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<h1>
  LLVM Atomic Instructions and Concurrency Guide
</h1>

<ol>
  <li><a href="#introduction">Introduction</a></li>
  <li><a href="#outsideatomic">Optimization outside atomic</a></li>
  <li><a href="#atomicinst">Atomic instructions</a></li>
  <li><a href="#ordering">Atomic orderings</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.
      (<a href="http://www.open-std.org/jtc1/sc22/wg21/">C++0x draft available here</a>.)
      (<a href="http://www.open-std.org/jtc1/sc22/wg14/">C1x draft available here</a>)</li>
  <li>Proper semantics for Java-style memory, for both <code>volatile</code> and
      regular shared variables.
      (<a href="http://java.sun.com/docs/books/jls/third_edition/html/memory.html">Java Specification</a>)</li>
  <li>gcc-compatible <code>__sync_*</code> builtins.
      (<a href="http://gcc.gnu.org/onlinedocs/gcc/Atomic-Builtins.html">Description</a>)</li>
  <li>Other scenarios with atomic semantics, including <code>static</code>
      variables with non-trivial constructors in C++.</li>
</ul>

<p>Atomic and volatile in the IR are orthogonal; "volatile" is the C/C++
   volatile, which ensures that every volatile load and store happens and is
   performed in the stated order.  A couple examples: if a
   SequentiallyConsistent store is immediately followed by another
   SequentiallyConsistent store to the same address, the first store can
   be erased. This transformation is not allowed for a pair of volatile
   stores. On the other hand, a non-volatile non-atomic load can be moved
   across a volatile load freely, but not an Acquire load.</p>

<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="outsideatomic">Optimization outside atomic</a>
</h2>
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<div>

<p>The basic <code>'load'</code> and <code>'store'</code> allow a variety of 
   optimizations, but can lead to undefined results in a concurrent environment;
   see <a href="#o_nonatomic">NonAtomic</a>. This section specifically goes
   into the one optimizer restriction which applies in concurrent environments,
   which gets a bit more of an extended description because any optimization
   dealing with stores needs to be aware of it.</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.  Take the following example:</p>

<pre>
/* C code, for readability; run through clang -O2 -S -emit-llvm to get
   equivalent IR */
int x;
void f(int* a) {
  for (int i = 0; i &lt; 100; i++) {
    if (a[i])
      x += 1;
  }
}
</pre>

<p>The following is equivalent in non-concurrent situations:</p>

<pre>
int x;
void f(int* a) {
  int xtemp = x;
  for (int i = 0; i &lt; 100; i++) {
    if (a[i])
      xtemp += 1;
  }
  x = xtemp;
}
</pre>

<p>However, LLVM is not allowed to transform the former to the latter: it could
   indirectly introduce undefined behavior if another thread can access x at
   the same time. (This example is particularly of interest because before the
   concurrency model was implemented, LLVM would perform this
   transformation.)</p>

<p>Note that speculative loads are allowed; a load which
   is part of a race returns <code>undef</code>, but does not have undefined
   behavior.</p>


</div>

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<h2>
  <a name="atomicinst">Atomic instructions</a>
</h2>
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<div>

<p>For cases where simple loads and stores are not sufficient, LLVM provides
   various atomic instructions. The exact guarantees provided depend on the
   ordering; see <a href="#ordering">Atomic orderings</a></p>

<p><code>load atomic</code> and <code>store atomic</code> provide the same
   basic functionality as non-atomic loads and stores, but provide additional
   guarantees in situations where threads and signals are involved.</p>

<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 on any thread
   between the load and store.  Note that LLVM's cmpxchg does not provide quite
   as many options 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="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. (See also <a href="LangRef.html#ordering">LangRef</a>.)</p>

<!-- ======================================================================= -->
<h3>
     <a name="o_notatomic">NotAtomic</a>
</h3>

<div>

<p>NotAtomic is the obvious, a load or store which is not atomic. (This isn't
   really a level of atomicity, but is listed here for comparison.) This is
   essentially a regular load or store. If there is a race on a given memory
   location, loads from that location return undef.</p>

