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<title>syclFlow Algorithms » Single Task | Taskflow QuickStart</title>

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<h1>

<a href="syclFlowAlgorithms.html">syclFlow Algorithms</a> »

Single Task

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<h3>Contents</h3>

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<li><a href="#SingleTaskSYCLSingleTask">Run a Task with a Single Thread</a></li>

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<a href="classtf_1_1syclFlow.html" class="m-doc">tf::syclFlow</a> provides a template method, <a href="classtf_1_1syclFlow.html#a05ff6f331b6cf48e21ae7f0d6aea9094" class="m-doc">tf::syclFlow::single_task</a>, for creating a task to run the given callable using a single kernel thread.<section id="SingleTaskSYCLSingleTask"><h2><a href="#SingleTaskSYCLSingleTask">Run a Task with a Single Thread</a></h2>You can create a task to run a kernel function just once, i.e., using one GPU thread. This is handy when you want to set up a single or a few global variables that do not need multiple threads and will be used by multiple kernels afterwards. The following example creates a single-task kernel that sets <code>gpu_variable</code> to 1.<pre class="m-code">sycl::queue queue;

int* gpu_variable = sycl::malloc_shared<int>(1, queue);

tf::Task = taskflow.emplace_on([&] (tf::syclFlow& sf) {

// create a single task to set the gpu_variable to 1

tf::syclTask set_var = sf.single_task(

[gpu_variable] () { *gpu_variable = 1; }

);

// create one kernel task that needs access to gpu_variable

tf::syclTask kernel1 = sf.parallel_for(

sycl::range<1>(N), [=] (sycl::id<1> id) { data1[id] *= gpu_variable; }

);

set_par.precede(kernel1);

}, queue);</pre></section>

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