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485 lines
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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN"
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<html>
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<head>
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<title>LLVM Atomic Instructions and Concurrency Guide</title>
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<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
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<link rel="stylesheet" href="llvm.css" type="text/css">
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</head>
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<body>
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<h1>
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LLVM Atomic Instructions and Concurrency Guide
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</h1>
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<ol>
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<li><a href="#introduction">Introduction</a></li>
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<li><a href="#loadstore">Load and store</a></li>
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<li><a href="#otherinst">Other atomic instructions</a></li>
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<li><a href="#ordering">Atomic orderings</a></li>
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<li><a href="#iropt">Atomics and IR optimization</a></li>
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<li><a href="#codegen">Atomics and Codegen</a></li>
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</ol>
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<div class="doc_author">
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<p>Written by Eli Friedman</p>
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</div>
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<!-- *********************************************************************** -->
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<h2>
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<a name="introduction">Introduction</a>
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</h2>
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<!-- *********************************************************************** -->
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<div>
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<p>Historically, LLVM has not had very strong support for concurrency; some
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minimal intrinsics were provided, and <code>volatile</code> was used in some
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cases to achieve rough semantics in the presence of concurrency. However, this
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is changing; there are now new instructions which are well-defined in the
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presence of threads and asynchronous signals, and the model for existing
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instructions has been clarified in the IR.</p>
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<p>The atomic instructions are designed specifically to provide readable IR and
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optimized code generation for the following:</p>
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<ul>
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<li>The new C++0x <code><atomic></code> header.
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(<a href="http://www.open-std.org/jtc1/sc22/wg21/">C++0x draft available here</a>.)
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(<a href="http://www.open-std.org/jtc1/sc22/wg14/">C1x draft available here</a>)</li>
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<li>Proper semantics for Java-style memory, for both <code>volatile</code> and
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regular shared variables.
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(<a href="http://java.sun.com/docs/books/jls/third_edition/html/memory.html">Java Specification</a>)</li>
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<li>gcc-compatible <code>__sync_*</code> builtins.
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(<a href="http://gcc.gnu.org/onlinedocs/gcc/Atomic-Builtins.html">Description</a>)</li>
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<li>Other scenarios with atomic semantics, including <code>static</code>
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variables with non-trivial constructors in C++.</li>
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</ul>
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<p>Atomic and volatile in the IR are orthogonal; "volatile" is the C/C++
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volatile, which ensures that every volatile load and store happens and is
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performed in the stated order. A couple examples: if a
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SequentiallyConsistent store is immediately followed by another
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SequentiallyConsistent store to the same address, the first store can
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be erased. This transformation is not allowed for a pair of volatile
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stores. On the other hand, a non-volatile non-atomic load can be moved
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across a volatile load freely, but not an Acquire load.</p>
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<p>This document is intended to provide a guide to anyone either writing a
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frontend for LLVM or working on optimization passes for LLVM with a guide
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for how to deal with instructions with special semantics in the presence of
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concurrency. This is not intended to be a precise guide to the semantics;
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the details can get extremely complicated and unreadable, and are not
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usually necessary.</p>
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</div>
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<!-- *********************************************************************** -->
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<h2>
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<a name="loadstore">Load and store</a>
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</h2>
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<!-- *********************************************************************** -->
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<div>
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<p>The basic <code>'load'</code> and <code>'store'</code> allow a variety of
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optimizations, but can have unintuitive results in a concurrent environment.
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For a frontend writer, the rule is essentially that all memory accessed
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with basic loads and stores by multiple threads should be protected by a
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lock or other synchronization; otherwise, you are likely to run into
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undefined behavior. (Do not use volatile as a substitute for atomics; it
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might work on some platforms, but does not provide the necessary guarantees
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in general.)</p>
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<p>From the optimizer's point of view, the rule is that if there
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are not any instructions with atomic ordering involved, concurrency does
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not matter, with one exception: if a variable might be visible to another
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thread or signal handler, a store cannot be inserted along a path where it
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might not execute otherwise. For example, suppose LICM wants to take all the
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loads and stores in a loop to and from a particular address and promote them
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to registers. LICM is not allowed to insert an unconditional store after
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the loop with the computed value unless a store unconditionally executes
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within the loop. Note that speculative loads are allowed; a load which
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is part of a race returns <code>undef</code>, but does not have undefined
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behavior.</p>
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<p>For cases where simple loads and stores are not sufficient, LLVM provides
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atomic loads and stores with varying levels of guarantees.</p>
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</div>
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<!-- *********************************************************************** -->
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<h2>
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<a name="otherinst">Other atomic instructions</a>
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</h2>
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<!-- *********************************************************************** -->
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<div>
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<p><code>cmpxchg</code> and <code>atomicrmw</code> are essentially like an
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atomic load followed by an atomic store (where the store is conditional for
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<code>cmpxchg</code>), but no other memory operation can happen between
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the load and store. Note that our cmpxchg does not have quite as many
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options for making cmpxchg weaker as the C++0x version.</p>
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<p>A <code>fence</code> provides Acquire and/or Release ordering which is not
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part of another operation; it is normally used along with Monotonic memory
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operations. A Monotonic load followed by an Acquire fence is roughly
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equivalent to an Acquire load.</p>
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<p>Frontends generating atomic instructions generally need to be aware of the
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target to some degree; atomic instructions are guaranteed to be lock-free,
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and therefore an instruction which is wider than the target natively supports
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can be impossible to generate.</p>
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</div>
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<!-- *********************************************************************** -->
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<h2>
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<a name="ordering">Atomic orderings</a>
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</h2>
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<!-- *********************************************************************** -->
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<div>
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<p>In order to achieve a balance between performance and necessary guarantees,
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there are six levels of atomicity. They are listed in order of strength;
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each level includes all the guarantees of the previous level except for
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Acquire/Release.</p>
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<!-- ======================================================================= -->
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<h3>
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<a name="o_unordered">Unordered</a>
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</h3>
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<div>
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<p>Unordered is the lowest level of atomicity. It essentially guarantees that
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races produce somewhat sane results instead of having undefined behavior.
