Trying to understand atomics by just reading random articles and the documentation in Rust (or C++ for that matter) feels like trying to learn physics by reverse engineeringE=MC^2.

I'll give it my best try to explain this for myself and for you in this article. If I succeed, the ratio should be WTF?/AHA! < 1. Let me know in the issue tracker of the repository for this article how we did.

Multiprocessor programming

When writing code for multiple CPUs, there are several subtle things we need to consider. You see, both compilers and CPU's reorder the code we write if they think it will lead to faster execution. In single threaded programs, this is not something we need to consider, but once we start writing multithreaded programs, the compiler reordering can get us into trouble.

However, while the compiler ordering is possible to check by looking at the disassembled code, things get much more difficult on systems with multiple CPUs.

When threads are run on different CPUs, the internal reordering of instructions on the CPU can lead to some very hard to debug problems since we mostly observe the side effects of CPU reordering, speculative execution, pipelining and caching.

I don't think the CPU knows in advance exactly how it's going to run your code either.

Let's start at the bottom and work our way up to a better understanding.

Strong vs Weak Memory Ordering

So to start off, we need to get some concepts right. CPUs give different guarantees when it comes to how they treat memory. We can classify them from Weak to Strong. However, it's not a precise specification so there are models which are somewhere in between.

To abstract over these differences, Rust has the concept of an abstract machine. It borrows this model from C++. This abstract machine needs to be an abstraction which makes it possible to program against weak and strong CPUs (and everything in between).

You see, the C++ abstract machine specifies many ways to access memory. It kind of has to if we're supposed to use the same semantics for weak and strong processors in the same language.

A CPU with a strong memory model gives some important guarantees that make much of the semantics we use in the abstract machine no-ops. It does nothing fancy at all, and is only a hint to the compiler to not change the order of memory operations from what we as programmers wrote.

On a weak system however, it might need to set up memory fences or use special instructions to prevent synchronization issues. The best way to learn this abstract machine using experiments would be using a CPU with a weak ordering. However, since most programmers program on a CPU with a strong model, we'll just have to point out the differences so we understand why the semantics are the way they are.

Most current desktop CPUs from AMD and Intel uses strong ordering. That means that the CPU itself gives some guarantees about not reordering certain operations. Some examples of this guarantee can be found in Intels Developer Manual, chapter 8.2.2:

• Reads are not reordered with other reads.

• Writes are not reordered with older reads.

• Writes to memory are not reordered with other writes (with some exceptions)

Critically, it also includes one non-guarantee:

• Reads may be reordered with older writes to different locations but not with older writes to the same location.

This last one will be important to understand SeqCst memory ordering later on, just make a note of it for now.

Now, in the following chapters, I'll try to be clear on these differences. I'll still use the weak model of the abstract machine as the basis for the explanations however...

CPU Caches

Normally, a CPU has three levels of caching: L1, L2, and L3. While L2, and L3 are shared between cores, L1 is a per core cache. Our challenges start here.

The L1 cache uses a sort of MESI caching protocol. While the name might sound mysterious, it's actually pretty simple. It is an acronym for the different states items in the cache can find themselves in:

These states apply to each cache line in the L1 cache:
​
(M) Modified - modified (dirty). Need to write back data to main memory.
(E) Exclusive - only exists in this cache. Doesn't need to be synced (clean).
(S) Shared - might exist in other caches. Is current with main memory (clean).
(I) Invalid - cache line is invalid. Another cache has modified it.

Ok, so we can model this for ourselves by thinking that every cache line in the CPU has an enum with four states attached to them.

Inter-processor Communication

So, if we really do need to access and change memory which is Shared how do the other cores know that their L1 cache is invalid?

Well, a cache line is invalidated if the data exists in the L1 cache on a different core (remember, it's in theSharedstate) and is modified there. To actually inform the other cores that their cached data is invalid, there must be some way for the cores to communicate with each other, right?

Yes there is, however, it's pretty hard to find documentation about the exact details. Each core has what we can think of as a mailbox.

This mailbox can buffer a certain number of messages. Each message is buffered here to avoid interrupting the CPU all the time and force it to handle every message sent from other cores immediately.

