The Exascale Computing Project has concluded. This site is retained for historical references.

ALExa

The Accelerated Libraries for Exascale (ALExa) project provides efficient scalable algorithms for geometric search and clustering, transferring data between grid with non-matching parallel distributions, and constructing reduced representations of high-dimensional data (e.g., to optimize storage). The several libraries of the project address these needs for the exascale applications, including those written in Fortran.

Technical Discussion

The ALExa project consists of four libraries to address the needs of the applications for an efficient use of the exascale systems: ArborX, Tasmanian, DataTransferKit, and ForTrilinos.

The ArborX library provides performance portable geometric search algorithms, such as finding all objects within certain distance or a fixed number of closest objects. While similar in scope to the well-known nanoflann and Boost.Geometry.Index libraries, the emphasis of the library is on providing efficient parallel algorithms for a high-performance computing (HPC) environment. The library further provides several algorithms built on top of the geometric search functionality, including popular density-based clustering algorithms such as DBSCAN and HDBSCAN.

The Tasmanian library provides the ability to construct surrogate models with low memory footprint, low cost, and optimal computational throughput, enabling optimization and uncertainty quantification for large-scale engineering problems, as well as efficient multiphysics simulations.

The DataTransferKit library provides the ability to transfer computed solutions between grids with different layouts on parallel accelerated architectures, enabling simulations to seamlessly combine results from different computational grids to perform their required simulations.

The ForTrilinos project developed SWIG-Fortran, a tool for easy automatic generation of Fortran interfaces to any C/C++ library. This tool generates the ForTrilinos interface library, as a seamless pathway for large and complex Fortran-based codes to access Trilinos numerical solvers. SWIG-Fortran also provides Fortran bindings to other scientific libraries, including DTK, STRUMPACK, SUNDIALS, Tasmanian, and numerical components of the C++ standard library.

Principal Investigator(s)

Andrey Prokopenko, Oak Ridge National Laboratory

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