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It also guarantees the operation to be lock-free, so it do not depend on
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the data being part of a special atomic structure or depend on a separate
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per-process global lock. Note that code generation will fail for
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unsupported atomic operations; if you need such an operation, use explicit
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locking.</p>
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<dl>
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<dt>Relevant standard</dt>
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<dd>This is intended to match the Java memory model for shared
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variables.</dd>
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<dt>Notes for frontends</dt>
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<dd>This cannot be used for synchronization, but is useful for Java and
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other "safe" languages which need to guarantee that the generated
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code never exhibits undefined behavior. Note that this guarantee
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is cheap on common platforms for loads of a native width, but can
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be expensive or unavailable for wider loads, like a 64-bit store
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on ARM. (A frontend for Java or other "safe" languages would normally
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split a 64-bit store on ARM into two 32-bit unordered stores.)
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<dt>Notes for optimizers</dt>
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<dd>In terms of the optimizer, this prohibits any transformation that
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transforms a single load into multiple loads, transforms a store
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into multiple stores, narrows a store, or stores a value which
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would not be stored otherwise. Some examples of unsafe optimizations
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are narrowing an assignment into a bitfield, rematerializing
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a load, and turning loads and stores into a memcpy call. Reordering
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unordered operations is safe, though, and optimizers should take
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advantage of that because unordered operations are common in
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languages that need them.</dd>
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<dt>Notes for code generation</dt>
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<dd>These operations are required to be atomic in the sense that if you
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use unordered loads and unordered stores, a load cannot see a value
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which was never stored. A normal load or store instruction is usually
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sufficient, but note that an unordered load or store cannot
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be split into multiple instructions (or an instruction which
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does multiple memory operations, like <code>LDRD</code> on ARM).</dd>
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</dl>
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</div>
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<!-- ======================================================================= -->
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<h3>
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<a name="o_monotonic">Monotonic</a>
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</h3>
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<div>
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<p>Monotonic is the weakest level of atomicity that can be used in
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synchronization primitives, although it does not provide any general
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synchronization. It essentially guarantees that if you take all the
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operations affecting a specific address, a consistent ordering exists.
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<dl>
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<dt>Relevant standard</dt>
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<dd>This corresponds to the C++0x/C1x <code>memory_order_relaxed</code>;
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see those standards for the exact definition.
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<dt>Notes for frontends</dt>
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<dd>If you are writing a frontend which uses this directly, use with caution.
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The guarantees in terms of synchronization are very weak, so make
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sure these are only used in a pattern which you know is correct.
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Generally, these would either be used for atomic operations which
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do not protect other memory (like an atomic counter), or along with
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a <code>fence</code>.</dd>
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<dt>Notes for optimizers</dt>
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<dd>In terms of the optimizer, this can be treated as a read+write on the
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relevant memory location (and alias analysis will take advantage of
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that). In addition, it is legal to reorder non-atomic and Unordered
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loads around Monotonic loads. CSE/DSE and a few other optimizations
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are allowed, but Monotonic operations are unlikely to be used in ways
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which would make those optimizations useful.</dd>
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<dt>Notes for code generation</dt>
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<dd>Code generation is essentially the same as that for unordered for loads
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and stores. No fences is required. <code>cmpxchg</code> and
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<code>atomicrmw</code> are required to appear as a single operation.</dd>
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</dl>
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</div>
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<!-- ======================================================================= -->
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<h3>
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<a name="o_acquire">Acquire</a>
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</h3>
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<div>
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<p>Acquire provides a barrier of the sort necessary to acquire a lock to access
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other memory with normal loads and stores.
