flesh out atomics

pull/10/head
Alexis Beingessner 9 years ago committed by Manish Goregaokar
parent 7851f27cb6
commit 37228b9d7d

@ -7,27 +7,138 @@ it is a pragmatic concession to the fact that *everyone* is pretty bad at modeli
atomics. At very least, we can benefit from existing tooling and research around
C.
Trying to fully explain the model is fairly hopeless. If you want all the
nitty-gritty details, you should check out [C's specification][C11-model].
Still, we'll try to cover the basics and some of the problems Rust developers
face.
Trying to fully explain the model in this book is fairly hopeless. It's defined
in terms of madness-inducing causality graphs that require a full book to properly
understand in a practical way. If you want all the nitty-gritty details, you
should check out [C's specification][C11-model]. Still, we'll try to cover the
basics and some of the problems Rust developers face.
The C11 memory model is fundamentally about trying to bridge the gap between C's
single-threaded semantics, common compiler optimizations, and hardware peculiarities
in the face of a multi-threaded environment. It does this by splitting memory
accesses into two worlds: data accesses, and atomic accesses.
The C11 memory model is fundamentally about trying to bridge the gap between
the semantics we want, the optimizations compilers want, and the inconsistent
chaos our hardware wants. *We* would like to just write programs and have them
do exactly what we said but, you know, *fast*. Wouldn't that be great?
# Compiler Reordering
Compilers fundamentally want to be able to do all sorts of crazy transformations
to reduce data dependencies and eleminate dead code. In particular, they may
radically change the actual order of events, or make events never occur! If we
write something like
```rust,ignore
x = 1;
y = 3;
x = 2;
```
The compiler may conclude that it would *really* be best if your program did
```rust,ignore
x = 2;
y = 3;
```
This has inverted the order of events *and* completely eliminated one event. From
a single-threaded perspective this is completely unobservable: after all the
statements have executed we are in exactly the same state. But if our program is
multi-threaded, we may have been relying on `x` to *actually* be assigned to 1 before
`y` was assigned. We would *really* like the compiler to be able to make these kinds
of optimizations, because they can seriously improve performance. On the other hand,
we'd really like to be able to depend on our program *doing the thing we said*.
# Hardware Reordering
On the other hand, even if the compiler totally understood what we wanted and
respected our wishes, our *hardware* might instead get us in trouble. Trouble comes
from CPUs in the form of memory hierarchies. There is indeed a global shared memory
space somewhere in your hardware, but from the perspective of each CPU core it is
*so very far away* and *so very slow*. Each CPU would rather work with its local
cache of the data and only go through all the *anguish* of talking to shared
memory *only* when it doesn't actually have that memory in cache.
After all, that's the whole *point* of the cache, right? If every read from the
cache had to run back to shared memory to double check that it hadn't changed,
what would the point be? The end result is that the hardware doesn't guarantee
that events that occur in the same order on *one* thread, occur in the same order
on *another* thread. To guarantee this, we must issue special instructions to
the CPU telling it to be a bit less smart.
For instance, say we convince the compiler to emit this logic:
```text
initial state: x = 0, y = 1
THREAD 1 THREAD2
y = 3; if x == 1 {
x = 1; y *= 2;
}
```
Ideally this program has 2 possible final states:
* `y = 3`: (thread 2 did the check before thread 1 completed)
* `y = 6`: (thread 2 did the check after thread 1 completed)
However there's a third potential state that the hardware enables:
* `y = 2`: (thread 2 saw `x = 2`, but not `y = 3`, and then overwrote `y = 3`)
```
It's worth noting that different kinds of CPU provide different guarantees. It
is common to seperate hardware into two categories: strongly-ordered and weakly-
ordered. Most notably x86/64 provides strong ordering guarantees, while ARM and
provides weak ordering guarantees. This has two consequences for
concurrent programming:
* Asking for stronger guarantees on strongly-ordered hardware may be cheap or
even *free* because they already provide strong guarantees unconditionally.
Weaker guarantees may only yield performance wins on weakly-ordered hardware.
* Asking for guarantees that are *too* weak on strongly-ordered hardware
is more likely to *happen* to work, even though your program is strictly
incorrect. If possible, concurrent algorithms should be tested on
weakly-ordered hardware.
