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Software for Linear Algebra Targeting Exascale
Innovative Computing Laboratory
University of Tennessee
SLATE will offer a modern replacement for ScaLAPACK. ScaLAPACK is a numerical software library of dense linear algebra routines essential to the field of scientific and engineering computing, with good asymptotic scaling properties, but lack of support for modern node architectures, which are based on multicore processors and hardware accelerators, and characterized by complex memory hierarchies.
SLATE will allow for the development of multicore and accelerator capabilities, by leveraging recent progress and ongoing efforts in mainstream programming models (MPI3 and beyond, OpenMP4 and beyond, OpenACC, etc.), and runtime scheduling systems (PaRSEC, Legion, etc.). Also, part of the SLATE project is the development of C++ APIs for BLAS++ and LAPACK++.
- SLATE Users' Guide
- SLATE Function Reference
- SLATE Working Note 3: Designing SLATE: Software for Linear Algebra Targeting Exascale
Need assistance with the SLATE software?
Join the SLATE User Google group by going to
Apply to join group.
Upon acceptance, email your questions and comments to firstname.lastname@example.org.
- Visit the SLATE website for more information about the SLATE project.
- Visit the SLATE Working Notes to find out more about ongoing SLATE developments.
- Visit the BLAS++ repository for more information about the C++ API for BLAS.
- Visit the LAPACK++ repository for more information about the C++ API for LAPACK.
- Visit the ECP website to find out more about the DOE Exascale Computing Initiative.
This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration) responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering and early testbed platforms, in support of the nation's exascale computing imperative.
This research uses resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. This research also uses resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.
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