Now, at some point the CPU checks this mailbox and updates its cache accordingly.

Let's take an example of a cache line which is marked as Shared.

If a CPU modifies this cache line, it is invalidated in the other caches. The core that modified the data sends a message to rest of the CPU's. When the other cores check their mailbox, they see that this cache line is now invalid and the state is updated accordingly in each cache on the other cores.

The L1 cache on each core then fetches the correct value from main memory (or L2/L3 cache) and sets its state to Shared again.

Memory ordering

Now that we have some idea of how the CPUs are designed to coordinate between them, we can talk about different memory orderings and what they mean.

In Rust, the memory ordering is represented by the std::sync::atomic::Ordering enum, which has 5 possible values.

A mental model

While in practice this is pretty hard to do in Rust due to its type system (we have no way to get a pointer to an Atomic for example), I find it useful to imagine an observer-core. This observer core is interested in the same memory as we perform atomic operations on for some reason, so we'll divide each model in two: how it looks on the core it's running and how it looks from an observer-core.

Relaxed

On the current CPU: Relaxed memory ordering on atomics will prevent the compiler from reordering these instructions themselves, but, on weakly ordered CPUs, it might reorder all other memory accesses. It's OK if you only increment a counter, but it might get you into trouble if you use a flag to implement a spin-lock for example, since you can't trust that "normal" memory access before and after the flag is set is not reordered.

On the observer CPU: Both the compiler and the CPU are free to reorder any other memory access except from switching two Relaxed load/stores with each other. The observer core might observe operations in a different order than the "program order" (as we wrote them). They will however, always see Relaxed operation-A before Relaxed operation-B if we wrote them in that order.

Relaxed is therefore the weakest of the possible memory orderings. It implies that the operation does not do any specific synchronization with the other CPUs.

Acquire

On the current CPU: Any memory operation written after the Acquire access stays after it. It's meant to be paired with a Release memory ordering flag, forming a sort of a "memory sandwich". All memory access between the load and store will be synchronized with the other CPUs.

On weakly ordered systems, this might result in using special CPU instructions before the Acquire operation, which forces the current core to process all messages in its mailbox (many CPUs have both serializing and memory ordering instructions). A memory fence will most likely also be implemented to prevent the CPU from reordering memory access before the Acquire load. The Acquire operation will therefore be synchronized with modifications on memory done on the other CPUs.

On the observer CPU: Since Acquire is a load operation, it doesn't modify memory, there is nothing to observe.

However, and there is one caveat, if the observer core itself does an Acquire load, it will be able to see all memory operations happening from the Acquire load, and to the Release store (including the store). This means there must be some global synchronization going on. Let's discuss this a bit more in when we talk about Release.

Acquire is often used to write locks, where some operations need to stay after the successful acquisition of the lock. For this exact reason, Acquire only makes sense in load operations. Most atomic methods in Rust that involve stores will panic if you pass in Acquire as the memory ordering of a store operation.

Release

On the current CPU: In contrast to Acquire, any memory operation written before the Release memory ordering flag stays before it. It's meant to be paired with an Acquire memory ordering flag.

On weakly ordered CPUs the compiler might insert a memory fence to ensure that the CPU doesn't reorder the memory operations before the Release operation so that they happen after it. There is also a guarantee that all other cores which do an Acquire must see all memory operations after the Acquire and before this Release.

So not only do the operations need to be correctly ordered locally, there is also a guarantee that the changes must be visible to an observing core at this point.

That means some global synchronization must happen either before each Acquire access, or after a Release store. This basically leaves us with two choices:

1. An Acquire load must ensure that it processes all messages and if any other core has invalidated any memory we load, it must fetch the correct value.

2. A Release store must be atomic and invalidate all other caches holding that value before it modifies it.

Only doing one of these is enough though. This is partially what makes it weaker than SeqCst but also more performant.

On the observer CPU: An observing CPU might not see these changes in any specific order, unless it itself uses an Acquire load of the memory. If it does, it will see all memory which has been modified between the Acquire and the Release, including the Release store itself.

Release is often used together with Acquire to write locks. For a lock to function, some operations need to stay after the successful acquisition of the lock, but before the lock is released. For this reason, and opposite of the Acquire ordering, most load methods in Rust will panic if you pass in a Release ordering.

