The behaviour of std::async() function, when used with std::launch::async, may be trivially emulated as follows:

template <class F, class... Args>
auto async(F&& f, Args&&... args)
{
  return post(
    use_future(
      std::bind(std::forward<F>(f),
        std::forward<Args>(args)...)));
}

Starting from the inside out, the expression:

std::bind(std::forward<F>(f),
  std::forward<Args>(args)...)

creates a function object that will invoke f with the specified arguments. Next:

use_future(...)

returns an object that will be lazily converted into a function object similar tostd::packaged_task<>. We could also have used std::packaged_task<> directly, as in:

std::packaged_task<
  std::result_of_t<
    std::decay_t<F>(std::decay_t<Args>...)>>(...)

In this example, the use_future() function saves on typing by determining the return type of F for us. Finally:

post(...)

submits the function object for execution on another thread, and then returns immediately. When we submit the result of use_future() (or if we were to submit a std::packaged_task<>), post() automatically deduces its return type to be the std::future<> type produced by the task. This future object is then returned from our version of async(). Note that, unlike std::async(), the returned future object's destructor will not block.

In the Active Object design pattern, all operations associated with an object are run in its own private thread.

To implement an active object, we begin by defining a class member that is a thread pool containing a single thread.

class bank_account
{
  int balance_ = 0;
  mutable thread_pool pool_{1};
  // ...
};

We then define each public member function so that it posts its implementation to the thread pool.

class bank_account
{
  // ...
  void deposit(int amount)
  {
    post(pool_,
      use_future([=]
        {
          balance_ += amount;
        })).get();
  }
  // ...
};

In more detail, to implement an active object operation we begin by defining the body of the function:

[=]
{
  balance_ += amount;
}

which we then wrap in a lazily created std::packaged_task<> equivalent:

use_future(...)

Finally, we submit the packaged task to the pool and wait for it to complete. When we submit the result of use_future(), post() automatically deduces its return type to be the std::future<> type produced by the task. We can use this future to block until the operation is complete.

post(...).get();

An Activatable object is a variant of the Active Object pattern where the object does not have a private thread of its own. Instead, it can borrow one of the calling threads to process operations^[1]. However, like Active Object, it ensures that all member state changes do not occur on more than one thread at a time.

To implement an activatable object, we create a strand on the system executor.

class bank_account
{
  int balance_ = 0;
  mutable strand<system_executor> strand_;
  // ...
};

We then define each public member function so that it dispatches its implementation to the strand.

class bank_account
{
  // ...
  void deposit(int amount)
  {
    dispatch(strand_,
      use_future([=]
        {
          balance_ += amount;
        })).get();
  }
  // ...
};

Recall that a system_executor object embodies this rule:

while a strand embodies this rule:

Finally, the call to dispatch() means:

Thus, when we combine system_executor, strand and dispatch():

dispatch(strand_, []{ ... });

we are effectively saying: if the strand is not busy, run the function object immediately. If there is no contention on the strand, latency is minimised. If there is contention, the strand still ensures that the function object never runs concurrently with any other function object submitted through the same strand.

The Leader/Followers design pattern is a model where multiple threads take turns to wait on event sources in order to dispatch and process incoming events.

Consider an example where a connection handler is responsible for receiving messages from a client via UDP. The Leader/Followers pattern is implemented using a thread_pool object:

class connection_handler
{
  // ...
private:
  udp_socket socket_;
  thread_pool thread_pool_;
  // ...
};

and involves the sequence of operations below.

void connection_handler::receive_and_dispatch()
{

The leader thread waits for the next message to arrive.

  char buffer[1024];
  std::size_t length = socket_.receive(buffer, sizeof(buffer));

A new message has arrived. The leader thread promotes a follower to become the new leader.

  std::experimental::concurrency::post(thread_pool_,
      [this]{ receive_and_dispatch(); });

The now former leader processes the message.

  // Process the new message and pass it to the order management bus.
  std::istringstream is(std::string(buffer, length));
  order_management::new_order event;
  if (is >> event)
    order_management_bus_.dispatch_event(event);
}

When the function returns, the former leader automatically returns to the pool as a follower thread.

