Publications
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Filters: Author is Hartwig Anzt [Clear All Filters]
Flexible Batched Sparse Matrix Vector Product on GPUs
, Denver, Colorado, ScalA'17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, November 2017.
(16.8 MB)

Experiences in autotuning matrix multiplication for energy minimization on GPUs,”
Concurrency in Computation: Practice and Experience, vol. 27, issue 17, pp. 5096-5113, December 2015.
(1.98 MB)
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Adaptive Precision in Block-Jacobi Preconditioning for Iterative Sparse Linear System Solvers,”
Concurrency and Computation: Practice and Experience, vol. 31, no. 6, pp. e4460, March 2019.
(341.54 KB)
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On block-asynchronous execution on GPUs,”
LAPACK Working Note, no. 291, November 2016.
(1.05 MB)
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Ginkgo: A Node-Level Sparse Linear Algebra Library for HPC (Poster)
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(699 KB)

A Block-Asynchronous Relaxation Method for Graphics Processing Units,”
University of Tennessee Computer Science Technical Report, no. UT-CS-11-687 / LAWN 258, November 2011.
(1.08 MB)
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Preconditioned Krylov Solvers on GPUs,”
Parallel Computing, June 2017.
(1.19 MB)
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