Migrating from low-level task API

Intel® oneAPI Threading Building Blocks Developer Guide and API Reference

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ID 772616

Date 6/24/2024

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Migrating from low-level task API

The low-level task API of Intel(R) Threading Building Blocks (TBB) was considered complex and hence error-prone, which was the primary reason it had been removed from oneAPI Threading Building Blocks (oneTBB). This guide helps with the migration from TBB to oneTBB for the use cases where low-level task API is used.

Spawning of individual tasks

For most use cases, the spawning of individual tasks can be replaced with the use of either oneapi::tbb::task_group or oneapi::tbb::parallel_invoke.

For example, RootTask, ChildTask1, and ChildTask2 are the user-side functors that inherit tbb::task and implement its interface. Then spawning of ChildTask1 and ChildTask2 tasks that can execute in parallel with each other and waiting on the RootTask is implemented as:

#include <tbb/task.h>

int main() {
    // Assuming RootTask, ChildTask1, and ChildTask2 are defined.
    RootTask& root = *new(tbb::task::allocate_root()) RootTask{};

    ChildTask1& child1 = *new(root.allocate_child()) ChildTask1{/*params*/};
    ChildTask2& child2 = *new(root.allocate_child()) ChildTask2{/*params*/};

    root.set_ref_count(3);

    tbb::task::spawn(child1);
    tbb::task::spawn(child2);

    root.wait_for_all();
}

Using oneapi::tbb::task_group

The code above can be rewritten using oneapi::tbb::task_group:

#include <oneapi/tbb/task_group.h>

int main() {
    // Assuming ChildTask1, and ChildTask2 are defined.
    oneapi::tbb::task_group tg;
    tg.run(ChildTask1{/*params*/});
    tg.run(ChildTask2{/*params*/});
    tg.wait();
}

The code looks more concise now. It also enables lambda functions and does not require you to implement tbb::task interface that overrides the tbb::task* tbb::task::execute() virtual method. With this new approach, you work with functors in a C++-standard way by implementing void operator() const:

struct Functor {
    // Member to be called when object of this type are passed into
    // oneapi::tbb::task_group::run() method
    void operator()() const {}
};

Using oneapi::tbb::parallel_invoke

It is also possible to use oneapi::tbb::parallel_invoke to rewrite the original code and make it even more concise:

#include <oneapi/tbb/parallel_invoke.h>

int main() {
    // Assuming ChildTask1, and ChildTask2 are defined.
    oneapi::tbb::parallel_invoke(
        ChildTask1{/*params*/},
        ChildTask2{/*params*/}
    );
}

Adding more work during task execution

oneapi::tbb::parallel_invoke follows a blocking style of programming, which means that it completes only when all functors passed to the parallel pattern complete their execution.

In TBB, cases when the amount of work is not known in advance and the work needs to be added during the execution of a parallel algorithm were mostly covered by tbb::parallel_do high-level parallel pattern. The tbb::parallel_do algorithm logic may be implemented using the task API as:

#include <cstddef>
#include <vector>
#include <tbb/task.h>

// Assuming RootTask and OtherWork are defined and implement tbb::task interface.

struct Task : public tbb::task {
    Task(tbb::task& root, int i)
        : m_root(root), m_i(i)
    {}

    tbb::task* execute() override {
        // ... do some work for item m_i ...

        if (add_more_parallel_work) {
            tbb::task& child = *new(m_root.allocate_child()) OtherWork;
            tbb::task::spawn(child);
        }
        return nullptr;
    }

    tbb::task& m_root;
    int m_i;
};

int main() {
    std::vector<int> items = { 0, 1, 2, 3, 4, 5, 6, 7 };
    RootTask& root = *new(tbb::task::allocate_root()) RootTask{/*params*/};

    root.set_ref_count(items.size() + 1);

    for (std::size_t i = 0; i < items.size(); ++i) {
        Task& task = *new(root.allocate_child()) Task(root, items[i]);
        tbb::task::spawn(task);
    }

    root.wait_for_all();
    return 0;
}

In oneTBB tbb::parallel_do interface was removed. Instead, the functionality of adding new work was included into the oneapi::tbb::parallel_for_each interface.

