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<title>LLVM Atomic Instructions and Concurrency Guide</title>
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<h1>
LLVM Atomic Instructions and Concurrency Guide
</h1>
<ol>
<li><a href="#introduction">Introduction</a></li>
<li><a href="#loadstore">Load and store</a></li>
<li><a href="#ordering">Atomic orderings</a></li>
<li><a href="#otherinst">Other atomic instructions</a></li>
<li><a href="#iropt">Atomics and IR optimization</a></li>
<li><a href="#codegen">Atomics and Codegen</a></li>
</ol>
<div class="doc_author">
<p>Written by Eli Friedman</p>
</div>
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<h2>
<a name="introduction">Introduction</a>
</h2>
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<div>
<p>Historically, LLVM has not had very strong support for concurrency; some
minimal intrinsics were provided, and <code>volatile</code> was used in some
cases to achieve rough semantics in the presence of concurrency. However, this
is changing; there are now new instructions which are well-defined in the
presence of threads and asynchronous signals, and the model for existing
instructions has been clarified in the IR.</p>
<p>The atomic instructions are designed specifically to provide readable IR and
optimized code generation for the following:</p>
<ul>
<li>The new C++0x <code>&lt;atomic&gt;</code> header.</li>
<li>Proper semantics for Java-style memory, for both <code>volatile</code> and
regular shared variables.</li>
<li>gcc-compatible <code>__sync_*</code> builtins.</li>
<li>Other scenarios with atomic semantics, including <code>static</code>
variables with non-trivial constructors in C++.</li>
</ul>
<p>This document is intended to provide a guide to anyone either writing a
frontend for LLVM or working on optimization passes for LLVM with a guide
for how to deal with instructions with special semantics in the presence of
concurrency. This is not intended to be a precise guide to the semantics;
the details can get extremely complicated and unreadable, and are not
usually necessary.</p>
</div>
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<h2>
<a name="loadstore">Load and store</a>
</h2>
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<div>
<p>The basic <code>'load'</code> and <code>'store'</code> allow a variety of
optimizations, but can have unintuitive results in a concurrent environment.
For a frontend writer, the rule is essentially that all memory accessed
with basic loads and stores by multiple threads should be protected by a
lock or other synchronization; otherwise, you are likely to run into
undefined behavior. (Do not use volatile as a substitute for atomics; it
might work on some platforms, but does not provide the necessary guarantees
in general.)</p>
<p>From the optimizer's point of view, the rule is that if there
are not any instructions with atomic ordering involved, concurrency does not
matter, with one exception: if a variable might be visible to another
thread or signal handler, a store cannot be inserted along a path where it
might not execute otherwise. Note that speculative loads are allowed;
a load which is part of a race returns <code>undef</code>, but is not
undefined behavior.</p>
<p>For cases where simple loads and stores are not sufficient, LLVM provides
atomic loads and stores with varying levels of guarantees.</p>
</div>
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<h2>
<a name="ordering">Atomic orderings</a>
</h2>
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<div>
<p>In order to achieve a balance between performance and necessary guarantees,
there are six levels of atomicity. They are listed in order of strength;
each level includes all the guarantees of the previous level except for
Acquire/Release.</p>
<p>Unordered is the lowest level of atomicity. It essentially guarantees that
races produce somewhat sane results instead of having undefined behavior.
This is intended to match the Java memory model for shared variables. It
cannot be used for synchronization, but is useful for Java and other
"safe" languages which need to guarantee that the generated code never
exhibits undefined behavior. Note that this guarantee is cheap on common
platforms for loads of a native width, but can be expensive or unavailable
for wider loads, like a 64-bit load on ARM. (A frontend for a "safe"
language would normally split a 64-bit load on ARM into two 32-bit
unordered loads.) In terms of the optimizer, this prohibits any
transformation that transforms a single load into multiple loads,
transforms a store into multiple stores, narrows a store, or stores a
value which would not be stored otherwise. Some examples of unsafe
optimizations are narrowing an assignment into a bitfield, rematerializing
a load, and turning loads and stores into a memcpy call. Reordering
unordered operations is safe, though, and optimizers should take
advantage of that because unordered operations are common in
languages that need them.</p>
<p>Monotonic is the weakest level of atomicity that can be used in
synchronization primitives, although it does not provide any general
synchronization. It essentially guarantees that if you take all the
operations affecting a specific address, a consistent ordering exists.
This corresponds to the C++0x/C1x <code>memory_order_relaxed</code>; see
those standards for the exact definition. If you are writing a frontend, do
not use the low-level synchronization primitives unless you are compiling
a language which requires it or are sure a given pattern is correct. In
terms of the optimizer, this can be treated as a read+write on the relevant
memory location (and alias analysis will take advantage of that). In
addition, it is legal to reorder non-atomic and Unordered loads around
Monotonic loads. CSE/DSE and a few other optimizations are allowed, but
Monotonic operations are unlikely to be used in ways which would make
those optimizations useful.</p>
<p>Acquire provides a barrier of the sort necessary to acquire a lock to access
other memory with normal loads and stores. This corresponds to the
C++0x/C1x <code>memory_order_acquire</code>. It should also be used for
C++0x/C1x <code>memory_order_consume</code>. This is a low-level
synchronization primitive. In general, optimizers should treat this like
a nothrow call.</p>
<p>Release is similar to Acquire, but with a barrier of the sort necessary to
release a lock. This corresponds to the C++0x/C1x
<code>memory_order_release</code>. In general, optimizers should treat this
like a nothrow call.</p>
<p>AcquireRelease (<code>acq_rel</code> in IR) provides both an Acquire and a Release barrier.
