taskflow/docs/ConditionalTasking.html at fix_multidll_memory_leak · ModuleWorks/taskflow

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<!DOCTYPE html>

<head>

<title>Cookbook » Conditional Tasking | Taskflow QuickStart</title>

</head>

<body>

<a href="https://taskflow.github.io"><img src="taskflow_logo.png" alt="" />Taskflow</a> | <a href="index.html" class="m-thin">QuickStart</a>

</svg></a>

</div>

<li><a href="pages.html">Handbook</a></li>

<li><a href="namespaces.html">Namespaces</a></li>

</ol>

<li><a href="annotated.html">Classes</a></li>

<li><a href="files.html">Files</a></li>

</svg></a></li>

</ol>

</div>

</nav></header>

<h1>

<a href="Cookbook.html">Cookbook</a> »

Conditional Tasking

</h1>

<h3>Contents</h3>

<ul>

<li><a href="#CreateAConditionTask">Create a Condition Task</a></li>

<li>

<a href="#TaskSchedulingPolicy">Understand our Task-level Scheduling</a>

<ul>

<li><a href="#TaskLevelSchedulingExample">Example</a></li>

</ul>

</li>

<li><a href="#AvoidCommonPitfalls">Avoid Common Pitfalls</a></li>

<li>

<a href="#ImplementControlFlowGraphs">Implement Control-flow Graphs</a>

<ul>

<li><a href="#ImplementIfElseControlFlow">Implement If-Else Control Flow</a></li>

<li><a href="#ImplementSwitchControlFlow">Implement Switch Control Flow</a></li>

<li><a href="#ImplementDoWhileLoopControlFlow">Implement Do-While-Loop Control Flow</a></li>

<li><a href="#ImplementWhileLoopControlFlow">Implement While-Loop Control Flow</a></li>

</ul>

</li>

<li><a href="#CreateAMultiConditionTask">Create a Multi-condition Task</a></li>

</ul>

</nav>

One of the most powerful features that distinguishes Taskflow from other systems is its support for conditional tasking, also known as the control taskflow programming model (CTFG). CTFG allows you to embed control flow directly within a taskflow graph, enabling tasks to make decisions dynamically during execution. This mechanism supports advanced in-graph control flow patterns, such as dynamic branching, loops, and conditionals—that are typically difficult or impossible to express in traditional task graph models.<section id="CreateAConditionTask"><h2><a href="#CreateAConditionTask">Create a Condition Task</a></h2>A condition task returns an integer index indicating which successor task to execute next. The index corresponds to the position of the successor in the order it was added during task construction. The following example creates an if-else block using a condition task.<pre class="m-code"> 1: tf::Taskflow taskflow;

2:

3: auto [init, cond, yes, no] = taskflow.emplace(

4: [] () { },

5: [] () { return 0; },

6: [] () { std::cout << "yes\n"; },

7: [] () { std::cout << "no\n"; }

8: );

9:

10: cond.succeed(init)

11: .precede(yes, no); // executes yes if cond returns 0

12: // executes no if cond returns 1</pre><div class="m-graph"><svg style="width: 25.600rem; height: 9.800rem;" viewBox="0.00 0.00 256.17 98.00">

<title>Taskflow</title>

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</div>Line 5 creates a condition task <code>cond</code> and line 11 creates two dependencies from <code>cond</code> to two other tasks, <code>yes</code> and <code>no</code>. With this order, when <code>cond</code> returns 0, the execution moves on to task <code>yes</code>. When <code>cond</code> returns 1, the execution moves on to task <code>no</code>.<aside class="m-note m-warning"><h4>Attention</h4>It is your responsibility to ensure that the return value of a condition task corresponds to a valid successor. If the returned index is out of range, the executor will not schedule any successor tasks.</aside>A condition task can form a cycle to express iterative control flow. The example below demonstrates a simple yet commonly used feedback loop implemented using a condition task (lines 7–10) that returns a random binary value. If the return value from <code>cond</code> is <code>0</code>, the task loops back to itself; otherwise, it proceeds to <code>stop</code>.<pre class="m-code"> 1: tf::Taskflow taskflow;

2:

3: tf::Task init = taskflow.emplace([](){}).name("init");

4: tf::Task stop = taskflow.emplace([](){}).name("stop");

5:

6: // creates a condition task that returns 0 or 1

7: tf::Task cond = taskflow.emplace([](){

8: std::cout << "flipping a coin\n";

9: return std::rand() % 2;

10: }).name("cond");

11:

12: // creates a feedback loop {0: cond, 1: stop}

13: init.precede(cond);