AcqRel

This is intended to be used on operations which both load and store a value. AtomicBool::compare_and_swap is one such operation. Since this operation both loads and stores a value, this could matter on weakly ordered systems in contrast to Relaxed operations.

We can think of this operation more or less like a fence. Memory operations that are written before it will not be reordered across this boundary and memory operations that are written after it will not be reordered before it.

SeqCst

SeqCst stands for Sequential Consistency and gives the same guarantee that Acquire/Release does but also promises to establish a single total modification order.

SeqCst has been critiqued for being promoted as the recommended ordering to use and I've seen several objections about using it since it seems to be hard to prove that you have a good reason for using it. It has also been criticized for being slightly broken.

This figure should explain where SeqCst might fail in upholding it's guarantees:

Got it? Good! We'll focus on the practical sides of SeqCst and not the theoretical foundations of it from now on.

Just know that there is a bit of discussion around it, and that most likely Acquire/Release will cover most of your challenges, at least on a strongly ordered CPU.

Let's consider SeqCst in contrast to an Acquire/Release operation.

I'll use this Godbolt example to explain:

The code looks like this:

use std::sync::atomic::{AtomicBool, Ordering};
static X: AtomicBool = AtomicBool::new(true);
static Y: AtomicBool = AtomicBool::new(true);
​
pub fn example(val: bool) -> bool {
    let x = X.load(Ordering::Acquire);
    X.store(val | x, Ordering::Release);
    let y = Y.load(Ordering::Acquire);
    x || y
}

The outputted assembly using Acquire/Releasewill look like this:

movb    example::X.0.0(%rip), %al # load(Acquire)
testb   %al, %al
setne   %al
orb     %dil, %al
movb    %al, example::X.0.0(%rip) # store(Release)
movb    $1, %al                   # load(Acquire)
retq

Now, on a weakly ordered CPU, the instructions might differ, but the result must be the same.

The store operation which used Release memory ordering is movb %al, example::X.0.0(%rip). We know that on a strongly ordered system, this is enough to make sure that this is immediately set as Invalid in other caches if they contain this data.

So what's the problem?

Well, to actually point that out, we need to take a look at the relevant part of the C++ specification for Release-Acquire:

The synchronization is established only between the threads releasing and acquiring the same atomic variable. Other threads can see different order of memory accesses than either or both of the synchronized threads.

Rusts documentation for Release re-iterates on that and states:

... In particular, all previous writes become visible to all threads that perform an Acquire (or stronger) load of this value.

An now is the time where we go and take a closer look that one non-guarantee I mentioned in the start. The Intel Developers Manual goes in to a little more detail in chapter 8.2.3.4:

8.2.3.4 Loads May Be Reordered with Earlier Stores to Different Locations

The Intel-64 memory-ordering model allows a load to be reordered with an earlier store to a different location. However, loads are not reordered with stores to the same location.

So if we put this information together, we could have the following situation:

let x = X.load(Ordering::Acquire);
X.store(val | x, Ordering::Release); # earlier store to different location
let y = Y.load(Ordering::Acquire);   # load
​
// *Could* get reordered on the CPU to this:
​
let x = X.load(Ordering::Acquire);
let y = Y.load(Ordering::Acquire);
X.store(val | x, Ordering::Release);

Now, I've tried my best on my Intel CPU to provoke a situation where this causes a problem, but I have not managed to get a simple example going to reliably showing that. But in theory, judging by the specs and the description of the abstract machine, Acquire/Release doesn't prevent this.

If we change our code to:

use std::sync::atomic::{AtomicBool, Ordering};
static X: AtomicBool = AtomicBool::new(true);
static Y: AtomicBool = AtomicBool::new(true);
​
pub fn example(val: bool) -> bool {
    let x = X.load(Ordering::SeqCst);
    X.store(val | x, Ordering::SeqCst);
    let y = Y.load(Ordering::SeqCst);
    x || y
}

We get the following assembly output:

movb    example::X.0.0(%rip), %al
testb   %al, %al
setne   %al
orb     %dil, %al
xchgb   %al, example::X.0.0(%rip)
movb    $1, %al
retq

The interesting change here is the store operation which is now changed from a simple load to a special instruction xchgb %al, example::X.0.0(%rip). This is an atomic operation (xchghas an implicit lockprefix).

