RAJA

RAJA is a collection of C++ software abstractions, being developed at Lawrence Livermore National Laboratory (LLNL), that enable architecture portability for HPC applications. The overarching goals of RAJA are to: Make existing (production) applications portable with minimal disruption; Provide a model for new applications so that they are portable from inception. RAJA uses standard C++11 -- C++ is the predominant programming language in which many LLNL codes are written. RAJA is rooted in a perspective based on substantial experience working on production mesh-based multiphysics applications at LLNL. Another goal of RAJA is to enable application developers to adapt RAJA concepts and specialize them for different code implementation patterns and C++ usage, since data structures and algorithms vary widely across applications. RAJA shares goals and concepts found in other C++ portability abstraction approaches, such as Kokkos and Thrust. However, it includes concepts that are absent in other models and which are fundamental to LLNL codes. It is important to note that RAJA is very much a work-in-progress. The community of researchers and application developers at LLNL that are actively contributing to it and developing new capabilities is growing. The publicly-released version contains only core pieces of RAJA as they exist today. While the basic interfaces are fairly stable, the implementation of the underlying concepts is being refined. Additional features will appear in future releases.


References in zbMATH (referenced in 7 articles )

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  1. Anderson, Robert; Andrej, Julian; Barker, Andrew; Bramwell, Jamie; Camier, Jean-Sylvain; Cerveny, Jakub; Dobrev, Veselin; Dudouit, Yohann; Fisher, Aaron; Kolev, Tzanio; Pazner, Will; Stowell, Mark; Tomov, Vladimir; Akkerman, Ido; Dahm, Johann; Medina, David; Zampini, Stefano: MFEM: a modular finite element methods library (2021)
  2. Anton Afanasyev, Mauro Bianco, Lukas Mosimann, Carlos Osuna, Felix Thaler, Hannes Vogt, Oliver Fuhrer, Joost VandeVondele, Thomas C. Schulthess: GridTools: A framework for portable weather and climate applications (2021) not zbMATH
  3. Christlieb, Andrew J.; Guthrey, Pierson T.; Sands, William A.; Thavappiragasm, Mathialakan: Parallel algorithms for successive convolution (2021)
  4. Hokkanen, Jaro; Kollet, Stefan; Kraus, Jiri; Herten, Andreas; Hrywniak, Markus; Pleiter, Dirk: Leveraging HPC accelerator architectures with modern techniques -- hydrologic modeling on GPUs with ParFlow (2021)
  5. Jean Sexton, Zarija Lukic, Ann Almgren, Chris Daley, Brian Friesen, Andrew Myers, Weiqun Zhang: Nyx: A Massively Parallel AMR Code for Computational Cosmology (2021) not zbMATH
  6. Greene, Patrick T.; Schofield, Samuel P.; Nourgaliev, Robert: Dynamic mesh adaptation for front evolution using discontinuous Galerkin based weighted condition number relaxation (2017)
  7. Nourgaliev, R.; Luo, H.; Weston, B.; Anderson, A.; Schofield, S.; Dunn, T.; Delplanque, J.-P.: Fully-implicit orthogonal reconstructed discontinuous Galerkin method for fluid dynamics with phase change (2016)