14: cond.precede(cond, stop); // returns 0 to 'cond' or 1 to 'stop'

15:

16: executor.run(taskflow).wait();</pre><div class="m-graph"><svg style="width: 25.600rem; height: 7.300rem;" viewBox="0.00 0.00 256.17 73.25">

<title>Taskflow</title>

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</div>Creating a taskflow with complex control flow often requires only a few lines of code to implement. Different control flow paths can execute in parallel, making it easy to express both logic and concurrency. The code below creates a taskflow with three condition tasks to demonstrate this capability:<pre class="m-code">tf::Taskflow taskflow;

tf::Task A = taskflow.emplace([](){}).name("A");

tf::Task B = taskflow.emplace([](){}).name("B");

tf::Task C = taskflow.emplace([](){}).name("C");

tf::Task D = taskflow.emplace([](){}).name("D");

tf::Task E = taskflow.emplace([](){}).name("E");

tf::Task F = taskflow.emplace([](){}).name("F");

tf::Task G = taskflow.emplace([](){}).name("G");

tf::Task H = taskflow.emplace([](){}).name("H");

tf::Task I = taskflow.emplace([](){}).name("I");

tf::Task K = taskflow.emplace([](){}).name("K");

tf::Task L = taskflow.emplace([](){}).name("L");

tf::Task M = taskflow.emplace([](){}).name("M");

tf::Task cond_1 = taskflow.emplace([](){ return std::rand()%2; }).name("cond_1");

tf::Task cond_2 = taskflow.emplace([](){ return std::rand()%2; }).name("cond_2");

tf::Task cond_3 = taskflow.emplace([](){ return std::rand()%2; }).name("cond_3");

A.precede(B, F);

B.precede(C);

C.precede(D);

D.precede(cond_1);

E.precede(K);

F.precede(cond_2);

H.precede(I);

I.precede(cond_3);

L.precede(M);

cond_1.precede(B, E); // return 0 to 'B' or 1 to 'E'

cond_2.precede(G, H); // return 0 to 'G' or 1 to 'H'

cond_3.precede(cond_3, L); // return 0 to 'cond_3' or 1 to 'L'

taskflow.dump(std::cout);</pre>The above code creates three condition tasks to implement three different control-flow tasks:<ol><li>A condition task <code>cond_1</code> that loops back to <code>B</code> on returning <code>0</code>, or proceeds to <code>E</code> on returning <code>1</code>,</li><li>A condition task <code>cond_2</code> that goes to <code>G</code> on returning <code>0</code>, or <code>H</code> on returning <code>1</code>,</li><li>A condition task <code>cond_3</code> that loops back to itself on returning <code>0</code>, or proceeds to <code>L</code> on returning <code>1</code></li></ol><div class="m-graph"><svg style="width: 78.800rem; height: 19.200rem;" viewBox="0.00 0.00 788.23 192.00">

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</div>In this particular example, we can clearly see the advantage of CTFG: the execution of <code>cond_1</code> can overlap with <code>cond_2</code> or <code>cond_3</code>, enabling greater concurrency in control-driven workloads. Unlike traditional task graph models that require static structure or external orchestration to handle control flow, CTFG allows tasks to make decisions dynamically and continue execution without global synchronization barriers. This design leads to better parallelism, reduced overhead, and more expressive task graphs, especially in workloads with branching or iterative control flows.</section><section id="TaskSchedulingPolicy"><h2><a href="#TaskSchedulingPolicy">Understand our Task-level Scheduling</a></h2>In order to understand how an executor schedules condition tasks, we define two dependency types, strong dependency and weak dependency. A strong dependency is a preceding link from one non-condition task to another task. A weak dependency is a preceding link from one condition task to another task. The number of dependencies of a task is the sum of its strong dependencies and weak dependencies. The table below lists the number of strong dependencies and weak dependencies of each task in the previous example:<table class="m-table"><thead><tr><th>task</th><th>strong dependency</th><th>weak dependency</th><th>dependencies</th></tr></thead><tbody><tr><td>A</td><td>0</td><td>0</td><td>0</td></tr><tr><td>B</td><td>1</td><td>1</td><td>2</td></tr><tr><td>C</td><td>1</td><td>0</td><td>1</td></tr><tr><td>D</td><td>1</td><td>0</td><td>1</td></tr><tr><td>E</td><td>0</td><td>1</td><td>1</td></tr><tr><td>F</td><td>1</td><td>0</td><td>1</td></tr><tr><td>G</td><td>0</td><td>1</td><td>1</td></tr><tr><td>H</td><td>0</td><td>1</td><td>1</td></tr><tr><td>I</td><td>1</td><td>0</td><td>1</td></tr><tr><td>K</td><td>1</td><td>0</td><td>1</td></tr><tr><td>L</td><td>0</td><td>1</td><td>1</td></tr><tr><td>M</td><td>1</td><td>0</td><td>1</td></tr><tr><td>cond_1</td><td>1</td><td>0</td><td>1</td></tr><tr><td>cond_2</td><td>1</td><td>0</td><td>1</td></tr><tr><td>cond_3</td><td>1</td><td>1</td><td>2</td></tr></tbody></table>You can query the number of strong dependencies, the number of weak dependencies, and the number of dependencies of a task.<pre class="m-code">1: tf::Taskflow taskflow;