Since the xchg instruction is a locked instruction (when it refers to memory) it will make sure that all cache lines on other cores referring to the same memory are locked when the memory is fetched and then invalidated after the modification. In addition it works as a full memory fence which we can derive from chapter 8.2.3.9 in the Intel Developer Manual:

8.2.3.9 Loads and Stores Are Not Reordered with Locked Instructions

The memory-ordering model prevents loads and stores from being reordered with locked instructions that execute earlier or later. The examples in this section illustrate only cases in which a locked instruction is executed before a load or a store. The reader should note that reordering is prevented also if the locked instruction is executed after a load or a store.

SeqCst is the strongest of the memory orderings. It also has a slightly higher cost than the others.

Atomic Operations

In addition to the memory fences discussed above, using the atomic types in the std::sync::atomic module gives access to some important CPU instructions we normally don't see in Rust:

From Implementing Scalable Atomic Locks for Multi-Core Intel® EM64T and IA32 Architectures:

User level locks involve utilizing the atomic instructions of processor to atomically update a memory space. The atomic instructions involve utilizing a lock prefix on the instruction and having the destination operand assigned to a memory address. The following instructions can run atomically with a lock prefix on current Intel processors: ADD, ADC, AND, BTC, BTR, BTS, CMPXCHG, CMPXCH8B, DEC, INC, NEG, NOT, OR, SBB, SUB, XOR, XADD, and XCHG...

Ok, so when we use the methods of an atomic, such as fetch_add on AtomicUsize, the compiler actually changes the instructions it emits for the addition of the two numbers on the CPU. The assembly would instead look something like (an AT&T dialect) lock addq ..., ...instead of addq ..., ...which we'd normally expect.

LOAD NUMBER
---- a competing core can load the same value here ----
INCREASE NUMBER
---- a competing core can increase the same value ----
---- a competing core can store its data here ----
STORE NUMBER
---- we overwrite that data here ----

A pretty normal use case for atomics is spin-locks. A very simple (and unsafe) one could look like this:

static LOCKED: AtomicBool = AtomicBool::new(false);
static mut COUNTER: usize = 0;
​
pub fn spinlock(inc: usize) {
    while LOCKED.compare_and_swap(false, true, Ordering::Acquire) {}
    unsafe { COUNTER += inc };
    LOCKED.store(false, Ordering::Release);
}

This will result in the following assembly:

xorl    %eax, %eax
lock    cmpxchgb %cl, example::LOCKED(%rip)
jne     .LBB0_1
addq    %rdi, example::COUNTER(%rip)
movb    $0, example::LOCKED(%rip)
retq

lock cmpxchgb %cl, example::LOCKED(%rip)is the atomic operation we do in compare_and_swap. lock cmpxchgb is a locking operation; it reads a flag and changes its value if a certain condition is met.

Now what does this lock instruction prefix do?

It can quickly become a bit technical, but as far as I understand it, an easy way to model this is that it sets the cache line state to Modified already when the memory is fetched from the cache.

This way, from the moment it's fetched from a core's L1 cache it's marked as Modified. The processor uses its cache coherence mechanism to make sure the state is updated to Invalid on all other caches where it exists - even though they've not yet processed all of their messages in their mailboxes yet.

If message passing is the normal way of synchronizing changes, the locked instruction (and other memory-ordering or serializing instructions) involves a more expensive and more powerful mechanism which bypasses the message passing, locks the cache lines on the other caches (so no load or store operation can happen when while it's in progress) and sets them as invalid accordingly, which forces the cache to fetch an updated value from memory.

Conclusion

Are you still there? If so, relax now, we're done for today. Thanks for staying with me and reading through, I do sincerely hope you enjoyed it and got some value out of it.

I fundamentally believe that getting a good mental model around problems you actually work hard to deal with has numerous benefits for both your personal motivation and how you write your code, even though you never venture into the std::sync::atomic module at all in your daily life.

Until next time!