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libconcurrent is a small library intended to be used both by kernel mode and user mode code to assist in implementing memory sharing patterns which involve readers observing memory concurrently with writers updating the same memory. Unlike techniques which use exclusion (such as mutexes, reader-writer locks, spinlocks, and so on) to ensure that reads to memory locations are never taking place at the same time as writes, concurrent read-write patterns require some extra care to ensure that programs are formally “data-race free” according to the C++ specification.

Data races in C++

Section of the C++20 Draft Specification formally defines what is considered to be a “data race” by the standard. Paragraph 2 defines a “conflict” by saying:

Two expression evaluations conflict if one of them modifies a memory location
(6.7.1) and the other one reads or modifies the same memory location.

Paragraph 20 then defines a “data race” by saying:

Two actions are potentially concurrent if

(21.1) — they are performed by different threads, or
(21.2) — they are unsequenced, at least one is performed by a signal handler,
         and they are not both performed by the same signal handler invocation.

The execution of a program contains a data race if it contains two potentially
concurrent conflicting actions, at least one of which is not atomic, and neither
happens before the other, except for the special case for signal handlers
described below. Any such data race results in undefined behavior.

So, when sharing data between concurrently executing threads where mutual exclusion cannot be used to ensure that data races cannot occur, extra care must be taken when reading and modifying the shared data. The data transfer utilities offered by libconcurrent ensure that all load and stores executed on shared memory regions are done using atomics, which should be sufficient to avoid introducing any formal data races (and therefore undefined behavior) to a program.

Transferring data

The lowest level building blocks offered by libconcurrent give the user the ability to concurrently transfer data into and out of a share memory location without accidentally introducing any undefined behavior as a result of unintentional data races. These building blocks are:

  • concurrent::WellDefinedCopyTo<SyncOpt, Alignment>(void* dst, const void* src, size_t len)
  • concurrent::WellDefinedCopyFrom<SyncOpt, Alignment>(void* dst, const void* src, size_t len)
  • concurrent::WellDefinedCopyable<T>::Update(const T&, SyncOptType<SyncOpt>)
  • concurrent::WellDefinedCopyable<T>::Read(T&, SyncOptType<SyncOpt>)

CopyTo operations move data from a thread‘s private buffer into a shared buffer which may be accessed concurrently by readers. CopyFrom operations move data from a shared buffer which may be concurrently written to into a thread’s private buffer.

Copy(To|From) both have memcpy semantics, not memmove semantics. In other words, it is illegal for |src| or |dst| to overlap in any way.

The individual Copy(To|From) functions represent the absolute lowest level building blocks of libconcurrent, and need to be used with care. When possible, prefer using one of the higher level building blocks which help to automate common patterns. They have memcpy compatible signatures, but include a few additional requirements. Specifically:

  1. The src and dst buffers must have the same alignment relative to the maximum atomic operation transfer granularity (currently 8 bytes). In other words, ASSERT((src & 0x7) == (dst & 0x7)).
  2. If these functions are being used to copy instances of structures or classes, it is required that those structs/classes be trivially copyable.
  3. When accessing shared memory, it is important that all read and write accesses operate using the same alignment and op-width at all times. For example: Given a shared buffer located at an 8 byte aligned address, shared, the following operations may all be safely conducted concurrently:
    • CopyTo(shared, local_1, 16);
    • CopyFrom(local_2, shared, 16);
    • CopyFrom(local_3, shared + 8, 8); Since shared is 8 byte aligned, all of the accesses to shared will also all be 8 byte aligned, and of 8 bytes in length, guaranteeing that all memory accesses to the same address in the shared region will use the same width memory transaction. Adding a CopyFrom(local_4, shared + 4, 8); to the list of concurrent operations, however, would not be safe as it would result in two 4 byte read transactions being conducted against the shared buffer, overlapping regions where 8 byte transactions are also taking place.