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<dl>
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<dt>Relevant standard</dt>
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<dd>This corresponds to the C++0x/C1x <code>memory_order_acquire</code>. It
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should also be used for C++0x/C1x <code>memory_order_consume</code>.
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<dt>Notes for frontends</dt>
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<dd>If you are writing a frontend which uses this directly, use with caution.
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Acquire only provides a semantic guarantee when paired with a Release
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operation.</dd>
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<dt>Notes for optimizers</dt>
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<dd>In general, optimizers should treat this like a nothrow call; the
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the possible optimizations are usually not interesting.</dd>
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<dt>Notes for code generation</dt>
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<dd>Architectures with weak memory ordering (essentially everything relevant
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today except x86 and SPARC) require some sort of fence to maintain
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the Acquire semantics. The precise fences required varies widely by
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architecture, but for a simple implementation, most architectures provide
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a barrier which is strong enough for everything (<code>dmb</code> on ARM,
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<code>sync</code> on PowerPC, etc.). Putting such a fence after the
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equivalent Monotonic operation is sufficient to maintain Acquire
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semantics for a memory operation.</dd>
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</dl>
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</div>
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<!-- ======================================================================= -->
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<h3>
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<a name="o_acquire">Release</a>
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</h3>
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<div>
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<p>Release is similar to Acquire, but with a barrier of the sort necessary to
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release a lock.
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<dl>
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<dt>Relevant standard</dt>
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<dd>This corresponds to the C++0x/C1x <code>memory_order_release</code>.</dd>
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<dt>Notes for frontends</dt>
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<dd>If you are writing a frontend which uses this directly, use with caution.
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Release only provides a semantic guarantee when paired with a Acquire
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operation.</dd>
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<dt>Notes for optimizers</dt>
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<dd>In general, optimizers should treat this like a nothrow call; the
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the possible optimizations are usually not interesting.</dd>
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<dt>Notes for code generation</dt>
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<dd>Similarly to Acquire, a fence after the relevant operation is usually
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sufficient; see the section on Acquire. Note that a store-store fence
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is not sufficient to implement Release semantics; store-store fences
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are generally not exposed to IR because they are extremely difficult to
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use correctly.</dd>
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</dl>
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</div>
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<!-- ======================================================================= -->
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<h3>
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<a name="o_acqrel">AcquireRelease</a>
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</h3>
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<div>
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<p>AcquireRelease (<code>acq_rel</code> in IR) provides both an Acquire and a
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Release barrier (for fences and operations which both read and write memory).
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<dl>
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<dt>Relevant standard</dt>
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<dd>This corresponds to the C++0x/C1x <code>memory_order_acq_rel</code>.
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<dt>Notes for frontends</dt>
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<dd>If you are writing a frontend which uses this directly, use with caution.
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Acquire only provides a semantic guarantee when paired with a Release
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operation, and vice versa.</dd>
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<dt>Notes for optimizers</dt>
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<dd>In general, optimizers should treat this like a nothrow call; the
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the possible optimizations are usually not interesting.</dd>
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<dt>Notes for code generation</dt>
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<dd>This operation has Acquire and Release semantics; see the sections on
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Acquire and Release.</dd>
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</dl>
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</div>
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<!-- ======================================================================= -->
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<h3>
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<a name="o_seqcst">SequentiallyConsistent</a>
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</h3>
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<div>
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<p>SequentiallyConsistent (<code>seq_cst</code> in IR) provides
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Acquire semantics for loads and Release semantics for
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stores. Additionally, it guarantees that a total ordering exists
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between all SequentiallyConsistent operations.
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<dl>
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<dt>Relevant standard</dt>
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<dd>This corresponds to the C++0x/C1x <code>memory_order_seq_cst</code>,
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Java volatile, and the gcc-compatible <code>__sync_*</code> builtins
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which do not specify otherwise.
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<dt>Notes for frontends</dt>
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<dd>If a frontend is exposing atomic operations, these are much easier to
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reason about for the programmer than other kinds of operations, and using
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them is generally a practical performance tradeoff.</dd>
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<dt>Notes for optimizers</dt>
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<dd>In general, optimizers should treat this like a nothrow call.
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However, optimizers may improve performance by reordering a
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store followed by a load unless both operations are sequentially
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consistent.</dd>
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<dt>Notes for code generation</dt>
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<dd>SequentiallyConsistent loads minimally require the same barriers
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as Acquire operations and SequeuentiallyConsistent stores require
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Release barriers. Additionally, the code generator must enforce
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ordering between SequeuentiallyConsistent stores followed by
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SequeuentiallyConsistent loads. On common architectures, this
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requires emitting a full fence after SequeuentiallyConsistent stores.</dd>
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</dl>
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</div>
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</div>
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<!-- *********************************************************************** -->
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<h2>
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<a name="iropt">Atomics and IR optimization</a>
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</h2>
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<!-- *********************************************************************** -->
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<div>
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<p>Predicates for optimizer writers to query:
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<ul>
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<li>isSimple(): A load or store which is not volatile or atomic. This is
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what, for example, memcpyopt would check for operations it might
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transform.
