What is Agency? 
  Agency is an experimental C++ template library for parallel programming. Unlike higher-level parallel algorithms libraries like Thrust, Agency provides lower-level primitives for creating execution. Agency interoperates with standard components like execution policies and executors to enable the creation of portable parallel algorithms.
Examples
Agency is best-explained through examples. The following program implements a parallel sum.
#include <agency/agency.hpp>
#include <agency/experimental.hpp>
#include <vector>
#include <numeric>
#include <iostream>
#include <cassert>
int parallel_sum(int* data, int n)
{
  // create a view of the input
  agency::experimental::span<int> input(data, n);
  // divide the input into 8 tiles
  int num_agents = 8;
  auto tiles = agency::experimental::tile_evenly(input, num_agents);
  // create 8 agents to sum each tile in parallel
  {
    // get this parallel agent's tile
    auto this_tile = tiles[self.index()];
    // return the sum of this tile
    return std::accumulate(this_tile.begin(), this_tile.end(), 0);
  });
  // return the sum of partial sums
  return std::accumulate(partial_sums.begin(), partial_sums.end(), 0);
}
int main()
{
  // create a large vector filled with 1s
  std::vector<int> vec(32 << 20, 1);
  int sum = parallel_sum(vec.data(), vec.size());
  std::cout << "sum is " << sum << std::endl;
  assert(sum == vec.size());
  return 0;
}
This code example implements a vector sum operation and executes it sequentially, in parallel, in parallel on a single GPU, and finally multiple GPUs:
#include <agency/agency.hpp>
#include <agency/cuda.hpp>
#include <vector>
#include <cassert>
#include <iostream>
#include <algorithm>
int main()
{
  using namespace agency;
  // allocate data in GPU memory
  using vector = std::vector<float, cuda::managed_allocator<float>>;
  size_t n = 1 << 20;
  float a = 13;
  vector x(n, 1);
  vector y(n, 2);
  vector z(n, 0);
  vector reference(n, 13 * 1 + 2);
  float* x_ptr = x.data();
  float* y_ptr = y.data();
  float* z_ptr = z.data();
  // execute sequentially in the current thread
  {
    int i = self.index();
    z_ptr[i] = a * x_ptr[i] + y_ptr[i];
  });
  assert(z == reference);
  std::fill(z.begin(), z.end(), 0);
  // execute in parallel on the CPU
  {
    int i = self.index();
    z_ptr[i] = a * x_ptr[i] + y_ptr[i];
  });
  assert(z == reference);
  std::fill(z.begin(), z.end(), 0);
  // execute in parallel on a GPU
  cuda::grid_executor gpu;
  {
    int i = self.index();
    z_ptr[i] = a * x_ptr[i] + y_ptr[i];
  });
  assert(z == reference);
  std::fill(z.begin(), z.end(), 0);
  // execute in parallel on all GPUs in the system
  cuda::multidevice_executor all_gpus;
  {
    int i = self.index();
    z_ptr[i] = a * x_ptr[i] + y_ptr[i];
  });
  assert(z == reference);
  std::fill(z.begin(), z.end(), 0);
  std::cout << "OK" << std::endl;
  return 0;
}
Discover the Library
- Refer to Agency's Quick Start Guide for further information and examples.
 - See Agency in action in the collection of example programs.
 - Browse Agency's online API documentation.
 
Agency is an NVIDIA Research project.
          
          