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auto merge of #6752 : osaut/rust/tutorial-tasks, r=graydon
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* Add a short section and an example illustrating the use of ARC. 
* Header for the section of Future changed to be more descriptive: "Backgrounding computations: Futures".
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bors committed May 28, 2013
2 parents 2061ce9 + dea6677 commit 6d7d759
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73 changes: 72 additions & 1 deletion doc/tutorial-tasks.md
Original file line number Diff line number Diff line change
Expand Up @@ -284,7 +284,7 @@ let result = ports.foldl(0, |accum, port| *accum + port.recv() );
# fn some_expensive_computation(_i: uint) -> int { 42 }
~~~

## Futures
## Backgrounding computations: Futures
With `extra::future`, rust has a mechanism for requesting a computation and getting the result
later.

Expand Down Expand Up @@ -329,6 +329,77 @@ fn main() {
}
~~~

## Sharing immutable data without copy: ARC

To share immutable data between tasks, a first approach would be to only use pipes as we have seen
previously. A copy of the data to share would then be made for each task. In some cases, this would
add up to a significant amount of wasted memory and would require copying the same data more than
necessary.

To tackle this issue, one can use an Atomically Reference Counted wrapper (`ARC`) as implemented in
the `extra` library of Rust. With an ARC, the data will no longer be copied for each task. The ARC
acts as a reference to the shared data and only this reference is shared and cloned.

Here is a small example showing how to use ARCs. We wish to run concurrently several computations on
a single large vector of floats. Each task needs the full vector to perform its duty.
~~~
use extra::arc::ARC;
fn pnorm(nums: &~[float], p: uint) -> float {
(vec::foldl(0.0, *nums, |a,b| a+(*b).pow(p as float) )).pow(1f / (p as float))
}
fn main() {
let numbers=vec::from_fn(1000000, |_| rand::random::<float>());
println(fmt!("Inf-norm = %?", numbers.max()));
let numbers_arc = ARC(numbers);
for uint::range(1,10) |num| {
let (port, chan) = stream();
chan.send(numbers_arc.clone());
do spawn {
let local_arc : ARC<~[float]> = port.recv();
let task_numbers = local_arc.get();
println(fmt!("%u-norm = %?", num, pnorm(task_numbers, num)));
}
}
}
~~~

The function `pnorm` performs a simple computation on the vector (it computes the sum of its items
at the power given as argument and takes the inverse power of this value). The ARC on the vector is
created by the line
~~~
# use extra::arc::ARC;
# let numbers=vec::from_fn(1000000, |_| rand::random::<float>());
let numbers_arc=ARC(numbers);
~~~
and a clone of it is sent to each task
~~~
# use extra::arc::ARC;
# let numbers=vec::from_fn(1000000, |_| rand::random::<float>());
# let numbers_arc = ARC(numbers);
# let (port, chan) = stream();
chan.send(numbers_arc.clone());
~~~
copying only the wrapper and not its contents.

Each task recovers the underlying data by
~~~
# use extra::arc::ARC;
# let numbers=vec::from_fn(1000000, |_| rand::random::<float>());
# let numbers_arc=ARC(numbers);
# let (port, chan) = stream();
# chan.send(numbers_arc.clone());
# let local_arc : ARC<~[float]> = port.recv();
let task_numbers = local_arc.get();
~~~
and can use it as if it were local.

The `arc` module also implements ARCs around mutable data that are not covered here.

# Handling task failure

Rust has a built-in mechanism for raising exceptions. The `fail!()` macro
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