Asynchronous operations are often chained, and in many cases an object may be associated with two or more chains. For example, an object to manage a connection may contain one chain to do the writing, and another to do the reading:

class connection
{
  tcp::socket socket_;
  mutable_buffers_1 in_buffer_;
  mutable_buffers_1 out_buffer_;

  // ...

  void do_read()
  {
    socket_.async_read_some(in_buffer_,
      [this](error_code ec, size_t n)
      {
        // ... process input data ...
        if (!ec) do_read();
      });
  }

  void do_write()
  {
    // ... generate output data ...
    async_write(socket_, out_buffer_,
      [this](error_code ec, size_t n)
      {
        if (!ec) do_write();
      });
  }
};

When these chains are run on a single-threaded event loop, it is not possible for more than one completion handler to run at any given time. This means that no synchronisation is required to protected shared data. However, if handlers are executed on a thread pool then some form of synchronisation will be required to avoid introducing data races.

The proposed library provides the strand<> template to synchronise handlers. A strand ensures that completion handlers never run concurrently, and explicit synchronisation (such as a mutex) is still not required to protect shared data. To implement this, we use the one strand for all asynchronous operations associated with the object.

class connection
{
  tcp::socket socket_;
  mutable_buffers_1 in_buffer_;
  mutable_buffers_1 out_buffer_;
  strand<io_service::executor_type> strand_;

  // ...

  void do_read()
  {
    socket_.async_read_some(in_buffer_,
      bind_executor(strand_, [this](error_code ec, size_t n)
        {
          // ... process input data ...
          if (!ec) do_read();
        }));
  }

  void do_write()
  {
    // ... generate output data ...
    async_write(socket_, out_buffer_,
      bind_executor(strand_, [this](error_code ec, size_t n)
        {
          if (!ec) do_write();
        }));
  }
};

The bind_executor function is used to associate an executor with an object. In this example, we used bind_executor to associate the strand with each of the lambdas. The bind_executor function works with any executor or execution context. For example, here we associate a thread pool with a lamdba:

async_getline(std::cin,
    bind_executor(pool, [](std::string line)
      {
        std::cout << "Line: " << line << "\n";
      }));

Rather than using the bind_executor function, the associated executor may be manually specified by providing a nested executor_type typedef and get_executor() member function.

class line_printer
{
public:
  typedef loop_scheduler::executor_type executor_type;

  explicit line_printer(loop_scheduler& s)
    : executor_(s.get_executor())
  {
  }

  executor_type get_executor() const noexcept
  {
    return executor_;
  }

  void operator()(std::string line)
  {
    std::cout << "Line: " << line << "\n";
  }

private:
  loop_scheduler::executor_type executor_;
};

// ...

async_getline(std::cin, line_printer(scheduler));

For this to work correctly, the async_getline asynchronous operation must participate in an executor-aware model. To be executor-aware, an asynchronous operation must:

Our async_getline operation can then be written as follows:

template <class Handler>
void async_getline(std::istream& is, Handler handler)
{

The make_work_guard function automatically obtains the associated executor and creates an executor_work_guard object for it.

  auto work = make_work_guard(handler);

The asynchronous operation itself is posted outside of the associated executor. This is because we want the line reading to be performed asynchronously with respect to the caller.

  post([&is, work, handler=std::move(handler)]() mutable
      {
        std::string line;
        std::getline(is, line);

Once the asynchronous work is complete, we execute the completion handler via its associated executor.

        // Pass the result to the handler, via the associated executor.
        dispatch(work.get_executor(),
            [line=std::move(line), handler=std::move(handler)]() mutable
            {
              handler(std::move(line));
            });
      });
}

When composing asynchronous operations, intermediate operations can simply reuse the associated executor of the final handler.

template <class Handler>
void async_getlines(std::istream& is, std::string init, Handler handler)
{
  // Get the final handler's associated executor.
  auto ex = get_associated_executor(handler);

  // Use the associated executor for each operation in the composition.
  async_getline(is,
      bind_executor(ex, [&is, lines=std::move(init), handler=std::move(handler)]
        (std::string line) mutable
        {
          if (line.empty())
            handler(lines);
          else
            async_getlines(is, lines + line + "\n", std::move(handler));
        }));
}

This ensures that all intermediate completion handlers are correctly executed according to the caller's executor's rules.

A pipeline is a sequence of two or more long-running functions, known as stages, with each stage passing data to the next via a queue. The initial stage acts as a source of data, the intermediate stages act as filters, and the final stage as a sink.