2:

3: tf::Task task = taskflow.emplace([](){});

4:

5: // ... add more tasks and preceding links

6:

7: std::cout << task.num_predecessors() << '\n';

8: std::cout << task.num_strong_dependencies() << '\n';

9: std::cout << task.num_weak_dependencies() << '\n';</pre>When you submit a task to an executor, the scheduler starts with tasks of zero dependencies (both zero strong and weak dependencies) and continues to execute successive tasks whenever their strong dependencies are met. However, the scheduler skips this rule when executing a condition task and jumps directly to its successors indexed by the return value.<div class="m-graph"><svg style="width: 58.600rem; height: 34.600rem;" viewBox="0.00 0.00 585.89 346.25">

<title>atask</title>

<text text-anchor="middle" x="483.89" y="-316.38" font-family="Helvetica,sans-Serif" font-size="10.00">pop a task T from the queue</text>

</g>

<text text-anchor="middle" x="363.89" y="-243.38" font-family="Helvetica,sans-Serif" font-size="10.00">is T a condition task?</text>

</g>

<title>atask->cond</title>

</g>

<title>invokeN</title>

<text text-anchor="middle" x="271.89" y="-160.12" font-family="Helvetica,sans-Serif" font-size="10.00">invoke(T)</text>

</g>

<title>cond->invokeN</title>

</g>

<title>invokeY</title>

<text text-anchor="middle" x="396.89" y="-160.12" font-family="Helvetica,sans-Serif" font-size="10.00">R = invoke(T)</text>

</g>

<title>cond->invokeY</title>

</g>

<title>decrement</title>

<text text-anchor="middle" x="171.89" y="-87.12" font-family="Helvetica,sans-Serif" font-size="10.00">decrement strong dependencies of each successor of T by one</text>

</g>

<title>invokeN->decrement</title>

</g>

<title>enqueueR</title>

<text text-anchor="middle" x="455.89" y="-87.12" font-family="Helvetica,sans-Serif" font-size="10.00">enqueue the R-th successor of T</text>

</g>

<title>invokeY->enqueueR</title>

</g>

<title>enqueueR->atask</title>

</g>

<title>enqueueS</title>

<text text-anchor="middle" x="374.89" y="-14.12" font-family="Helvetica,sans-Serif" font-size="10.00">enqueue successors of zero strong dependencies</text>

</g>

<title>decrement->enqueueS</title>

</g>

<title>enqueueS->atask</title>

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</div>Each task has an atomic join counter to keep track of strong dependencies that are met at runtime. When a task completes, the join counter is restored to the task's strong dependency number in the graph, such that the subsequent execution can reuse the counter again.<section id="TaskLevelSchedulingExample"><h3><a href="#TaskLevelSchedulingExample">Example</a></h3>Let's take a look at an example to understand how task-level scheduling works. Suppose we have the following taskflow of one condition task <code>cond</code> that forms a loop to itself on returning <code>0</code> and moves on to <code>stop</code> on returning <code>1</code>:<div class="m-graph"><svg style="width: 25.600rem; height: 7.300rem;" viewBox="0.00 0.00 256.17 73.25">

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</div>The scheduler starts with <code>init</code> task because it has no dependencies (both strong and weak dependencies). Then, the scheduler moves on to the condition task <code>cond</code>. If <code>cond</code> returns <code>0</code>, the scheduler enqueues <code>cond</code> and runs it again. If <code>cond</code> returns <code>1</code>, the scheduler enqueues <code>stop</code> and then moves on.</section></section><section id="AvoidCommonPitfalls"><h2><a href="#AvoidCommonPitfalls">Avoid Common Pitfalls</a></h2>Condition tasks are handy in creating dynamic and cyclic control flows, but they are also easy to make mistakes. It is your responsibility to ensure a taskflow is properly conditioned. Top things to avoid include no source tasks to start with and task race. The figure below shows common pitfalls and their remedies.<div class="m-graph"><svg style="width: 91.000rem; height: 26.200rem;" viewBox="0.00 0.00 910.00 261.75">

