symbols that are considered part of the public API of a module, but are not exported when you call using. This is part of the wider discussion in the Julia community that exporting everything is not always the best idea – there's been a lot of clutter and such with people being trigger-happy about exports. Thanks to Lilith Hafner for the work.

As an example, you might have a module like

module MyModule

export foo, bar

foo() = println("foo")
bar() = println("bar")
baz() = println("baz") # not exported, have to use MyModule.baz()

end # module

when you using MyModule, you get foo and bar directly accessible:

julia> using MyModule

julia> foo()
foo

julia> bar()
bar

julia> MyModule.baz()

Now, you'll be able to use public functions like foo and bar without having to export them. This is a nice feature because it allows you to keep your module clean and not export everything.

module MyModule

public foo
export bar

foo() = println("foo")
bar() = println("bar")
baz() = println("baz") # not exported, have to use MyModule.baz()

end # module

Now you'd have the following behavior:

julia> using MyModule

julia> MyModule.foo() # have to use MyModule.foo() because it's not exported
foo

julia> bar() # can use bar() directly, as it is exported
bar

julia> MyModule.baz() # no change
baz

I'm curious to see how the community will use this stuff. I'm not sure it's immediately obvious to me how I'll use it, but it seems like standard engineering practice.

The :greedy thread scheduler

You can now use a greedy thread scheduler, which greedily works on iterator elements as they are produced. Greedy threads simply take the next available task in an iterator without regard to how hard the task is, how many threads there are, etc. If you have a lot of tasks that are all about the same difficulty, greedy scheduling can be a good choice.

Threads.@threads :greedy for i in 1:100
    println(i)
end

Julia has the other scheduling options :dynamic and :static, which are more sophisticated and can be more efficient in some cases. :static will partition the iterator into chunks and assign each chunk to a thread, while :dynamic will dynamically allocate small chunks to threads. :dynamic is the default scheduler, but I suspect :greedy will be useful in some repeated, small multithreading tasks.

The PR is here. Thanks to Valentin Bogad/Sukera.

Cameron Pfiffer. Last modified: April 10, 2024. Website built with Franklin.jl and the Julia programming language.