The previous use case can be rewritten in oneTBB as follows:

#include <vector>
#include <oneapi/tbb/parallel_for_each.h>

int main() {
    std::vector<int> items = { 0, 1, 2, 3, 4, 5, 6, 7 };

    oneapi::tbb::parallel_for_each(
        items.begin(), items.end(),
        [](int& i, tbb::feeder<int>& feeder) {

            // ... do some work for item i ...

            if (add_more_parallel_work)
                feeder.add(i);
        }
    );
}

Since both TBB and oneTBB support nested expressions, you can run additional functors from within an already running functor.

The previous use case can be rewritten using oneapi::tbb::task_group as:

#include <cstddef>
#include <vector>
#include <oneapi/tbb/task_group.h>

int main() {
    std::vector<int> items = { 0, 1, 2, 3, 4, 5, 6, 7 };

    oneapi::tbb::task_group tg;
    for (std::size_t i = 0; i < items.size(); ++i) {
        tg.run([&i = items[i], &tg] {

            // ... do some work for item i ...

            if (add_more_parallel_work)
                // Assuming OtherWork is defined.
                tg.run(OtherWork{});

        });
    }
    tg.wait();
}

Task recycling

You can re-run the functor by passing *this to the oneapi::tbb::task_group::run() method. The functor will be copied in this case. However, its state can be shared among instances:

#include <memory>
#include <oneapi/tbb/task_group.h>

struct SharedStateFunctor {
    std::shared_ptr<Data> m_shared_data;
    oneapi::tbb::task_group& m_task_group;

    void operator()() const {
        // do some work processing m_shared_data

        if (has_more_work)
            m_task_group.run(*this);

        // Note that this might be concurrently accessing m_shared_data already
    }
};

int main() {
    // Assuming Data is defined.
    std::shared_ptr<Data> data = std::make_shared<Data>(/*params*/);
    oneapi::tbb::task_group tg;
    tg.run(SharedStateFunctor{data, tg});
    tg.wait();
}

Such patterns are particularly useful when the work within a functor is not completed but there is a need for the task scheduler to react to outer circumstances, such as cancellation of group execution. To avoid issues with concurrent access, it is recommended to submit it for re-execution as the last step:

#include <memory>
#include <oneapi/tbb/task_group.h>

struct SharedStateFunctor {
    std::shared_ptr<Data> m_shared_data;
    oneapi::tbb::task_group& m_task_group;

    void operator()() const {
        // do some work processing m_shared_data

        if (need_to_yield) {
            m_task_group.run(*this);
            return;
        }
    }
};

int main() {
    // Assuming Data is defined.
    std::shared_ptr<Data> data = std::make_shared<Data>(/*params*/);
    oneapi::tbb::task_group tg;
    tg.run(SharedStateFunctor{data, tg});
    tg.wait();
}

Recycling as child or continuation

In oneTBB this kind of recycling is done manually. You have to track when it is time to run the task:

#include <cstddef>
#include <vector>
#include <atomic>
#include <cassert>
#include <oneapi/tbb/task_group.h>

struct ContinuationTask {
    ContinuationTask(std::vector<int>& data, int& result)
        : m_data(data), m_result(result)
    {}

    void operator()() const {
        for (const auto& item : m_data)
            m_result += item;
    }

    std::vector<int>& m_data;
    int& m_result;
};

struct ChildTask {
    ChildTask(std::vector<int>& data, int& result,
              std::atomic<std::size_t>& tasks_left, std::atomic<std::size_t>& tasks_done,
              oneapi::tbb::task_group& tg)
        : m_data(data), m_result(result), m_tasks_left(tasks_left), m_tasks_done(tasks_done), m_tg(tg)
    {}

    void operator()() const {
        std::size_t index = --m_tasks_left;
        m_data[index] = produce_item_for(index);
        std::size_t done_num = ++m_tasks_done;
        if (index % 2 != 0) {
            // Recycling as child
            m_tg.run(*this);
            return;
        } else if (done_num == m_data.size()) {
            assert(m_tasks_left == 0);
            // Spawning a continuation that does reduction
            m_tg.run(ContinuationTask(m_data, m_result));
        }
    }
    std::vector<int>& m_data;
    int& m_result;
    std::atomic<std::size_t>& m_tasks_left;
    std::atomic<std::size_t>& m_tasks_done;
    oneapi::tbb::task_group& m_tg;
};


