HPX meets Fedora

With the release of HPX 1.2.0, we added support of HPX to the offical Fedora updates-testing repository. Following packages are available on Fedora 28/29

We provide HPX compiled with the GNU compiler collection, with the OpenMPI compiler, and the MPICH compiler.  The hpx-devel packages contains the header files and he hpx-*-examples package contains all the examples compiled with the respective compiler.  The purpose of these packages is educational and we hope to lower the entrance point to experiment with HPX. For performance measurements we recommend to compile HPX on the used hardware.

HPX 1.2.0 Released!

The STE||AR Group is proud to announce the release of HPX 1.2.0. This release is the first in our more frequent release schedule. We are aiming to produce one release every six months in an effort to get new features and stable releases out to users more quickly. As a result this release is smaller than many previous releases, but nevertheless contains many important improvements. This release includes among others performance improvements, a new implementation of hpx_main.hpp, scheduler hints, and many stability improvements. This release also removes many previously deprecated features. Make sure you read the full release notes to see which deprecated features were removed.

Thank you to everyone who has contributed from all over the world!

Download the release below, from our download page, or from our GitHub page.

HPX 1.1.0 Released!

The STE||AR Group is proud to announce the release of HPX 1.1.0, 10 years after the first commit! This release contains 2300 commits since the previous release and has closed over 150 issues. HPX 1.1.0 brings users full control over how HPX uses processing units, improvements to parallel algorithms and many other usability improvements. This release would not have been possible without the help of all the people who have contributed bug reports, questions, testing, code and improvements to the documentation. Thank you!

Download the release using the links below, from our download page, or from our GitHub page.

Using HPX on Windows

HPX is a C++ Standard Library for Parallelism and Concurrency. Building and using it on Windows just got much less involved. We have now integrated HPX into the VcPkg VC++ Packaging Tool. This tool is design to help you getting C and C++ libraries built and installed on Windows without hassle. It manages all package dependencies for you, such that — once HPX has been built — no additional settings have to be supplied to your build environment.

HPX V1.0 Released!

The STE||AR Group is proud to announce the release of HPX V1.0. While we call it version one, it is in fact the fifteenth official release of our library. This release has become possible as we now have implemented all the features we set out to put in place for this version.

HPX is the C++ Standard library for parallelism and concurrency.  It implements all of the related facilities as defined by the C++ Standard. As of this writing, HPX provides the only widely available open-source implementation of the new C++17 parallel algorithms. Additionally, in HPX we implement functionalities proposed as part of the ongoing C++ standardization process, such as large parts of the C++ Concurrency TS, task blocks, data-parallel algorithms, executors, index-based parallel for loops, and many more. We also extend the existing C++ Standard APIs to the distributed case (e.g. compute clusters) and for heterogeneous systems (e.g. GPUs).

At its heart, HPX is an asynchronous many-task runtime system for the distributed world. It is portable in code and performance across a wide variety of architectures and operating systems. We have shown that it is usable on almost any machine from a Raspberry Pi to the biggest computers available to us. Applications relying on HPX will scale from small handheld devices up to machines with thousands of compute-nodes and millions of processors. For example, we have just successfully run an HPX application on the full NERSC Cori machine, a cluster with 9640 Intel Knight’s Landing compute nodes (655520 cores).

The new C++ Standard facilities listed fit perfectly with some of our extensions targeting asynchronous operations, such as asynchronous parallel algorithms, asynchronous task blocks, or dataflow constructs. As a result, HPX changes the way we write programs in modern C++. It seamlessly enables a new asynchronous C++ Standard Programming Model which tends to improve the parallel efficiency of our applications and helps reduce complexities usually associated with concurrency. At the same time, HPX’s API is strictly aligned with the C++ standardization process which removes the barriers of adoption.

The code base of HPX is very mature and of very high code quality. Our extensive testing has definitely paid off. Many people have contributed to this release — we would like to thank all of them for their efforts. This release incorporates nearly 1500 commits and has closed almost 300 tickets and pull requests submitted by collaborators from all over the world. We have introduced several important changes:

  • We added various new higher-level parallelization facilities, such as more parallel algorithms, range based parallel algorithms, and channels — all well aligned with various C++ standardization documents.
  • We now support transparently migrating objects across compute-node boundaries, which is a major feature supporting dynamic load balancing in large distributed applications.
  • We have refactored our thread-scheduling subsystem for improved performance and less overheads.
  • We have added a new network transport module enabling direct support for Infiniband networks.
  • We have added a long list of new performance counters exposing different runtime parameters.
  • We have improved the integration with external diagnostic tools, such as APEX and Intel Amplifier or Intel Inspector.

How to Download:

For a complete list of new features and breaking changes please see our release notes. If you have any questions, comments, or exploits to report you can comment below, reach us on IRC (#stellar on Freenode), or email us at hpx-users@stellar.cct.lsu.edu. We value your input!