Synchronization Options

By default, Copy(To|From) operations to the same regions of memory attempt to synchronize-with each other by adding memory_order_release semantics to each of the atomic store operations executed during a call to CopyTo, and memory_order_acquire semantics to each of the atomic load operations executed during a call to CopyFrom.

Depending on the use case, however, it is possible that synchronizing like this might not be as efficient as using a thread fence instead. Users may control the synchronization behavior of the operation using the first template parameter of the call to Copy(To|From), which must be a member of the SyncOpt enumeration. The options are as follows:

  1. SyncOpt::AcqRelOps. This is the default option, and causes each atomic load/store, to use memory_order_acquire/memory_order_release, as appropriate, during the transfer.
  2. SyncOpt::Fence. Instead of synchronizing each of the load/store operations individually, all atomic load/stores are executed with memory_order_relaxed, and thread fences are used instead. CopyTo operations will be proceeded by a memory_order_release thread fence, while CopyFrom operations will be followed with a memory_order_acquire thread fence.
  3. SyncOpt::None. No synchronization will be added to the transfer operation. No explicit thread fences will be generated, and all atomic load/store operations will use memory_order_relaxed.

Extreme care should be taken when using SyncOpt::None. It is almost always the case that at least some synchronization will be needed when publishing and consuming data concurrently. The SyncOpt::None option is offered for users who may need to move data to/from multiple disjoint regions of shared memory, and wish to use fences to achieve synchronization. In this case, the first/last (CopyTo/CopyFrom) operation in the sequence should use a fence, while other operations would choose SyncOpt::None avoiding the need for superfluous load/store or thread fence synchronization. For example:

void PublishData(const Foo& foo1, const Foo& foo2, const Bar& bar) {
  WellDefinedCopyTo<SyncOpt::Fence>(&shared_foo1, &foo1, sizeof(foo1));
  WellDefinedCopyTo<SyncOpt::None>(&shared_foo2, &foo2, sizeof(foo2));
  WellDefinedCopyTo<SyncOpt::None>(&shared_bar1, &bar1, sizeof(bar1));

void ObserveData(Foo& foo1, Foo& foo2, Bar& bar) {
  WellDefinedCopyFrom<SyncOpt::None>(&foo1, &shared_foo1, sizeof(foo1));
  WellDefinedCopyFrom<SyncOpt::None>(&foo2, &shared_foo2, sizeof(foo2));
  WellDefinedCopyFrom<SyncOpt::Fence>(&bar1, &shared_bar1, sizeof(bar1));

Alignment Optimizations

If alignment of a transfer can be compile-time guaranteed to be greater than or equal to the maximum atomic transfer granularity of 8 bytes, a minor optimization can be achieved during the transfer by skipping the transfer phase which brings the operation into 8 byte alignment. Users can access this optimization by specifying the guaranteed alignment of their operation as the second template parameter of the Copy(To|From) operation. For example:

template <typename T>
void PublishData(const T& src, T& dst) {
  WellDefinedCopyTo<SyncOpt::AcqRelOps, alignof(T)>(&dst, &src, sizeof(T));

template <typename T>
void ObserveData(const T& src, T& dst) {
  WellDefinedCopyFrom<SyncOpt::AcqRelOps, alignof(T)>(&dst, &src, sizeof(T));


In order to make life a bit easier for users who need copy data in a well defined way into and out of structures, a helper class named WellDefinedCopyable<T> is offered.

Users may wrap any trivially copyable type, T in one of these wrapper instances, and the use the provided Update and Read methods to copy data into and out of the contained T instance, respectively. These methods, by design, deliberately restrict the ways that the user can gain access to the underlying storage, forcing them make use of the lowest level well-defined transfer functions.

Constructor parameters are directly forwarded to the underlying T instance.

WellDefinedCopyable<Foo> default_constructed;
WellDefinedCopyable<Foo> explicit_construction{45};
WellDefinedCopyable<Foo> moar_args{"Foo", 45, "Bar", 34.4};

Just remember that T (and therefore all of its data members) must be trivially copyable.

