namespace tf {

/** @page release-2-2-0 Release 2.2.0 (2019/06/15)

%Taskflow 2.2.0 is the 3rd release in the 2.x line! 
This release includes several new changes such as tf::ExecutorObserverInterface,
tf::Executor, isolation of taskflow graph and executor, benchmarks, and so forth.
In particular, this release improve the performance of the work stealing scheduler.

@tableofcontents

@section release-2-2-0_download Download

%Taskflow 2.2.0 can be downloaded from <a href="https://github.com/cpp-taskflow/cpp-taskflow/releases/tag/v2.2.0">here</a>.

@section release-2-2-0_new_features New Features

@li A new executor class to isolate the execution module from a taskflow
@li A new observer interface to inspect the activities of an executor
@li A decomposable taskflow construction interface
@li A new work-stealing algorithm to improve the performance

@section release-2-2-0_breaks_and_deprecated_features Breaks and Deprecated Features

In this release, we isolated the executor interface from tf::Taskflow, 
and merge tf::Framework with tf::Taskflow.
This change largely improved the modularity and composability of %Taskflow
in creating clean task dependency graphs and execution flows.
Performance is also better.
While this introduced some breaks in tf::Taskflow,
we have managed to make it as less painful as possible for users to adapt to the new change.

Previously, tf::Taskflow is a hero class that manages 
both a task dependency graph and the execution of all graphs including frameworks.
For example:

@code{.cpp}
// before v2.2.0, tf::Taskflow manages both graph and execution
tf::Taskflow taskflow(4);  // create a taskflow object with 4 threads
taskflow.emplace([] () { std::cout << "task A\n"; });
taskflow.wait_for_all();   // dispatch the present graph

tf::Framework framework;   // create a framework object
framework.emplace([] () { std::cout << "task B\n"; });
taskflow.run(framework);   // run the framework once
taskflow.wait_for_all();   // wait until the framework finishes
@endcode

However, this design is awkward in many aspects.
For instance, calling @c wait_for_all dispatches the present graph
and the graph vanishes when the execution completes.
To reuse a graph, users have to create another special graph called framework
and mix its execution with the one in a taskflow object.
Given the user feedback and lessons we have learned so far, 
we decided to isolate the executor interface out of tf::Taskflow and 
merge tf::Framework with tf::Taskflow.
All execution methods such as @c dispatch and @c wait_for_all 
have been moved from tf::Taskflow to tf::Executor.

@code{.cpp}
// starting from v2.2.0, tf::Executor manages the execution of graphs
tf::Taskflow taskflow;      // create a taskflow to build dependent tasks
tf::Task A = taskflow.emplace([] () { std::cout << "task A\n"; });
tf::Task B = taskflow.emplace([] () { std::cout << "task B\n"; });
A.precede(B);

tf::Executor executor(4);   // create an executor of 4 threads
executor.run(taskflow);     // run the taskflow once
executor.run(taskflow, 2);  // run the taskflow twice
executor.wait_for_all();    // wait for the three runs to finish
@endcode

The new design has a clean separation between
a task dependency graph builder tf::Taskflow and
the execution of graphs tf::Executor.
Users are fully responsible for the lifetime of a taskflow, 
and need to ensure a taskflow is alive during its execution.
Besides, all task constructs remain unchanged in tf::Taskflow.
In most situations, you will just need to add an executor to your program
to run your taskflow graphs.

Again, we apologize this breaking change! 
I hope you can understand what we did is to make %Taskflow provide good performance scaling
and user experience.

*/

}