# Data Accesses
The C11 memory model attempts to bridge the gap by allowing us to talk about
the *causality* of our program. Generally, this is by establishing a
*happens before* relationships between parts of the program and the threads
that are running them. This gives the hardware and compiler room to optimize the
program more aggressively where a strict happens-before relationship isn't
established, but forces them to be more careful where one *is* established.
The way we communicate these relationships are through *data accesses* and
*atomic accesses*.
Data accesses are the bread-and-butter of the programming world. They are
fundamentally unsynchronized and compilers are free to aggressively optimize
them. In particular data accesses are free to be reordered by the compiler
them. In particular, data accesses are free to be reordered by the compiler
on the assumption that the program is single-threaded. The hardware is also free
to propagate the changes made in data accesses as lazily and inconsistently as
it wants to other threads. Mostly critically, data accesses are where we get data
races. These are pretty clearly awful semantics to try to write a multi-threaded
program with.
to propagate the changes made in data accesses to other threads
as lazily and inconsistently as it wants. Mostly critically, data accesses are
how data races happen. Data accesses are very friendly to the hardware and
compiler, but as we've seen they offer *awful* semantics to try to
write synchronized code with.
Atomic accesses are the answer to this. Each atomic access can be marked with
an *ordering*. The set of orderings Rust exposes are:
Atomic accesses are how we tell the hardware and compiler that our program is
multi-threaded. Each atomic access can be marked with
an *ordering* that specifies what kind of relationship it establishes with
other accesses. In practice, this boils down to telling the compiler and hardware
certain things they *can't* do. For the compiler, this largely revolves
around re-ordering of instructions. For the hardware, this largely revolves
around how writes are propagated to other threads. The set of orderings Rust
exposes are:
* Sequentially Consistent (SeqCst)
* Release
@ -36,11 +147,80 @@ an *ordering*. The set of orderings Rust exposes are:
(Note: We explicitly do not expose the C11 *consume* ordering)
TODO: give simple "basic" explanation of these
TODO: implementing Arc example (why does Drop need the trailing barrier?)
TODO: negative reasoning vs positive reasoning?
# Sequentially Consistent
Sequentially Consistent is the most powerful of all, implying the restrictions
of all other orderings. A Sequentially Consistent operation *cannot*
be reordered: all accesses on one thread that happen before and after it *stay*
before and after it. A program that has sequential consistency has the very nice
property that there is a single global execution of the program's instructions
that all threads agree on. This execution is also particularly nice to reason
about: it's just an interleaving of each thread's individual executions.
The relative developer-friendliness of sequential consistency doesn't come for
free. Even on strongly-ordered platforms, sequential consistency involves
emitting memory fences.
In practice, sequential consistency is rarely necessary for program correctness.
However sequential consistency is definitely the right choice if you're not
confident about the other memory orders. Having your program run a bit slower
than it needs to is certainly better than it running incorrectly! It's also
completely trivial to downgrade to a weaker consistency later.
# Acquire-Release
Acquire and Release are largely intended to be paired. Their names hint at
their use case: they're perfectly suited for acquiring and releasing locks,
and ensuring that critical sections don't overlap.
An acquire access ensures that every access after it *stays* after it. However
operations that occur before an acquire are free to be reordered to occur after
it.
A release access ensures that every access before it *stays* before it. However
operations that occur after a release are free to be reordered to occur before
it.
Basic use of release-acquire is simple: you acquire a location of memory to
begin the critical section, and the release that location to end it. If
thread A releases a location of memory and thread B acquires that location of
memory, this establishes that A's critical section *happened before* B's
critical section. All accesses that happened before the release will be observed
by anything that happens after the acquire.
On strongly-ordered platforms most accesses have release or acquire semantics,
making release and acquire often totally free. This is not the case on
weakly-ordered platforms.
# Relaxed
Relaxed accesses are the absolute weakest. They can be freely re-ordered and
provide no happens-before relationship. Still, relaxed operations *are* still
atomic, which is valuable. Relaxed operations are appropriate for things that
you definitely want to happen, but don't particularly care about much else. For
instance, incrementing a counter can be relaxed if you're not using the
counter to synchronize any other accesses.
There's rarely a benefit in making an operation relaxed on strongly-ordered
platforms, since they usually provide release-acquire semantics anyway. However
relaxed operations can be cheaper on weakly-ordered platforms.
TODO: implementing Arc example (why does Drop need the trailing barrier?)
[C11-busted]: http://plv.mpi-sws.org/c11comp/popl15.pdf

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