int main() {
    int result = 0;
    std::vector<int> items(10, 0);
    std::atomic<std::size_t> tasks_left{items.size()};
    std::atomic<std::size_t> tasks_done{0};

    oneapi::tbb::task_group tg;
    for (std::size_t i = 0; i < items.size(); i+=2) {
        tg.run(ChildTask(items, result, tasks_left, tasks_done, tg));
    }
    tg.wait();
}

Scheduler Bypass

TBB task::execute() method can return a pointer to a task that can be executed next by the current thread. This might reduce scheduling overheads compared to direct spawn. Similar to spawn, the returned task is not guaranteed to be executed next by the current thread.

#include <tbb/task.h>

// Assuming OtherTask is defined.

struct Task : tbb::task {
    task* execute(){
        // some work to do ...

        auto* other_p = new(this->parent().allocate_child()) OtherTask{};
        this->parent().add_ref_count();

        return other_p;
    }
};

int main(){
    // Assuming RootTask is  defined.
    RootTask& root = *new(tbb::task::allocate_root()) RootTask{};

    Task& child = *new(root.allocate_child()) Task{/*params*/};

    root.add_ref_count();

    tbb::task_spawn(child);

    root.wait_for_all();
}

In oneTBB, this can be done using oneapi::tbb::task_group.

#include <oneapi/tbb/task_group.h>

// Assuming OtherTask is defined.

int main(){
    oneapi::tbb::task_group tg;

    tg.run([&tg](){
        //some work to do ...

        return tg.defer(OtherTask{});
    });

    tg.wait();
}

Here oneapi::tbb::task_group::defer adds a new task into the tg. However, the task is not put into a queue of tasks ready for execution via oneapi::tbb::task_group::run, but bypassed to the executing thread directly via function return value.

Deferred task creation

The TBB low-level task API separates the task creation from the actual spawning. This separation allows to postpone the task spawning, while the parent task and final result production are blocked from premature leave. For example, RootTask, ChildTask, and CallBackTask are the user-side functors that inherit tbb::task and implement its interface. Then, blocking the RootTask from leaving prematurely and waiting on it is implemented as follows:

#include <tbb/task.h>

int main() {
    // Assuming RootTask, ChildTask, and CallBackTask are defined.
    RootTask& root = *new(tbb::task::allocate_root()) RootTask{};

    ChildTask&    child    = *new(root.allocate_child()) ChildTask{/*params*/};
    CallBackTask& cb_task  = *new(root.allocate_child()) CallBackTask{/*params*/};

    root.set_ref_count(3);

    tbb::task::spawn(child);

    register_callback([cb_task&](){
        tbb::task::enqueue(cb_task);
    });

    root.wait_for_all();
    // Control flow will reach here only after both ChildTask and CallBackTask are executed,
    // i.e. after the callback is called
}

In oneTBB, this can be done using oneapi::tbb::task_group.

#include <oneapi/tbb/task_group.h>

int main(){
    oneapi::tbb::task_group tg;
    oneapi::tbb::task_arena arena;
    // Assuming ChildTask and CallBackTask are defined.

    auto cb = tg.defer(CallBackTask{/*params*/});

    register_callback([&tg, c = std::move(cb), &arena]{
        arena.enqueue(c);
    });

    tg.run(ChildTask{/*params*/});


    tg.wait();
    // Control flow gets here once both ChildTask and CallBackTask are executed
    // i.e. after the callback is called
}

Here oneapi::tbb::task_group::defer adds a new task into the tg. However, the task is not spawned until oneapi::tbb::task_arena::enqueue is called.

NOTE:

The call to oneapi::tbb::task_group::wait will not return control until both ChildTask and CallBackTask are executed.

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Intel® oneAPI Threading Building Blocks Developer Guide and API Reference

Migrating from low-level task API

Spawning of individual tasks

Adding more work during task execution

Task recycling

Scheduler Bypass

Deferred task creation