The traditionally used and well established parallel programming models OpenMP and MPI are both targeting lower level parallelism and are meant to be as language agnostic as possible. For a long time, those models were the only widely available portable options for developing parallel C++ applications beyond using plain threads. This has strongly limited the optimization capabilities of compilers, has inhibited extensibility and genericity, and has restricted the use of those models together with other, modern higher level abstractions introduced by the C++11 and C++14 standards.
The recent revival of interest in the industry and wider community for the C++ language has also spurred a remarkable amount of standardization proposals and technical specifications being developed. Those efforts however have so far failed to build a vision on how to seamlessly integrate various types of parallelism, such as iterative parallel execution, task-based parallelism, asynchronous many-task execution flows, continuation style computation, or explicit fork-join control flow of independent and non-homogeneous code paths.

In this talk we present the results of developing higher level parallelization facilities in HPX, a general purpose C++ runtime system for applications of any scale. The developed higher-level parallelization APIs have been designed aiming at overcoming the limitations of today's prevalently used programming models in C++ codes.
HPX exposes a uniform higher-level API which gives the application programmer syntactic and semantic equivalence of various types of on-node and off-node parallelism, all of which are well integrated into the C++ type system. We show that these higher level facilities are fully aligned with modern C++ programming concepts, they are easily extensible, fully generic, and enable highly efficient parallelization on par with or better than what existing equivalent applications based on OpenMP and/or MPI can achieve.