HPX, short for High Performance ParalleX, is a runtime system for high-performance computing. It is currently under active development by the STE||AR group[2] at Louisiana State University. Focused on scientific computing, it provides an alternative execution model to conventional approaches such as MPI. HPX aims to overcome the challenges MPI faces with increasing large supercomputers by using asynchronous communication between nodes and lightweight control objects instead of global barriers, allowing application developers to exploit fine-grained parallelism.[3][4][5]
HPX is developed in idiomatic C++ and released as open source under the Boost Software License, which allows usage in commercial applications.
Applications
Though designed as a general-purpose environment for high-performance computing, HPX has primarily been used in
^Kaiser, Hartmut; Brodowicz, Maciek; Sterling, Thomas (2009). "ParalleX an Advanced Parallel Execution Model for Scaling-Impaired Applications". 2009 International Conference on Parallel Processing Workshops. pp. 394–401. doi:10.1109/icppw.2009.14. ISBN978-1-4244-4923-1. S2CID898158.
^Wagle, Bibek; Kellar, Samuel; Serio, Adrian; Kaiser, Hartmut (2018). "Methodology for Adaptive Active Message Coalescing in Task Based Runtime Systems". 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). pp. 1133–1140. doi:10.1109/IPDPSW.2018.00173. ISBN978-1-5386-5555-9. S2CID51921994.
^ abWagle, Bibek; Monil, Mohammad Alaul Haque; Huck, Kevin; Malony, Allen D.; Serio, Adrian; Kaiser, Hartmut (2019). "Runtime Adaptive Task Inlining on Asynchronous Multitasking Runtime Systems". Proceedings of the 48th International Conference on Parallel Processing. pp. 1–10. doi:10.1145/3337821.3337915. ISBN9781450362955. S2CID198963569.
^C. Dekate, M. Anderson, M. Brodowicz, H. Kaiser, B. Adelstein-Lelbach and T. Sterling (2012). "Improving the Scalability of Parallel N-body Applications with an Event-driven Constraint-based Execution Model". International Journal of High Performance Computing Applications. 26 (3): 319–332. arXiv:1109.5190. doi:10.1177/1094342012440585. S2CID9556798.{{cite journal}}: CS1 maint: multiple names: authors list (link)
^D. Pfander, G. Daiß, D. Marcello, H. Kaiser, D. Pflüger, David (2018). "Accelerating Octo-Tiger: Stellar Mergers on Intel Knights Landing with HPX". DHPCC++ Conference 2018 Hosted by IWOCL. doi:10.1145/3204919.3204938. S2CID21126354.{{cite journal}}: CS1 maint: multiple names: authors list (link)
^A. Schäfer, D. Fey (2008). "LibGeoDecomp: A Grid-Enabled Library for Geometric Decomposition Codes". Recent Advances in Parallel Virtual Machine and Message Passing Interface. Lecture Notes in Computer Science. Vol. 5205. pp. 285–294. doi:10.1007/978-3-540-87475-1_39. ISBN978-3-540-87474-4.