Explicit synchronization

The wrapper's Update and Read methods allow the user to specify the synchronization option to use, with a default of SyncOpt::AcqRelOps, just like the WellDefinedCopy(To|From) functions do. Because of the somewhat awkward dependent name rules of C++, the type of explicit synchronization desired can be specified using a type-tagging pattern, instead of needing to specify the sync option as an explicit template parameter.

WellDefinedCopyable<Foo> shared_foo;
Foo my_foo;

shared_foo.Read<SyncOpt::Fence>(my_foo);          // this does not work.
shared_foo.template Read<SyncOpt::Fence>(my_foo); // this is one way to make it work.
shared_foo.Read(my_foo, SyncOpt_Fence);           // this reads a bit better.

Aliases for the synchronization type tags are as follows. | enum class | type tag instance | |--------------------|-------------------| | SyncOpt::AcqRelOps | SyncOpt_AcqRelOps | | SyncOpt::Fence | SyncOpt_Fence | | SyncOpt::None | SyncOpt_None |

Raw storage access

User don‘t always have to access their T instance’s storage only by copying data into or out of it. Direct read-only access may be obtained using the WellDefinedCopyable<T>'s unsynchronized_get method, however users should exercise caution when choosing to do this.

Accessing the buffer using unsynchronized_get is only safe if the user can guarantee that no write operations may be concurrently performed against the storage while the user is reading the instance.

One example of a legitimate use of this method might be when a user is operating in the write exclusive portion of a sequence lock. They are guaranteed to be the only potential writer of the wrapped object, so while it is still important that they continue to use Update when they wish to mutate their instance of T, it is OK for them to read T directly without using Read as this will not cause any undefined behavior when done concurrently with other readers in the system.



Sequence locks are synchronization primitives which allow for concurrent read access to a set of data without ever excluding write updates. Reads are performed as transactions, which succeed if and only if there is no concurrent write operation which overlaps with the read transaction. Sequence locks can be useful in patterns where any of the following conditions hold:

  • Read operations are expected to greatly out-number write operations, and high levels of read concurrency are desired.
  • Write operations must never be delayed by concurrent read operations.
  • Readers have strictly read-only access to the shared state of the published data. No modifications of the state are allowed, as would be required when using a shared synchronization building-block such as a reader/writer lock obtained for shared access.

To assist in implementing data sharing via a sequence lock, libconcurrent offers the SeqLock primitive. The SeqLock behaves like a spinlock when acquired exclusively for write access, while still allowing concurrent read transactions to take place.


In order to properly implement a sequence lock pattern, there are a few rules which must be obeyed at all times.

  1. Data protected by a SeqLock may be both read and written concurrently, therefore care must be taken to always access the data in a way which is free from data races.
  2. Reads of, and writes to the data protected by the SeqLock must always properly synchronize-with the internals of the lock in order to ensure proper behavior on architectures with weak memory ordering.
  3. No decisions based on protected data should ever be made during a read transaction. It is only after a read transaction has successfully concluded that a program is guaranteed to have made a coherent observation of the protected data.

Given a sequence of write transactions, a read transaction has made a “coherent” observation if all of the values of the members of the protected data is observes came from a single write transaction. If it ever might have observed values written by two different write transactions, the read transaction must fail, and the user may choose to either retry the operation, or give up.

Patterns for properly using SeqLocks in the kernel.

Here are a small set of patterns which demonstrate how to properly observe and make updates to a set of data protected by a SeqLock. It is strongly advised that you follow these patterns exactly as presented. Do not deviate from the patterns presented here unless you are extremely knowledgable with both the internals of the SeqLock implementation, its synchronization requirements, and the formal C++ memory model. Even then, you probably don't want to deviate from these patterns without an extremely compelling reason.

Each of these examples will be shown with the assumption that the code is being used in the context of the Zircon kernel. While it is possible to use SeqLock's in user-mode, they only make sense when being used to read data from a piece of memory shared with the kernel, where all updates to the protected data are done from the kernel.

