40 citations · 101 across the 19 of their papers we have counts for
7 papers · 1 filter
pyGinkgo: A Sparse Linear Algebra Operator Framework for Python
Keshvi Tuteja, Gregor Olenik, Roman Mishchuk +5
Sparse linear algebra is a cornerstone of many scientific computing and machine learning applications. Python has become a popular choice for these applications due to its simplici…
Interface for Sparse Linear Algebra Operations
Ahmad Abdelfattah, Willow Ahrens, Hartwig Anzt +32
The standardization of an interface for dense linear algebra operations in the BLAS standard has enabled interoperability between different linear algebra libraries, thereby boosti…
Compressed Basis GMRES on High Performance GPUs
José I. Aliaga, Hartwig Anzt, Thomas Grützmacher +2
Krylov methods provide a fast and highly parallel numerical tool for the iterative solution of many large-scale sparse linear systems. To a large extent, the performance of practic…
Evaluating the Performance of NVIDIA's A100 Ampere GPU for Sparse Linear Algebra Computations
Yuhsiang Mike Tsai, Terry Cojean, Hartwig Anzt
GPU accelerators have become an important backbone for scientific high performance computing, and the performance advances obtained from adopting new GPU hardware are significant.…
A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic
Ahmad Abdelfattah, Hartwig Anzt, Erik G. Boman +22
Within the past years, hardware vendors have started designing low precision special function units in response to the demand of the Machine Learning community and their demand for…
Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing
Hartwig Anzt, Terry Cojean, Goran Flegar +6
In this paper, we present Ginkgo, a modern C++ math library for scientific high performance computing. While classical linear algebra libraries act on matrix and vector objects, Gi…