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Bulk is a new interface for writing bulk synchronous parallel programs in C++. It lets you implement parallel algorithms by providing common communication mechanisms between processing elements, such as threads, MPI nodes or cores in a many-core accelerator,

Bulk does away with unnecessary boilerplate code and the unsafe API's that are found in for example MPI, or the BSPlib standard. It provides a unified syntax for parallel programming across different platforms and modalities. Our BSP interface supports and encourages the use of modern C++ features, enabling safer and more efficient distributed programming. We have a flexible backend architecture, so that programs written with Bulk work for both shared memory, distributed memory, or mixed systems.

About BSP

The bulk synchronous parallel (BSP) programming model, is a way of writing parallel and distributed programs. BSP is the underlying model for Bulk. Instead of communicating between processors (or nodes, or cores) asynchronously, all communication is staged and resolved at fixed synchronization points. These synchronizations delimit so-called supersteps. This way of writing parallel programs has the following benefits:

  • The resulting programs are structured, easy to understand and maintain, and their performance and correctness can be reasoned about precisely.
  • Data races are eliminated by construction, because of simple rules which can be enforced at runtime.
  • Scalability is easy to obtain, programs are written in a SPMD fashion.
  • The number of communication mechanisms required are very limited, support for message passing or named communication (through distributed variables). This makes BSP based libraries very economic (you can do much with very little).
  • It has a low cost of entry. It is easy to write correct BSP programs (while it is notoriously hard to write correct asynchronous parallel programs).


Hello world!

bulk::thread::environment env;
env.spawn(env.available_processors(), [](auto& world) {
    auto s = world.rank();
    auto p = world.active_processors();

    world.log("Hello world from processor %d / %d!", s, p);

Distributed variables are the easiest way to communicate.

auto a = bulk::var<int>(world);
a(world.next_rank()) = s;
// ... a is now updated

auto b = a(world.next_rank()).get();
// ... b.value() is now available

Coarrays are convenient distributed arrays.

auto xs = bulk::coarray<int>(world, 10);
xs(world.next_rank())[3] = s;

Message passing can be used for more flexible communication.

auto q = bulk::queue<int, float>(world);
for (int t = 0; t < p; ++t) {
    q(t).send(s, 3.1415f);  // send (s, pi) to processor t

// messages are now available in q
for (auto [tag, content] : q) {
    world.log("%d got sent %d, %f\n", s, tag, content);


Bulk requires an up-to-date compiler, that supports C++17, e.g. GCC >= 7.0, or Clang >= 4.0.

Bulk supports a number of different backends, allowing the programs to run in parallel using:

  • thread for multi-core systems using standard C++ <thread> threading support
  • mpi for distributed environments using MPI

The examples in the examples directory work for every backend. To build them, do the following. The backends (e.g. thread, mpi) are built optionally, just remove or add the option if you do not require them.

mkdir build
cd build
cmake ..
make thread mpi

The examples will be compiled in the bin/{backend} directory, prepended with the backend name, i.e. to run the hello example with the thread backend:


There is also a special backend available for the Epiphany coprocessor, which can be found in the epiphany branch. It also has modified version of Bulk to support portability between MPI, <thread> and the Epiphany coprocessor. See backends/epiphany/README.md for more details.


Bulk is developed at Centrum Wiskunde & Informatica (CWI) in Amsterdam by:

  • Jan-Willem Buurlage (@jwbuurlage)
  • Tom Bannink (@tombana)


Bulk is released under the MIT license, see LICENSE.md.


We welcome contributions. Please submit pull requests against the develop branch.

If you have any issues, questions, or remarks, then please open an issue on GitHub.