<dl>
  <dt>Relevant standard</dt>
  <dd>This is intended to match shared variables in C/C++, and to be used
      in any other context where memory access is necessary, and
      a race is impossible. (The precise definition is in
      <a href="LangRef.html#memmodel">LangRef</a>.)
  <dt>Notes for frontends</dt>
  <dd>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. If your frontend is for a "safe" language like Java,
      use Unordered to load and store any shared variable.  Note that NotAtomic
      volatile loads and stores are not properly atomic; do not try to use
      them as a substitute. (Per the C/C++ standards, volatile does provide
      some limited guarantees around asynchronous signals, but atomics are
      generally a better solution.)
  <dt>Notes for optimizers</dt>
  <dd>Introducing loads to shared variables along a codepath where they would
      not otherwise exist is allowed; introducing stores to shared variables
      is not. See <a href="#outsideatomic">Optimization outside
      atomic</a>.</dd>
  <dt>Notes for code generation</dt>
  <dd>The one interesting restriction here is that it is not allowed to write
      to bytes outside of the bytes relevant to a store.  This is mostly
      relevant to unaligned stores: it is not allowed in general to convert
      an unaligned store into two aligned stores of the same width as the
      unaligned store. Backends are also expected to generate an i8 store
      as an i8 store, and not an instruction which writes to surrounding
      bytes.  (If you are writing a backend for an architecture which cannot
      satisfy these restrictions and cares about concurrency, please send an
      email to llvmdev.)</dd>
</dl>

</div>


<!-- ======================================================================= -->
<h3>
     <a name="o_unordered">Unordered</a>
</h3>

<div>

<p>Unordered is the lowest level of atomicity. It essentially guarantees that
   races produce somewhat sane results instead of having undefined behavior.
   It also guarantees the operation to be lock-free, so it do not depend on
   the data being part of a special atomic structure or depend on a separate
   per-process global lock.  Note that code generation will fail for
   unsupported atomic operations; if you need such an operation, use explicit
   locking.</p>

<dl>
  <dt>Relevant standard</dt>
  <dd>This is intended to match the Java memory model for shared
      variables.</dd>
  <dt>Notes for frontends</dt>
  <dd>This 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 store
      on ARM. (A frontend for Java or other "safe" languages would normally
      split a 64-bit store on ARM into two 32-bit unordered stores.)
  <dt>Notes for optimizers</dt>
  <dd>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.</dd>
  <dt>Notes for code generation</dt>
  <dd>These operations are required to be atomic in the sense that if you
      use unordered loads and unordered stores, a load cannot see a value
      which was never stored.  A normal load or store instruction is usually
      sufficient, but note that an unordered load or store cannot
      be split into multiple instructions (or an instruction which
      does multiple memory operations, like <code>LDRD</code> on ARM).</dd>
</dl>

</div>

<!-- ======================================================================= -->
<h3>
     <a name="o_monotonic">Monotonic</a>
</h3>

<div>

<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.

<dl>
  <dt>Relevant standard</dt>
  <dd>This corresponds to the C++0x/C1x <code>memory_order_relaxed</code>;
     see those standards for the exact definition.
  <dt>Notes for frontends</dt>
  <dd>If you are writing a frontend which uses this directly, use with caution.
      The guarantees in terms of synchronization are very weak, so make
      sure these are only used in a pattern which you know is correct.
      Generally, these would either be used for atomic operations which
      do not protect other memory (like an atomic counter), or along with
      a <code>fence</code>.</dd>
  <dt>Notes for optimizers</dt>
  <dd>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.</dd>
  <dt>Notes for code generation</dt>
  <dd>Code generation is essentially the same as that for unordered for loads
     and stores.  No fences are required.  <code>cmpxchg</code> and 
     <code>atomicrmw</code> are required to appear as a single operation.</dd>
</dl>

</div>

<!-- ======================================================================= -->
<h3>
     <a name="o_acquire">Acquire</a>
</h3>

<div>

<p>Acquire provides a barrier of the sort necessary to acquire a lock to access
   other memory with normal loads and stores.

<dl>
  <dt>Relevant standard</dt>
  <dd>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>.
  <dt>Notes for frontends</dt>
  <dd>If you are writing a frontend which uses this directly, use with caution.
      Acquire only provides a semantic guarantee when paired with a Release
      operation.</dd>
  <dt>Notes for optimizers</dt>
  <dd>Optimizers not aware of atomics can treat this like a nothrow call.
      It is also possible to move stores from before an Acquire load
      or read-modify-write operation to after it, and move non-Acquire
      loads from before an Acquire operation to after it.</dd>
  <dt>Notes for code generation</dt>
  <dd>Architectures with weak memory ordering (essentially everything relevant
      today except x86 and SPARC) require some sort of fence to maintain
      the Acquire semantics.  The precise fences required varies widely by
      architecture, but for a simple implementation, most architectures provide
      a barrier which is strong enough for everything (<code>dmb</code> on ARM,
      <code>sync</code> on PowerPC, etc.).  Putting such a fence after the
      equivalent Monotonic operation is sufficient to maintain Acquire
      semantics for a memory operation.</dd>
</dl>

</div>

<!-- ======================================================================= -->
<h3>
     <a name="o_acquire">Release</a>
</h3>

<div>

<p>Release is similar to Acquire, but with a barrier of the sort necessary to
   release a lock.

