C++ Execution Policy Number Of Threads

6 min read Jul 03, 2024

C++ Execution Policy: Understanding Threads and Parallelism

C++ offers a powerful mechanism for utilizing multi-core processors and maximizing computational resources: execution policies. These policies guide the execution of algorithms, allowing you to control whether they run sequentially, in parallel, or with a specific number of threads.

Execution Policies in C++

C++ execution policies are primarily associated with the <execution> header. These policies specify how algorithms, such as std::for_each, std::transform, and std::accumulate, should execute.

Here are some common execution policies:

1. std::execution::seq: Sequential Execution

This policy ensures that the algorithm runs on a single thread, in a purely sequential manner. This is useful when:

Data Dependencies: The algorithm has data dependencies that make parallelization impossible or inefficient.
Overhead: The overhead of managing threads may outweigh the performance gains from parallel execution.
Debugging: Sequential execution simplifies debugging and can help isolate problems.

2. std::execution::par: Parallel Execution

This policy enables parallel execution of the algorithm. The standard library will utilize multiple threads to process the data concurrently, potentially offering significant performance improvements on multi-core processors.

3. std::execution::par_unseq: Parallel Unsequenced Execution

This policy is similar to par, but it allows for the execution order of operations within the algorithm to be unspecified. This means the order in which operations are performed is not guaranteed, leading to potential race conditions. Use this policy with caution, as it can lead to unexpected behavior if the algorithm relies on specific execution order.

4. std::execution::unseq: Unsequenced Execution

This policy executes the algorithm in an unsequenced manner, similar to par_unseq, but without the guarantee of parallel execution. The standard library may or may not utilize multiple threads.

Specifying the Number of Threads

While the execution policies par and par_unseq utilize multiple threads, you typically don't have direct control over the exact number of threads used. The standard library will attempt to determine the optimal number of threads based on available resources.

However, you can influence the number of threads indirectly through:

Environment Variables: System-specific environment variables, such as OMP_NUM_THREADS for OpenMP, can affect the number of threads used by the parallel execution policies.
Thread Pools: Consider using a thread pool, such as the one provided by the <thread> library, to manage your threads explicitly. This allows you to control the number of threads available for parallel algorithms.

Example: Parallel Summation

#include 
#include 
#include 
#include 

int main() {
  std::vector numbers = {1, 2, 3, 4, 5};

  // Calculate the sum using parallel execution
  int sum = std::reduce(std::execution::par, numbers.begin(), numbers.end(), 0);

  std::cout << "Sum: " << sum << std::endl;

  return 0;
}

Note: The actual number of threads used by std::execution::par in this example depends on the implementation of the standard library and the available resources.

Choosing the Right Execution Policy

The choice of execution policy depends on several factors:

Algorithm: Understand if the algorithm benefits from parallelization and if it has data dependencies.
Data Size: Parallelism is generally more beneficial for larger datasets.
Hardware: Consider the number of cores on your processor and the potential for thread contention.
Performance: Experiment and measure the performance impact of different execution policies to determine the best approach for your specific application.

By understanding execution policies and their nuances, you can write C++ programs that effectively utilize multi-core processors and achieve significant performance gains.