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It is very common for a parallel program to spawn task dependency graphs at runtime. In Taskflow, we call this subflow tasking.
Subflow tasks are those created during the execution of a graph. These tasks are spawned from a parent task and are grouped together to a subflow dependency graph. To create a subflow, emplace a callable that takes an argument of type tf::Subflow. A tf::Subflow object will be created and forwarded to the execution context of the task. All methods you find in tf::Taskflow are applicable for tf::Subflow.
1: tf::Taskflow taskflow; 2: tf::Executor executor; 3: 4: tf::Task A = taskflow.emplace([] () {}).name("A"); // static task A 5: tf::Task C = taskflow.emplace([] () {}).name("C"); // static task C 6: tf::Task D = taskflow.emplace([] () {}).name("D"); // static task D 7: 8: tf::Task B = taskflow.emplace([] (tf::Subflow& subflow) { 9: tf::Task B1 = subflow.emplace([] () {}).name("B1"); // subflow task B1 10: tf::Task B2 = subflow.emplace([] () {}).name("B2"); // subflow task B2 11: tf::Task B3 = subflow.emplace([] () {}).name("B3"); // subflow task B3 12: B1.precede(B3); // B1 runs bofore B3 13: B2.precede(B3); // B2 runs before B3 14: }).name("B"); 15: 16: A.precede(B); // B runs after A 17: A.precede(C); // C runs after A 18: B.precede(D); // D runs after B 19: C.precede(D); // D runs after C 20: 21: executor.run(taskflow).get(); // execute the graph to spawn the subflow 22: taskflow.dump(std::cout); // dump the taskflow to a DOT format
Debrief:
Lines 8-14 are the main block to enable subflow tasking at task B. The runtime will create a tf::Subflow passing it to task B, and spawn a dependency graph as described by the associated callable. This new subflow graph will be added to the topology of its parent task B. Due to the property of subflow tasking, we cannot dump its structure before execution. We will need to run the graph first to spawn the graph and then call tf::Taskflow::dump.
By default, a subflow joins its parent task when the program leaves its execution context. All nodes of zero outgoing edges in the subflow precede its parent task. You can explicitly join a subflow within its execution context to carry out recursive patterns. A famous implementation is fibonacci recursion.
int spawn(int n, tf::Subflow& sbf) { if (n < 2) return n; int res1, res2; sbf.emplace([&res1, n] (tf::Subflow& sbf) { res1 = spawn(n - 1, sbf); } ); sbf.emplace([&res2, n] (tf::Subflow& sbf) { res2 = spawn(n - 2, sbf); } ); sbf.join(); // join to materialize the subflow immediately return res1 + res2; } taskflow.emplace([&res] (tf::Subflow& sbf) { res = spawn(5, sbf); }); executor.run(taskflow).wait();
The code above computes the fifth fibonacci number using recursive subflow. Calling tf::Subflow::join immediately materializes the subflow by executing all associated tasks to recursively compute fibonacci numbers. The taskflow graph is shown below:
Our implementation to join subflows is recursive in order to preserve the thread context in each subflow task. Having a deep recursion of subflows may cause stack overflow.
In contract to joined subflow, you can detach a subflow from its parent task, allowing its execution to flow independently.
1: tf::Taskflow taskflow; 2: 3: tf::Task A = taskflow.emplace([] () {}).name("A"); // static task A 4: tf::Task C = taskflow.emplace([] () {}).name("C"); // static task C 5: tf::Task D = taskflow.emplace([] () {}).name("D"); // static task D 6: 7: tf::Task B = taskflow.emplace([] (tf::Subflow& subflow) { 8: tf::Task B1 = subflow.emplace([] () {}).name("B1"); // static task B1 9: tf::Task B2 = subflow.emplace([] () {}).name("B2"); // static task B2 10: tf::Task B3 = subflow.emplace([] () {}).name("B3"); // static task B3 11: B1.precede(B3); // B1 runs bofore B3 12: B2.precede(B3); // B2 runs before B3 13: subflow.detach(); // detach this subflow 14: }).name("B"); 15: 16: A.precede(B); // B runs after A 17: A.precede(C); // C runs after A 18: B.precede(D); // D runs after B 19: C.precede(D); // D runs after C 20: 21: tf::Executor executor; 22: executor.run(taskflow).wait(); // execute the graph to spawn the subflow 22: taskflow.dump(std::cout); // dump the taskflow to DOT format
The figure below demonstrates a detached subflow based on the previous example. A detached subflow will eventually join the topology of its parent task.
Detached subflow becomes an independent graph attached to the top-most taskflow. Running a taskflow multiple times will accumulate all detached tasks in the graph. For example, running the above taskflow 5 times results in a total of 19 tasks.
executor.run_n(taskflow, 5).wait(); assert(taskflow.num_tasks() == 19); taskflow.dump(std::cout);
The dumped graph is shown as follows:
A subflow can be nested or recursive. You can create another subflow from the execution of a subflow and so on.
1: tf::Taskflow taskflow; 2: 3: tf::Task A = taskflow.emplace([] (tf::Subflow& sbf){ 4: std::cout << "A spawns A1 & subflow A2\n"; 5: tf::Task A1 = sbf.emplace([] () { 6: std::cout << "subtask A1\n"; 7: }).name("A1"); 8: 9: tf::Task A2 = sbf.emplace([] (tf::Subflow& sbf2){ 10: std::cout << "A2 spawns A2_1 & A2_2\n"; 11: tf::Task A2_1 = sbf2.emplace([] () { 12: std::cout << "subtask A2_1\n"; 13: }).name("A2_1"); 14: tf::Task A2_2 = sbf2.emplace([] () { 15: std::cout << "subtask A2_2\n"; 16: }).name("A2_2"); 17: A2_1.precede(A2_2); 18: }).name("A2"); 19: A1.precede(A2); 20: }).name("A"); 21: 22: // execute the graph to spawn the subflow 23: tf::Executor().run(taskflow).get(); 24: taskflow.dump(std::cout);
Debrief:
Similarly, you can detach a nested subflow from its parent subflow. A detached subflow will run independently and eventually join the topology of its parent subflow.
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Taskflow handbook is part of the Taskflow project, copyright Dr. Tsung-Wei Huang, 2018–2023.
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