<dl>
  <dt>Relevant standard</dt>
  <dd>This corresponds to the C++0x/C1x <code>memory_order_release</code>.</dd>
  <dt>Notes for frontends</dt>
  <dd>If you are writing a frontend which uses this directly, use with caution.
      Release only provides a semantic guarantee when paired with a Acquire
      operation.</dd>
  <dt>Notes for optimizers</dt>
  <dd>Optimizers not aware of atomics can treat this like a nothrow call.
      It is also possible to move loads from after a Release store
      or read-modify-write operation to before it, and move non-Release
      stores from after an Release operation to before it.</dd>
  <dt>Notes for code generation</dt>
  <dd>See the section on Acquire; a fence before the relevant operation is
      usually sufficient for Release. Note that a store-store fence is not
      sufficient to implement Release semantics; store-store fences are
      generally not exposed to IR because they are extremely difficult to
      use correctly.</dd>
</dl>

</div>

<!-- ======================================================================= -->
<h3>
     <a name="o_acqrel">AcquireRelease</a>
</h3>

<div>

<p>AcquireRelease (<code>acq_rel</code> in IR) provides both an Acquire and a
   Release barrier (for fences and operations which both read and write memory).

<dl>
  <dt>Relevant standard</dt>
  <dd>This corresponds to the C++0x/C1x <code>memory_order_acq_rel</code>.
  <dt>Notes for frontends</dt>
  <dd>If you are writing a frontend which uses this directly, use with caution.
      Acquire only provides a semantic guarantee when paired with a Release
      operation, and vice versa.</dd>
  <dt>Notes for optimizers</dt>
  <dd>In general, optimizers should treat this like a nothrow call; the
      the possible optimizations are usually not interesting.</dd>
  <dt>Notes for code generation</dt>
  <dd>This operation has Acquire and Release semantics; see the sections on
      Acquire and Release.</dd>
</dl>

</div>

<!-- ======================================================================= -->
<h3>
     <a name="o_seqcst">SequentiallyConsistent</a>
</h3>

<div>

<p>SequentiallyConsistent (<code>seq_cst</code> in IR) provides
   Acquire semantics for loads and Release semantics for
   stores. Additionally, it guarantees that a total ordering exists
   between all SequentiallyConsistent operations.

<dl>
  <dt>Relevant standard</dt>
  <dd>This corresponds to the C++0x/C1x <code>memory_order_seq_cst</code>,
      Java volatile, and the gcc-compatible <code>__sync_*</code> builtins
      which do not specify otherwise.
  <dt>Notes for frontends</dt>
  <dd>If a frontend is exposing atomic operations, these are much easier to
      reason about for the programmer than other kinds of operations, and using
      them is generally a practical performance tradeoff.</dd>
  <dt>Notes for optimizers</dt>
  <dd>Optimizers not aware of atomics can treat this like a nothrow call.
      For SequentiallyConsistent loads and stores, the same reorderings are
      allowed as for Acquire loads and Release stores, except that
      SequentiallyConsistent operations may not be reordered.</dd>
  <dt>Notes for code generation</dt>
  <dd>SequentiallyConsistent loads minimally require the same barriers
     as Acquire operations and SequentiallyConsistent stores require
     Release barriers. Additionally, the code generator must enforce
     ordering between SequentiallyConsistent stores followed by
     SequentiallyConsistent loads. This is usually done by emitting
     either a full fence before the loads or a full fence after the
     stores; which is preferred varies by architecture.</dd>
</dl>

</div>

</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>
  <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>
  <li>mayReadFromMemory()/mayWriteToMemory(): Existing predicate, but note
      that they return true for any operation which is volatile or at least
      Monotonic.</li>
  <li>Alias analysis: Note that AA will return ModRef for anything Acquire or
      Release, and for the address accessed by any Monotonic operation.</li>
</ul>

<p>To support optimizing around atomic operations, make sure you are using
   the right predicates; everything should work if that is done.  If your
   pass should optimize some atomic operations (Unordered operations in
   particular), make sure it doesn't replace an atomic load or store with
   a non-atomic operation.</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>
<!-- *********************************************************************** -->

<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>Common architectures have some way of representing at least a pointer-sized
   lock-free <code>cmpxchg</code>; such an operation can be used to implement
   all the other atomic operations which can be represented in IR up to that
   size.  Backends are expected to implement all those operations, but not
   operations which cannot be implemented in a lock-free manner.  It is
   expected that backends will give an error when given an operation which
   cannot be implemented.  (The LLVM code generator is not very helpful here
   at the moment, but hopefully that will change.)</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>cmpxchg</code> and <code>atomicrmw</code> can be represented using
   a loop with LL/SC-style instructions which take some sort of exclusive
   lock on a cache line  (<code>LDREX</code> and <code>STREX</code> on
   ARM, etc.). At the moment, the IR does not provide any way to represent a
   weak <code>cmpxchg</code> which would not require a loop.</p>
</div>

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