This corresponds to the C++0x/C1x <code>memory_order_acq_rel</code>. In general,
optimizers should treat this like a nothrow call.</p>
<p>SequentiallyConsistent (<code>seq_cst</code> in IR) provides Acquire and/or
Release semantics, and in addition guarantees a total ordering exists with
all other SequentiallyConsistent operations. This corresponds to the
C++0x/C1x <code>memory_order_seq_cst</code>, and Java volatile. The intent
of this ordering level is to provide a programming model which is relatively
easy to understand. In general, optimizers should treat this like a
nothrow call.</p>
</div>
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<h2>
<a name="otherinst">Other atomic instructions</a>
</h2>
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<div>
<p><code>cmpxchg</code> and <code>atomicrmw</code> are essentially like an
atomic load followed by an atomic store (where the store is conditional for
<code>cmpxchg</code>), but no other memory operation can happen between
the load and store. Note that our cmpxchg does not have quite as many
options for making cmpxchg weaker as the C++0x version.</p>
<p>A <code>fence</code> provides Acquire and/or Release ordering which is not
part of another operation; it is normally used along with Monotonic memory
operations. A Monotonic load followed by an Acquire fence is roughly
equivalent to an Acquire load.</p>
<p>Frontends generating atomic instructions generally need to be aware of the
target to some degree; atomic instructions are guaranteed to be lock-free,
and therefore an instruction which is wider than the target natively supports
can be impossible to generate.</p>
</div>
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<h2>
<a name="iropt">Atomics and IR optimization</a>
</h2>
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<div>
<p>Predicates for optimizer writers to query:
<ul>
<li>isSimple(): A load or store which is not volatile or atomic. This is
what, for example, memcpyopt would check for operations it might
transform.
<li>isUnordered(): A load or store which is not volatile and at most
Unordered. This would be checked, for example, by LICM before hoisting
an operation.
<li>mayReadFromMemory()/mayWriteToMemory(): Existing predicate, but note
that they return true for any operation which is volatile or at least
Monotonic.
<li>Alias analysis: Note that AA will return ModRef for anything Acquire or
Release, and for the address accessed by any Monotonic operation.
</ul>
<p>There are essentially two components to supporting atomic operations. The
first is making sure to query isSimple() or isUnordered() instead
of isVolatile() before transforming an operation. The other piece is
making sure that a transform does not end up replacing, for example, an
Unordered operation with a non-atomic operation. Most of the other
necessary checks automatically fall out from existing predicates and
alias analysis queries.</p>
<p>Some examples of how optimizations interact with various kinds of atomic
operations:
<ul>
<li>memcpyopt: An atomic operation cannot be optimized into part of a
memcpy/memset, including unordered loads/stores. It can pull operations
across some atomic operations.
<li>LICM: Unordered loads/stores can be moved out of a loop. It just treats
monotonic operations like a read+write to a memory location, and anything
stricter than that like a nothrow call.
<li>DSE: Unordered stores can be DSE'ed like normal stores. Monotonic stores
can be DSE'ed in some cases, but it's tricky to reason about, and not
especially important.
<li>Folding a load: Any atomic load from a constant global can be
constant-folded, because it cannot be observed. Similar reasoning allows
scalarrepl with atomic loads and stores.
</ul>
</div>
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<h2>
<a name="codegen">Atomics and Codegen</a>
</h2>
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<div>
<p>Atomic operations are represented in the SelectionDAG with
<code>ATOMIC_*</code> opcodes. On architectures which use barrier
instructions for all atomic ordering (like ARM), appropriate fences are
split out as the DAG is built.</p>
<p>The MachineMemOperand for all atomic operations is currently marked as
volatile; this is not correct in the IR sense of volatile, but CodeGen
handles anything marked volatile very conservatively. This should get
fixed at some point.</p>
<p>The implementation of atomics on LL/SC architectures (like ARM) is currently
a bit of a mess; there is a lot of copy-pasted code across targets, and
the representation is relatively unsuited to optimization (it would be nice
to be able to optimize loops involving cmpxchg etc.).</p>
<p>On x86, all atomic loads generate a <code>MOV</code>.
SequentiallyConsistent stores generate an <code>XCHG</code>, other stores
generate a <code>MOV</code>. SequentiallyConsistent fences generate an
<code>MFENCE</code>, other fences do not cause any code to be generated.
cmpxchg uses the <code>LOCK CMPXCHG</code> instruction.
<code>atomicrmw xchg</code> uses <code>XCHG</code>,
<code>atomicrmw add</code> and <code>atomicrmw sub</code> use
<code>XADD</code>, and all other <code>atomicrmw</code> operations generate
a loop with <code>LOCK CMPXCHG</code>. Depending on the users of the
result, some <code>atomicrmw</code> operations can be translated into
operations like <code>LOCK AND</code>, but that does not work in
general.</p>
<p>On ARM, MIPS, and many other RISC architectures, Acquire, Release, and
SequentiallyConsistent semantics require barrier instructions
for every such operation. Loads and stores generate normal instructions.
<code>atomicrmw</code> and <code>cmpxchg</code> generate LL/SC loops.</p>
</div>
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