We have released HPX 1.9.1 that adds a number of small new features and fixes a handful of problems discovered since the last 1.9.0 release. In particular: we fixed various occasional hanging during startup and shutdown in distributed scenarios. We also added support for zero-copy serialization on the receiving side to the TCP, MPI, and LCI parcelports. Moreover, we have added support for Visual Studio 2019 and GCC using MINGW on Windows, and also support for GCC 13 and Clang 15.0.0. Furthermore, we aligned our header names to their standards counterparts so porting from standard C++ to HPX is now easier. Last but not least, and by adhering to popular demand, we started adding migration guides for people interested in moving their codes away from other, commonplace parallelization frameworks like OpenMP and MPI. We have also continued to improve our documentation, please have a look here.
If you have any questions, comments, or exploits to report you can reach us on IRC or Matrix (#ste||ar on libera.chat) or email us at hpx-users. We depend on your input!
HPX is a general-purpose parallel C++ runtime system for applications of any scale. It implements all of the related facilities as defined by the C++20 Standard. As of this writing, HPX provides the only widely available open-source implementation of the new C++17, C++20, and C++23 parallel algorithms, including a full set of parallel range-based algorithms. Additionally, HPX implements functionalities proposed as part of the ongoing C++ standardization process, such as large parts of the features related parallelism and concurrency as specified by the upcoming C++23 Standard, the C++ Concurrency TS, Parallelism TS V2, data-parallel algorithms, executors, and many more. It also extends the existing C++ Standard APIs to the distributed case (e.g., compute clusters) and for heterogeneous systems (e.g., GPUs).
HPX seamlessly enables a new Asynchronous C++ Standard Programming Model that tends to improve the parallel efficiency of our applications and helps reducing complexities usually associated with parallelism and concurrency.