This is because user mode has no guaranteed way to prevent a situation where their thread might become preempted in the middle of a write transaction. Any readers attempting to read data concurrently with this write transaction are going to get stuck, spinning at the start of the transaction until either the writer is re-scheduled and finishes, or they themselves exhaust their timeslice and are preempted.

The simplest example.

Let's start with a simple setup. We will define a class which contains an instance of a structure (Foo) which is guarded by an instance of a SeqLock. We will declare a method Update which takes a constant reference to a Foo instance and updates the local contents of foo_ with it. Likewise, we will declare an Observe method which will perform a successful observation of the internal foo_, and return the observed copy of the data to the caller.

#include <lib/kconcurrent/seqlock.h>

struct Foo {
  uint32_t a, b;

class MyClass {
  void Update(const Foo& foo);
  Foo Observe();

  DECLARE_SEQLOCK(MyClass) seq_lock_;
  SeqLockPayload<Foo, decltype(seq_lock_)> foo_ TA_GUARDED(seq_lock_);

Note that our class:

  1. Declares the SeqLock instance seq_lock_.
  2. Declares the instance of Foo as being wrapped in a SeqLockPayload<...> template.
  3. Declares foo_ instance as being TA_GUARDED by the instance of the lock.

Always follow these steps.

Step #1 declares the instance of the lock using a macro which ensures that the instance is properly instrumented by lockdep (when lockdep is enabled). This allows us to use lockdep defined RAII style Guards, in addition to getting the runtime cycle analysis provided by lockdep. Finally, this also automatically chooses synchronization methodology that we will use to ensure that we get proper, coherent observations of the payloads protected by the lock. By default, this is atomic Acquire/Release operations used on individual payload loads/stores.

Step #2 (wrapping the Foo instance in a SeqLockPayload<...>) does two things for us.

First, it will prevent anyone from accidentally reaching in and reading or writing the contents of the protected data directly, running the risk of failing to access the data in a atomic fashion (which could lead to a data-race).

Second, it binds the synchronization method chosen during the declaration of the lock, to the synchronization method implemented by the payload wrapper. This prevents a user from accidentally accessing the data using a sync method which does not match that implemented by the lock instance, leading to the possibility of an incoherent observation being made by a reader.

Finally, Step #3. Flagging the protected data as being TA_GUARDED by the lock guarantees that clang static thread analysis (when enabled) will catch at compile time any attempts to access the protected data while not inside a SeqLock transaction, and well prevent all attempts to mutate the protected data during a read transaction instead of a write transaction.

Now let's take a look at the implementation of Update and Observe

void MyClass::Update(const Foo& foo) {
  Guard<SeqLock<>, ExclusiveIrqSave> lock{&seq_lock_};

Foo MyClass::Observe() {
  Foo ret;

  bool success;
  do {
    Guard<SeqLock<>, SharedNoIrqSave> lock{&seq_lock_, success};
  } while (!success);

  return ret;

Update is extremely simple. We simply:

  1. Declare a lockdep::Guard with the appropriate type and access mode (SeqLock<> and ExclusiveIrqSave)
  2. Copy our payload into the structure using the WellDefinedCopyWrapper's Update methods.

The lockdep::Guard guarantees that we will properly disable and re-enable interrupts, as well as acquire and release the lock exclusively, before and after the update of the payload. Disabling and re-enabling interrupts guarantees that we will never be preempted during the update operation itself, which is important to preventing readers from spinning pointlessly. Acquiring the lock exclusively is required in order to be able to Update the paylod.

Observe is almost as simple, but has a few extra details involved. Read transactions are not guaranteed to succeed, so we need a loop to try again in he case of failure. In this example, we don't define any timeout conditions, we simply try repeatedly until we eventually succeed.

