HPX V1.10.0 released -- STE||AR Group

The STE||AR Group has released V1.10.0 of HPX -- A C++ Standard library for Concurrency and Parallelism.

HPX V1.10.0 Released

We have released HPX 1.10.0 — a major update to our C++ Standard Library for Concurrency and Parallelism. We have continued to modernize HPX to fully conform to the latest standardization efforts in the are of parallelism and concurrency. Our HPX documentation has seen a major overhaul for this release, please have a look here. We finished documenting the public local HPX API, we have added migration guides from widely used parallelization platforms to HPX (OpenMP, TBB, and MPI). Among other things, we have performed a lot of code cleanup and refactoring to improve the overall code quality and decrease compile times and to improve the consistency of our exposed APIs. The core implementation has seen many performance optimizations that impact every aspect of our applications.

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!

You can download the release from our releases page or check out the v1.10.0 tag using git. A full list of changes can be found in the release notes.

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.


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