Publications
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Filters: Author is Hartwig Anzt [Clear All Filters]
“Towards a New Peer Review Concept for Scientific Computing ensuring Technical Quality, Software Sustainability, and Result Reproducibility,”
Proceedings in Applied Mathematics and Mechanics, vol. 19, issue 1, November 2019.
DOI: 10.1002/pamm.201900490
“Flexible Batched Sparse Matrix-Vector Product on GPUs,”
8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA '17), Denver, CO, ACM Press, November 2017.
DOI: http://dx.doi.org/10.1145/3148226.3148230 
(583.4 KB)
(583.4 KB)
“Ginkgo: A High Performance Numerical Linear Algebra Library,”
Journal of Open Source Software, vol. 5, issue 52, August 2020.
DOI: 10.21105/joss.02260 (721.84 KB)
(721.84 KB)
“Load-Balancing Sparse Matrix Vector Product Kernels on GPUs,”
ACM Transactions on Parallel Computing, vol. 7, issue 1, March 2020.
DOI: 10.1145/3380930 (5.67 MB)
(5.67 MB)
“Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse and Batched Computations,”
2020 IEEE/ACM Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS): IEEE, November 2020.
(1.9 MB)
(1.9 MB)
Ginkgo: A Node-Level Sparse Linear Algebra Library for HPC (Poster)
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(699 KB)
(699 KB)
Gingko: A Sparse Linear Algebrea Library for HPC
: 2021 ECP Annual Meeting, April 2021.
(893.04 KB)
(893.04 KB)
