Create an Index-based Parallel-Iteration Task

Index-based parallel-for performs parallel iterations over a range [first, last) with the given step size. The task created by tf::Taskflow::for_each_index(B first, E last, S step, C callable) represents parallel execution of the following loop:

// positive step
for(auto i=first; i<last; i+=step) {
  callable(i);
}
 
// negative step
for(auto i=first; i>last; i+=step) {
  callable(i);
}

We support only integer-based range. The range can go positive or negative direction.

taskflow.for_each_index(0, 100, 2, [](int i) { }); // 50 loops with a + step

taskflow.for_each_index(100, 0, -2, [](int i) { }); // 50 loops with a - step

Notice that either positive or negative direction is defined in terms of the range, [first, last), where end is excluded. In the positive case, the 50 items are 0, 2, 4, 6, 8, ..., 96, 98. In the negative case, the 50 items are 100, 98, 96, 04, ... 4, 2. An example of the Taskflow graph for the positive case under 12 workers is depicted below:

The index types, B, E, and S, are templates to preserve the variable types and their underlying types must be of the same integral type (e.g., int, size_t, unsigned). By default, tf::Taskflow::for_each_index creates a task that spawns a subflow (see Dynamic Tasking) to run iterations in parallel. The subflow closure captures all input arguments through perfect forwarding to form a stateful closure such that any changes on the arguments will be visible to the execution context of the subflow. For example:

int* vec;
int first, last;
 
auto init = taskflow.emplace([&](){
  first = 0;
  last  = 1000;
  vec = new int[1000];  
});
 
auto pf = taskflow.for_each_index(std::ref(first), std::ref(last), 1, 
  [&] (int i) {
    std::cout << "parallel iteration on index " << vec[i] << '\n';
  }
);
 
// wrong! must use std::ref, or first and last are captured by copy
// auto pf = taskflow.for_each_index(first, last, 1, [&](int i) {
//   std::cout << "parallel iteration on index " << vec[i] << '\n';
// });
 
init.precede(pf);

When init finishes, the parallel-for task pf will see first as 0 and last as 1000 and performs parallel iterations over the 1000 items. This property is especially important for task graph parallelism, because users can define end-to-end parallelism through stateful closures that marshal parameter exchange between dependent tasks.

Create an Iterator-based Parallel-Iteration Task

Iterator-based parallel-for performs parallel iterations over a range specified by two STL-styled iterators, first and last. The task created by tf::Taskflow::for_each(B first, E last, C callable) represents a parallel execution of the following loop:

for(auto i=first; i<last; i++) {
  callable(*i);
}

By default, tf::Taskflow::for_each(B first, E last, C callable) creates a task that spawns a subflow (see Dynamic Tasking) that applies the callable to the object obtained by dereferencing every iterator in the range [first, last). It is user's responsibility for ensuring the range is valid within the execution of the parallel-for task. Iterators must have the post-increment operator ++ defined. This version of parallel-for applies to all iterable STL containers.

std::vector<int> vec = {1, 2, 3, 4, 5};
taskflow.for_each(vec.begin(), vec.end(), [](int i){ 
  std::cout << "parallel for on item " << i << '\n';  
});
 
std::list<std::string> list = {"hi", "from", "t", "a", "s", "k", "f", "low"};
taskflow.for_each(list.begin(), list.end(), [](const std::string& str){ 
  std::cout << "parallel for on item " << str << '\n';  
});

Similar to index-based parallel-for, the iterator types are templates to enable users to leverage the property of stateful closure. For example:

std::vector<int> vec;
std::vector<int>::iterator first, last;;
 
tf::Task init = taskflow.emplace([&](){
  vec.resize(1000);
  first = vec.begin();
  last  = vec.end();
});
 
tf::Task pf = taskflow.for_each(std::ref(first), std::ref(last), [&](int i) {
  std::cout << "parallel iteration on item " << i << '\n';
});
 
// wrong! must use std::ref, or first and last are captured by copy
// tf::Task pf = taskflow.for_each(first, last, [&](int i) {
//   std::cout << "parallel iteration on item " << i << '\n';
// });
 
init.precede(pf);

When init finishes, the parallel-for task pf will see first pointing to the beginning of vec and last pointing to the end of vec and performs parallel iterations over the 1000 items. The two tasks form an end-to-end task graph where the parameters of parallel-for are computed on the fly.

Table of Contents

Create an Index-based Parallel-Iteration Task

Create an Iterator-based Parallel-Iteration Task