Shaping a Scalable Future
The STE||AR Group is an international team of researchers who understand that a new approach to parallel computation is needed. Our work is crafted around the idea that we need to invent new ways to more efficiently use the resources that we have and use the knowledge that we gain to help guide the creation of the machines of tomorrow. While we develop several software products, the library which is most heavily developed and core to our team is HPX.
HPX (High Performance ParalleX) is a general purpose C++ runtime system for parallel and distributed applications of any scale. It strives to provide a unified programming model which transparently utilizes the available resources to achieve unprecedented levels of scalability.
This library strictly adheres to the C++11 Standard and leverages the Boost C++ Libraries which makes HPX easy to use, highly optimized, and very portable. HPX is developed for conventional architectures including Linux-based systems, Windows, Mac, and the BlueGene/Q, as well as accelerators such as the Xeon Phi.
We envision HPX as a library which provides services to applications which makes writing efficient, maintainable, and scalable parallel and distributed codes much simpler than current popular paradigms. Currently HPX is used to develop scientific and industrial applications and in the future we hope to expand its influence to include common applications that touch our everyday lives.
If you are looking for a project which incorporates cutting edge HPC research, runtime library development, and C++ standardization check out our ideas page and contact us either through the #ste||ar channel on IRC (Freenode) or via an email at
Ste||ar group 2020 Projects
Adapt parallel algorithms to C++20The goal is to adapt or add all the algorithms that are exposed by the latest C++ standard (C++20). This includes, creating new algorithm...
Concurrent Data StructureSTL containers such as vectors/maps/sets/etc are not thread-safe. One cannot safely add or remove elements from one of these containers in one...
Domain decomposition, load balancing, and massively parallel solvers for the class of nonlocal modelsRecently various nonlocal models have been applied for understanding of complex spatially multiscale phenomena like solid mechanics, fluid mechanics,...
pip package for PhylanxPhylanx relies on many external libraries which makes the building process tedious and error prone, especially to the target audience of the...
Time Series Updates for TravelerIn this Google summer project, my goal is to make the Traveler interface more illustrative, interactive, and responsive by reducing visual lagging,...