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<text text-anchor="middle" x="787" y="-232.25" font-family="Helvetica,sans-Serif" font-size="10.00">risky: X might be raced</text>

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</div>In the <code>error1</code> scenario, there is no source task for the scheduler to start with, and the simplest fix is to add a task <code>S</code> that has no dependencies. In the <code>error2</code> scenario, <code>D</code> might be scheduled twice by <code>E</code> through the strong dependency and <code>C</code> through the weak dependency (on returning <code>1</code>). To fix this problem, you can add an auxiliary task <code>D-aux</code> to break the mixed use of strong dependency and weak dependency. In the risky scenario, task <code>X</code> may be raced by <code>M</code> and <code>P</code> if <code>M</code> returns <code>0</code> and P returns <code>1</code>.<aside class="m-note m-warning"><h4>Attention</h4>It is your responsibility to ensure a written taskflow graph is properly conditioned. We suggest that you <a href="#TaskSchedulingPolicy" class="m-doc">Understand our Task-level Scheduling</a> and infer if task race exists in the execution of your graph.</aside></section><section id="ImplementControlFlowGraphs"><h2><a href="#ImplementControlFlowGraphs">Implement Control-flow Graphs</a></h2><section id="ImplementIfElseControlFlow"><h3><a href="#ImplementIfElseControlFlow">Implement If-Else Control Flow</a></h3>You can use conditional tasking to implement if-else control flow. The following example creates a nested if-else control flow diagram that executes three condition tasks to check the range of <code>i</code>.<pre class="m-code">tf::Taskflow taskflow;

int i;

// create three condition tasks for nested control flow

auto initi = taskflow.emplace([&](){ i=3; });

auto cond1 = taskflow.emplace([&](){ return i>1 ? 1 : 0; });

auto cond2 = taskflow.emplace([&](){ return i>2 ? 1 : 0; });

auto cond3 = taskflow.emplace([&](){ return i>3 ? 1 : 0; });

auto equl1 = taskflow.emplace([&](){ std::cout << "i=1\n"; });

auto equl2 = taskflow.emplace([&](){ std::cout << "i=2\n"; });

auto equl3 = taskflow.emplace([&](){ std::cout << "i=3\n"; });

auto grtr3 = taskflow.emplace([&](){ std::cout << "i>3\n"; });

initi.precede(cond1);

cond1.precede(equl1, cond2); // goes to cond2 if i>1

cond2.precede(equl2, cond3); // goes to cond3 if i>2

cond3.precede(equl3, grtr3); // goes to grtr3 if i>3</pre><div class="m-graph"><svg style="width: 75.600rem; height: 15.200rem;" viewBox="0.00 0.00 756.23 152.00">

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</div></section><section id="ImplementSwitchControlFlow"><h3><a href="#ImplementSwitchControlFlow">Implement Switch Control Flow</a></h3>You can use condition tasks to implement switch-style control flow. The following example demonstrates this by creating a switch structure that randomly selects and executes one of three cases using four condition tasks.<pre class="m-code">tf::Taskflow taskflow;

auto [source, swcond, case1, case2, case3, target] = taskflow.emplace(

[](){ std::cout << "switch\n"; return rand()%3; },

[](){ std::cout << "case 1\n"; return 0; },

[](){ std::cout << "case 2\n"; return 0; },

[](){ std::cout << "case 3\n"; return 0; },

);

source.precede(swcond);

swcond.precede(case1, case2, case3);

target.succeed(case1, case2, case3);</pre><div class="m-graph"><svg style="width: 38.600rem; height: 15.200rem;" viewBox="0.00 0.00 385.70 152.00">

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</div>Assuming <code>swcond</code> returns 1, the program outputs:<pre class="m-code">source

switch

case 2

target</pre>Keep in mind, both switch and case tasks must be described as condition tasks. The following implementation is a common mistake in which case tasks are not described as condition tasks.<pre class="m-code">// wrong implementation of switch control flow using only one condition task

tf::Taskflow taskflow;

[](){ std::cout << "target\n"; } // target has three strong dependencies

);

source.precede(swcond);

target.succeed(case1, case2, case3);</pre><div class="m-graph"><svg style="width: 36.000rem; height: 15.200rem;" viewBox="0.00 0.00 359.72 152.00">

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