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<li>isUnordered(): A load or store which is not volatile and at most
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Unordered. This would be checked, for example, by LICM before hoisting
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an operation.
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<li>mayReadFromMemory()/mayWriteToMemory(): Existing predicate, but note
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that they return true for any operation which is volatile or at least
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Monotonic.
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<li>Alias analysis: Note that AA will return ModRef for anything Acquire or
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Release, and for the address accessed by any Monotonic operation.
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</ul>
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<p>There are essentially two components to supporting atomic operations. The
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first is making sure to query isSimple() or isUnordered() instead
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of isVolatile() before transforming an operation. The other piece is
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making sure that a transform does not end up replacing, for example, an
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Unordered operation with a non-atomic operation. Most of the other
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necessary checks automatically fall out from existing predicates and
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alias analysis queries.</p>
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<p>Some examples of how optimizations interact with various kinds of atomic
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operations:
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<ul>
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<li>memcpyopt: An atomic operation cannot be optimized into part of a
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memcpy/memset, including unordered loads/stores. It can pull operations
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across some atomic operations.
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<li>LICM: Unordered loads/stores can be moved out of a loop. It just treats
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monotonic operations like a read+write to a memory location, and anything
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stricter than that like a nothrow call.
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<li>DSE: Unordered stores can be DSE'ed like normal stores. Monotonic stores
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can be DSE'ed in some cases, but it's tricky to reason about, and not
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especially important.
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<li>Folding a load: Any atomic load from a constant global can be
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constant-folded, because it cannot be observed. Similar reasoning allows
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scalarrepl with atomic loads and stores.
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</ul>
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</div>
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<!-- *********************************************************************** -->
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<h2>
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<a name="codegen">Atomics and Codegen</a>
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</h2>
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<!-- *********************************************************************** -->
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<div>
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<p>Atomic operations are represented in the SelectionDAG with
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<code>ATOMIC_*</code> opcodes. On architectures which use barrier
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instructions for all atomic ordering (like ARM), appropriate fences are
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split out as the DAG is built.</p>
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<p>The MachineMemOperand for all atomic operations is currently marked as
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volatile; this is not correct in the IR sense of volatile, but CodeGen
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handles anything marked volatile very conservatively. This should get
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fixed at some point.</p>
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<p>Common architectures have some way of representing at least a pointer-sized
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lock-free <code>cmpxchg</code>; such an operation can be used to implement
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all the other atomic operations which can be represented in IR up to that
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size. Backends are expected to implement all those operations, but not
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operations which cannot be implemented in a lock-free manner. It is
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expected that backends will give an error when given an operation which
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cannot be implemented. (The LLVM code generator is not very helpful here
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at the moment, but hopefully that will change.)</p>
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<p>The implementation of atomics on LL/SC architectures (like ARM) is currently
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a bit of a mess; there is a lot of copy-pasted code across targets, and
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the representation is relatively unsuited to optimization (it would be nice
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to be able to optimize loops involving cmpxchg etc.).</p>
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<p>On x86, all atomic loads generate a <code>MOV</code>.
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SequentiallyConsistent stores generate an <code>XCHG</code>, other stores
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generate a <code>MOV</code>. SequentiallyConsistent fences generate an
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<code>MFENCE</code>, other fences do not cause any code to be generated.
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cmpxchg uses the <code>LOCK CMPXCHG</code> instruction.
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<code>atomicrmw xchg</code> uses <code>XCHG</code>,
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<code>atomicrmw add</code> and <code>atomicrmw sub</code> use
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<code>XADD</code>, and all other <code>atomicrmw</code> operations generate
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a loop with <code>LOCK CMPXCHG</code>. Depending on the users of the
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result, some <code>atomicrmw</code> operations can be translated into
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operations like <code>LOCK AND</code>, but that does not work in
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general.</p>
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<p>On ARM, MIPS, and many other RISC architectures, Acquire, Release, and
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SequentiallyConsistent semantics require barrier instructions
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|
for every such operation. Loads and stores generate normal instructions.
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<code>cmpxchg</code> and <code>atomicrmw</code> can be represented using
|
|
a loop with LL/SC-style instructions which take some sort of exclusive
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|
lock on a cache line (<code>LDREX</code> and <code>STREX</code> on
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ARM, etc.). At the moment, the IR does not provide any way to represent a
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weak <code>cmpxchg</code> which would not require a loop.</p>
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</div>
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<a href="http://llvm.org/">LLVM Compiler Infrastructure</a><br>
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