As an example, let us consider a small framework for implementing pipelines. The function used to construct a pipeline is declared as:

template <class F, class... Tail>
  std::future<void> pipeline(F f, Tail... t);

This function returns a future that can be used to wait until the pipeline is complete. The initial stage of the pipeline must be a function with signature:

void initial(queue_front<T0> out);

The intermediate stages have signature:

void intermediate(queue_back<Tn> in, queue_front<Tn+1> out);

The pipeline's final stage has the signature:

void final(queue_back<TN> in);

By default, we want each stage of a pipeline to have its own thread. The pipeline framework achieves this by calling get_associated_executor with two arguments:

template <class F, class... Tail>
std::future<void> pipeline(F f, Tail... t)
{
  // ...
  auto ex = get_associated_executor(f, thread_executor());
  // ...
}

The thread_executor class is a custom executor type defined for the example. It starts a new thread for every function passed to dispatch, post or defer. If the function object type F already has an associated executor then that executor will be used. The thread_executor is used for types that do not specify an associated executor.

So, when we construct and run a pipeline like this:

void reader(queue_front<std::string> out);
void filter(queue_back<std::string> in, queue_front<std::string> out);
void upper(queue_back<std::string> in, queue_front<std::string> out);
void writer(queue_back<std::string> in);

// ...

thread_pool pool;
auto f = pipeline(reader, filter, bind_executor(pool, upper), writer);
f.wait();

we are specifying that the the upper stage should run on the thread pool, while reader, filter and writer should use the default behaviour of launching a new thread.

The Actor model is a model for concurrency where objects, known as actors, communicate only by sending and receiving messages. Each actor's state is accessed only by its own internal thread or strand. This means that actors are inherently thread-safe.

To illustrate how executors may be used to facilitate actors, a tiny actor framework is included with the executors reference implementation. This framework is loosely based on the Theron library^[2].

To implement an actor using this framework, we start by deriving a class from actor:

class member : public actor
{
  // ...

When constructing an actor, we specify the executor to be used:

  explicit member(executor e)
    : actor(std::move(e))
  {
    // ...
  }

The polymorphic type executor is used to allow the selection of an actor's executor to be delayed until runtime. All of an actor's message handlers are executed according to that policy. This could be a thread pool executor, but we may equally construct actors with an executor that knows about priorities.

The actor's message handlers are member functions, identified by argument type, and may be arbitrarily registered or deregistered:

  void init_handler(actor_address next, actor_address from)
  {
    // ...
    register_handler(&member::token_handler);
    deregister_handler(&member::init_handler);
  }

Internally, the actor framework uses a per-actor strand to ensure that the member functions are never called concurrently.

To send a message between actors we use either actor::send() or actor::tail_send(). The send() operation is implemented in terms of the actor's executor's post() member function. The tail_send() function is a distinct operation and conveys additional information about the caller's intent which may be used to optimise inter-actor messaging. It is implemented in terms of defer().

  void token_handler(int token, actor_address /*from*/)
  {
    // ...
    tail_send(msg, to);
  }

  // ...
};

Executor objects are lightweight and copyable to allow us to encapsulate all sorts of additional information and behaviour on a fine-grained basis. One use case for this is attaching priorities to function objects or tasks.

We begin by defining our priority scheduler class as an execution context. Internally, this class uses a priority queue to store pending function objects.

class priority_scheduler : public execution_context
{
  // ...

private:

  // ...

  struct item_comp
  {
    bool operator()(
        const std::shared_ptr<item_base>& a,
        const std::shared_ptr<item_base>& b)
    {
      return a->priority_ < b->priority_;
    }
  };

  std::mutex mutex_;
  std::condition_variable condition_;
  std::priority_queue<
    std::shared_ptr<item_base>,
    std::vector<std::shared_ptr<item_base>>,
    item_comp> queue_;
  bool stopped_ = false;
};

The priority_scheduler class provides a nested class executor_type which satisfies the executor type requirements, and a member function get_executor() to obtain an executor object. On construction, an executor_type object captures a reference to the priority scheduler, as well as the specified priority value.

class priority_scheduler : public execution_context
{
public:
  class executor_type
  {
  public:
    executor_type(priority_scheduler& ctx, int pri) noexcept
      : context_(ctx), priority_(pri)
    {
    }

    // ...

  private:
    priority_scheduler& context_;
    int priority_;
  };

  executor_type get_executor(int pri = 0) noexcept
  {
    return executor_type(*this, pri);
  }

  // ...
};

When a function object is submitted, the executor uses its stored priority to insert the function into the correct position in the priority queue:

class priority_scheduler : public execution_context
{
public:
  class executor_type
  {
  public:

    // ...

    template <class Func, class Alloc>
    void post(Func f, const Alloc& a)
    {
      auto p(std::allocate_shared<item<Func>>(a, priority_, std::move(f)));
      std::lock_guard<std::mutex> lock(context_.mutex_);
      context_.queue_.push(p);
      context_.condition_.notify_one();
    }

    // ...
  };

  // ...
};

The priority scheduler's executors can then be used like any other:

priority_scheduler sched;
auto low = sched.get_executor(0);
auto med = sched.get_executor(1);
auto high = sched.get_executor(2);
// ...
dispatch(low, []{ std::cout << "1\n"; });
dispatch(med, []{ std::cout << "2\n"; });
dispatch(high, []{ std::cout << "3\n"; });

Throughout this Technical Specification, the names of the template parameters are used to express type requirements, as listed in the table below.

namespace std {
namespace experimental {
inline namespace concurrency_v2 {

  template<class CompletionToken, class Signature, class = void>
    class async_result;

  template<class CompletionToken, class Signature>
    struct async_completion;

  template<class T, class ProtoAllocator = allocator<void>>
    struct associated_allocator;

  template<class T, class ProtoAllocator = allocator<void>>
    using associated_allocator_t = typename associated_allocator<T, ProtoAllocator>::type;

  // get_associated_allocator:

  template<class T>
    associated_allocator_t<T> get_associated_allocator(const T& t) noexcept;
  template<class T, class ProtoAllocator>
    associated_allocator_t<T, ProtoAllocator>
      get_associated_allocator(const T& t, const ProtoAllocator& a) noexcept;

  enum class fork_event {
    prepare,
    parent,
    child
  };

  class execution_context;

  class service_already_exists;

  template<class Service> Service& use_service(execution_context& ctx);
  template<class Service, class... Args> Service&
    make_service(execution_context& ctx, Args&&... args);
  template<class Service> bool has_service(execution_context& ctx) noexcept;

  template<class T> struct is_executor;

  struct executor_arg_t { };
  constexpr executor_arg_t executor_arg = executor_arg_t();

  template<class T, class Executor> struct uses_executor;

  template<class T, class Executor = system_executor>
    struct associated_executor;

  template<class T, class Executor = system_executor>
    using associated_executor_t = typename associated_executor<T, Executor>::type;

  // get_associated_executor:

  template<class T>
    associated_executor_t<T> get_associated_executor(const T& t) noexcept;
  template<class T, class Executor>
    associated_executor_t<T, Executor>
      get_associated_executor(const T& t, const Executor& ex) noexcept;
  template<class T, class ExecutionContext>
    associated_executor_t<T, typename ExecutionContext::executor_type>
      get_associated_executor(const T& t, ExecutionContext& ctx) noexcept;

  template<class T, class Executor>
    class executor_binder;

  template<class T, class Executor, class Signature>
    class async_result<executor_binder<T, Executor>, Signature>;

  template<class T, class Executor, class ProtoAllocator>
    struct associated_allocator<executor_binder<T, Executor>, ProtoAllocator>;

  template<class T, class Executor, class Executor1>
    struct associated_executor<executor_binder<T, Executor>, Executor1>;

  // bind_executor:

  template<class Executor, class T>
    executor_binder<decay_t<T>, Executor>
      bind_executor(const Executor& ex, T&& t);
  template<class ExecutionContext, class T>
    executor_binder<decay_t<T>, typename ExecutionContext::executor_type>
      bind_executor(ExecutionContext& ctx, T&& t);

  template<class Executor>
    class executor_work_guard;

  // make_work_guard:

  template<class Executor>
    executor_work_guard<Executor>
      make_work_guard(const Executor& ex);
  template<class ExecutionContext>
    executor_work_guard<typename ExecutionContext::executor_type>
      make_work_guard(ExecutionContext& ctx);
  template<class T>
    executor_work_guard<associated_executor_t<T>>
      make_work_guard(const T& t);
  template<class T, class U>
    auto make_work_guard(const T& t, U&& u)
      -> decltype(make_work_guard(get_associated_executor(t, forward<U>(u))));

  class system_executor;
  class system_context;

  bool operator==(const system_executor&, const system_executor&);
  bool operator!=(const system_executor&, const system_executor&);

  class bad_executor;

  class executor;

  bool operator==(const executor& a, const executor& b) noexcept;
  bool operator==(const executor& e, nullptr_t) noexcept;
  bool operator==(nullptr_t, const executor& e) noexcept;
  bool operator!=(const executor& a, const executor& b) noexcept;
  bool operator!=(const executor& e, nullptr_t) noexcept;
  bool operator!=(nullptr_t, const executor& e) noexcept;

