Release Notes » Release 3.10.0 (Master)

Taskflow Core

• improved work-stealing loop with an adaptive breaking strategy
• improved shut-down signal detection using decentralized variables
• added debug mode for the windows CI to GitHub actions
• added index range-based parallel-for algorithm (#551)

// initialize data1 and data2 to 10 using two different approaches
std::vector<int> data1(100), data2(100);

// Approach 1: initialize data1 using explicit index range
taskflow.for_each_index(0, 100, 1, [&](int i){ data1[i] = 10; });

// Approach 2: initialize data2 using tf::IndexRange
tf::IndexRange<int> range(0, 100, 1);
taskflow.for_each_by_index(range, [&](tf::IndexRange<int>& subrange){
  for(int i=subrange.begin(); i<subrange.end(); i+=subrange.step_size()) {
    data2[i] = 10;
  }
});

• added index range-based parallel-reduction algorithm (i#654)

std::vector<double> data(100000);
double res = 1.0;
taskflow.reduce_by_index(
  // index range
  tf::IndexRange<size_t>(0, N, 1),
  // final result
  res,
  // local reducer
  [&](tf::IndexRange<size_t> subrange, std::optional<double> running_total) { 
    double residual = running_total ? *running_total : 0.0;
    for(size_t i=subrange.begin(); i<subrange.end(); i+=subrange.step_size()) {
      data[i] = 1.0;
      residual += data[i];
    }
    printf("partial sum = %lf\n", residual);
    return residual;
  },
  // global reducer
  std::plus<double>()
);

• added static keyword to the executor creation in taskflow benchmarks

Utilities

• added tf::IndexRange for index range-based parallel-for algorithm
• added tf::distance to calculate the number of iterations in an index range
• added tf::is_index_range_invalid to check if the given index range is valid