The lockdep::Guard guard we use:

  1. Uses the access type SharedNoIrqSave. Shared is the access level we use when reading the protected data, and we do not disable IRQs during this operation. We don‘t need to, and we don’t really want to, as we don't want to spin for any length of time with interrupts off attempting to start the transaction.
  2. Is declared in the scope of the while body, while the success bool is declared outside of the while body scope. This is important because the end of the transaction and the determination of success or failure happens when the guard destructs, and the results are recorded in success. The guard must destruct, and therefore is declared in the while body, but the success needs to be evaluated as part of the while predicate, so it must exist in a scope outside of the while body.

Finally, we copy our protected data into a local stack-allocated Foo instance while inside the guard, and return that copy to the caller after we have ended the transaction successfully.

Reads of data while writing

Writes protected by a SeqLock are exclusive, meaning no two writes can ever take place at the same time. They must happen sequentially with a well defined order. Therefore we can actually read our protected data while the lock is held exclusively without needing to consider either memory order or data race issues. What we can never do, however, is update the contents without using the SeqLockPayload<...>‘s Update method. Let’s take a quick look at two simple examples of this:

class MyClass {
  // ...

  void Sort();
  void Inc(uitn32_t amt);

void MyClass::Sort() {
  Guard<SeqLock<>, ExclusiveIrqSave> lock{&seq_lock_};

  const Foo& current_foo = foo_.unsynchronized_get();
  if (current_foo.a > current_foo.b) {
    Foo new_foo{current_foo.b, current_foo.a};

void MyClass::Inc(uitn32_t amt) {
  Guard<SeqLock, ExclusiveIrqSave> lock{&seq_lock_};

  Foo new_foo = foo_.unsynchronized_get();
  new_foo.a += amt;
  new_foo.b += amt;

We declare two new methods for our class. Sort (as the name implies) sorts the elements of the protected Foo instance in ascending order. It grabs a const Foo& from the payload wrapper‘s unsynchronized_get method, then based on the relationship between the protected data’s a and b. It either constructs a new Foo instance on the stack with the values of the fields swapped, then updates foo_ using the Update method, or it simply exits because the elements are already in the desired order.

Note that we are actually directly accessing the contends of foo_ via the const Foo& we obtained from our call to unsynchronized_get(). This is OK when we have the SeqLock locked exclusively because we are the only possible writer in the lock. No other writers can issue any stores, so it is impossible to create a data-race, even if our loads are non-atomic.

The second example, Inc is going to increment both of the fields of the foo_ instance by amt. In this case, we also read the current state of foo_ via a call to unsynchronized_get(), but this time we do it to copy-construct a local copy new_foo, then increment both members, and finally update the protected data using a call to WellDefinedCopyWrapper<>::Update().

Never attempt to use unsynchronised_get() during a read transaction. The data being observed in the middle of a read transaction:

  1. Could be getting concurrently written to by a writer, creating a data-race, and
  2. Even if no writes were happening, there absolutely no guarantee that the loads performed against the data would provide a coherent view of the data.

If you have clang static thread analysis enabled (you should), and you have annotated your protected data as being TA_GUARDED by your lock, the static analysis should catch this mistake at compile time. If you are using some other tool-chain, or you have not enabled static analysis, this mistake will get missed, and you will be Very Sad.

Partial updates and partial observations.

Users of SeqLocks can also protect multiple sets of data with one SeqLock. The easiest way is to simply introduce more structures wrapped in SeqLockPayload<...>s.

struct Foo { uint32_t a, b; };
struct Bar { uint32_t c, d; };

class MyClass {
  void Update(const Foo& foo);
  void Update(const Bar& bar);
  void Update(const Foo& foo, const Bar& bar);

  Foo ObserveFoo();
  Bar ObserveBar();
  ktl::pair<Foo, Bar> Observe();

  DECLARE_SEQLOCK(MyClass) seq_lock_;
  SeqLockPayload<Foo, decltype(seq_lock_)> foo_ TA_GUARDED(seq_lock_);
  SeqLockPayload<Bar> decltype(seq_lock_)> bar_ TA_GUARDED(seq_lock_);

We may now observe or update one, or the other, or both of these containers of protected data, provided we follow the previously established rules for obtaining the SeqLock as we do.