  // dispatch:

  template<class CompletionToken>
    DEDUCED dispatch(CompletionToken&& token);
  template<class Executor, class CompletionToken>
    DEDUCED dispatch(const Executor& ex, CompletionToken&& token);
  template<class ExecutionContext, class CompletionToken>
    DEDUCED dispatch(ExecutionContext& ctx, CompletionToken&& token);

  // post:

  template<class CompletionToken>
    DEDUCED post(CompletionToken&& token);
  template<class Executor, class CompletionToken>
    DEDUCED post(const Executor& ex, CompletionToken&& token);
  template<class ExecutionContext, class CompletionToken>
    DEDUCED post(ExecutionContext& ctx, CompletionToken&& token);

  // defer:

  template<class CompletionToken>
    DEDUCED defer(CompletionToken&& token);
  template<class Executor, class CompletionToken>
    DEDUCED defer(const Executor& ex, CompletionToken&& token);
  template<class ExecutionContext, class CompletionToken>
    DEDUCED defer(ExecutionContext& ctx, CompletionToken&& token);

  template<class Executor>
    class strand;

  template<class Executor>
    bool operator==(const strand<Executor>& a, const strand<Executor>& b);
  template<class Executor>
    bool operator!=(const strand<Executor>& a, const strand<Executor>& b);

  template<class ProtoAllocator = allocator<void>>
    class use_future_t;

  constexpr use_future_t<> use_future = use_future_t<>();

  template<class ProtoAllocator, class Result, class... Args>
    class async_result<use_future_t<ProtoAllocator>, Result(Args...)>;

  template<class R, class... Args, class Signature>
    class async_result<packaged_task<Result(Args...)>, Signature>;

} // inline namespace concurrency_v2
} // namespace experimental

  template<class Allocator>
    struct uses_allocator<experimental::concurrency_v2::executor, Allocator>
      : true_type {};

} // namespace std

The async_result class template is a customization point for asynchronous operations. Template parameter CompletionToken specifies the model used to obtain the result of the asynchronous operation. Template parameter Signature is the call signature (C++Std [func.def]) for the completion handler type invoked on completion of the asynchronous operation. The async_result template:

— transforms a CompletionToken into a completion handler type that is based on a Signature; and

— determines the return type and return value of an asynchronous operation's initiating function.

namespace std {
namespace experimental {
inline namespace concurrency_v2 {

  template<class CompletionToken, class Signature, class = void>
  class async_result
  {
  public:
    typedef CompletionToken completion_handler_type;
    typedef void return_type;

    explicit async_result(completion_handler_type&) {}
    async_result(const async_result&) = delete;
    async_result& operator=(const async_result&) = delete;

    return_type get() {}
  };

} // inline namespace concurrency_v2
} // namespace experimental
} // namespace std

The template parameter CompletionToken shall be an object type. The template parameter Signature shall be a call signature (C++Std [func.def]).

Specializations of async_result shall satisfy the Destructible requirements (C++Std [destructible]) in addition to the requirements in the table below. In this table, R is a specialization of async_result; r is a modifiable lvalue of type R; and h is a modifiable lvalue of type R::completion_handler_type.

Class template async_completion is provided as a convenience, to simplify the implementation of asynchronous operations that use async_result.

namespace std {
namespace experimental {
inline namespace concurrency_v2 {

  template<class CompletionToken, class Signature>
  struct async_completion
  {
    typedef async_result<decay_t<CompletionToken>,
      Signature>::completion_handler_type
        completion_handler_type;

    explicit async_completion(CompletionToken& t);
    async_completion(const async_completion&) = delete;
    async_completion& operator=(const async_completion&) = delete;

    see below completion_handler;
    async_result<decay_t<CompletionToken>, Signature> result;
  };

} // inline namespace concurrency_v2
} // namespace experimental
} // namespace std

The template parameter Signature shall be a call signature (C++Std [func.def]).

explicit async_completion(CompletionToken& t);

see below completion_handler;

Class template associated_allocator is an associator for the ProtoAllocator type requirements, with default candidate type allocator<void> and default candidate object allocator<void>().