Fence-to-Fence Synchronization

As noted earlier, the default synchronization mechanism used by SeqLock is to use atomic loads/stores with Acquire/Release semantics whenever accessing the protected payload contents. This is not the only option, however. Depending on the specific underlying machine architecture and the size of the payload which needs to be observed/published, it might be more efficient to use Relaxed loads/stores, and use fence-to-fence synchronization instead.

Switching approaches should be pretty easy overall. All we need to do is to update how we declare our lock, as well as the lock type specified when we use a Guard. So:

class MyClass {
  void Update(const Foo& foo);

  DECLARE_SEQLOCK(MyClass) seq_lock_;
  SeqLockPayload<Foo, decltype(seq_lock_)> foo_ TA_GUARDED(seq_lock_);


class MyClass {
  void Update(const Foo& foo);

  SeqLockPayload<Foo, decltype(seq_lock_)> foo_ TA_GUARDED(seq_lock_);


void MyClass::Update(const Foo& foo) {
  Guard<SeqLock<>, ExclusiveIrqSave> lock{&seq_lock_};


// Either this...
void MyClass::Update(const Foo& foo) {
  Guard<SeqLockFenceSync, ExclusiveIrqSave> lock{&seq_lock_};

// .. or this
void MyClass::Update(const Foo& foo) {
  Guard<SeqLock<::concurrent::SyncOpt::Fence>, ExclusiveIrqSave> lock{&seq_lock_};

Blocking/Spinning behavior

Both the BeginReadTransaction and the Acquire operations have the potential to spin-wait if there happens to be another thread which has currently Acquireed the lock for exclusive access. Technically, the operations never result in the thread blocking in the scheduler, however they will spin waiting for the lock to become uncontested before proceeding.

If users are executing in a time sensitive context, or a read operation is being conducted against data which is being updated by another (potentially malicious) process, Try versions of the BeginReadTransaction and the Acquire may be used along with a timeout to limit the amount of spinning which may eventually take place.

  • bool TryBeginReadTransaction(ReadTransactionToken& out_token, zx_duration_t timeout)
  • bool TryBeginReadTransactionDeadline(ReadTransactionToken& out_token, zx_time_t deadline)
  • bool TryAcquire(zx_duration_t timeout)
  • bool TryAcquireDeadline(zx_time_t deadline)

Note that there is currently no lockdep::Guard adapter defined which works with timeouts/deadlines, so we will need to manually manage locking/unlocking and manipulating read tokens ourselves. Additionally, because of the fact that lockdep instrumented SeqLocks are actually wrapped in an outer LockDep<...> wrapper, it can be a bit awkward to remember how to declare the proper type for the ReadTransactionToken we need to use with the Try methods. The kernel environment provides a helper called SeqLockReadTransactionToken which can be used to automatically deduce the proper type for the token based on the lock, and this is the technique used in the example below.

For example:

zx_status_t MyClass::UpdateWithTimeout(const Foo& foo, zx_duration_t timeout) {
  if (!seq_lock_.lock().TryAcquire(timeout)) {
    return ZX_ERR_TIMED_OUT;
  return ZX_OK;

zx::result<Foo> MyClass::ObserveWithTimeout(zx_duration_t timeout) {
  // Instead of needing to say this to decalre our token:
  // decltype(seq_lock_)::LockType::ReadTransactionToken token;
  // We can say this instead:
  SeqLockReadTransactionToken token{seq_lock_};
  zx_time_t deadline = zx_deadline_after(timeout);
  Foo ret;

  do {
    if (!seq_lock_.lock().TryBeginReadTransactionDeadline(token, deadline)) {
      return zx::error(ZX_ERR_TIMED_OUT);
  } while (!seq_lock_.lock().EndReadTransaction(token));

  return zx::ok(ret);