namespace std {
namespace experimental {
inline namespace concurrency_v2 {

  template<class T, class ProtoAllocator = allocator<void>>
  struct associated_allocator
  {
    typedef see below type;

    static type get(const T& t, const ProtoAllocator& a = ProtoAllocator()) noexcept;
  };

} // inline namespace concurrency_v2
} // namespace experimental
} // namespace std

Specializations of associated_allocator shall satisfy the requirements in the table below. In this table, X is a specialization of associated_allocator for the template parameters T and ProtoAllocator; t is a value of (possibly const) T; and a is an object of type ProtoAllocator.

typedef see below type;

type get(const T& t, const ProtoAllocator& a = ProtoAllocator()) noexcept;

template<class T>
  associated_allocator_t<T> get_associated_allocator(const T& t) noexcept;

template<class T, class ProtoAllocator>
  associated_allocator_t<T, ProtoAllocator>
    get_associated_allocator(const T& t, const ProtoAllocator& a) noexcept;

Class execution_context implements an extensible, type-safe, polymorphic set of services, indexed by service type.

namespace std {
namespace experimental {
inline namespace concurrency_v2 {

  class execution_context
  {
  public:
    class service;

    // construct / copy / destroy:

    execution_context();
    execution_context(const execution_context&) = delete;
    execution_context& operator=(const execution_context&) = delete;
    virtual ~execution_context();

    // execution context operations:

    void notify_fork(fork_event e);

  protected:

    // execution context protected operations:

    void shutdown() noexcept;
    void destroy() noexcept;
  };

  // service access:
  template<class Service> typename Service::key_type&
    use_service(execution_context& ctx);
  template<class Service, class... Args> Service&
    make_service(execution_context& ctx, Args&&... args);
  template<class Service> bool has_service(const execution_context& ctx) noexcept;
  class service_already_exists : public logic_error { };

} // inline namespace concurrency_v2
} // namespace experimental
} // namespace std

Access to the services of an execution_context is via three function templates, use_service<>, make_service<> and has_service<>.

In a call to use_service<Service>(), the type argument chooses a service. If the service is not present in an execution_context, an object of type Service is created and added to the execution_context. A program can check if an execution_context implements a particular service with the function template has_service<Service>().

Service objects may be explicitly added to an execution_context using the function template make_service<Service>(). If the service is already present, make_service exits via an exception of type service_already_exists.

Once a service reference is obtained from an execution_context object by calling use_service<>, that reference remains usable until a call to destroy().

execution_context();

~execution_context();

void notify_fork(fork_event e);

void shutdown() noexcept;

void destroy() noexcept;

template<class Service> typename Service::key_type&
  use_service(execution_context& ctx);

template<class Service, class... Args> Service&
  make_service(execution_context& ctx, Args&&... args);

template<class Service> bool has_service(const execution_context& ctx) noexcept;

namespace std {
namespace experimental {
inline namespace concurrency_v2 {

  class execution_context::service
  {
  protected:
    // construct / copy / destroy:

    explicit service(execution_context& owner);
    service(const service&) = delete;
    service& operator=(const service&) = delete;
    virtual ~service();

    // service observers:

    execution_context& context() noexcept;

  private:
    // service operations:

    virtual void shutdown() noexcept = 0;
    virtual void notify_fork(fork_event e) {}

    execution_context& context_; // exposition only
  };

} // inline namespace concurrency_v2
} // namespace experimental
} // namespace std

explicit service(execution_context& owner);

execution_context& context() noexcept;

The class template is_executor can be used to detect executor types satisfying the Executor type requirements.

namespace std {
namespace experimental {
inline namespace concurrency_v2 {

  template<class T> struct is_executor;

} // inline namespace concurrency_v2
} // namespace experimental
} // namespace std

T shall be a complete type.

Class template is_executor is a UnaryTypeTrait (C++Std [meta.rqmts]) with a BaseCharacteristic of true_type if the type T meets the syntactic requirements for Executor, otherwise false_type.

namespace std {
namespace experimental {
inline namespace concurrency_v2 {

  struct executor_arg_t { };
  constexpr executor_arg_t executor_arg = executor_arg_t();

} // inline namespace concurrency_v2
} // namespace experimental
} // namespace std

The executor_arg_t struct is an empty structure type used as a unique type to disambiguate constructor and function overloading. Specifically, types may have constructors with executor_arg_t as the first argument, immediately followed by an argument of a type that satisfies the Executor requirements.