A survey of numerical linear algebra methods utilizing mixed-precision arithmetic A Abdelfattah, H Anzt, EG Boman, E Carson, T Cojean, J Dongarra, A Fox, ... The International Journal of High Performance Computing Applications 35 (4 …, 2021 | 189 | 2021 |
FAIR principles for research software (FAIR4RS principles) NP Chue Hong, DS Katz, M Barker, AL Lamprecht, C Martinez, ... Zenodo, 2022 | 112 | 2022 |
Iterative sparse triangular solves for preconditioning H Anzt, E Chow, J Dongarra Euro-Par 2015: Parallel Processing: 21st International Conference on …, 2015 | 108 | 2015 |
Adaptive precision in block‐Jacobi preconditioning for iterative sparse linear system solvers H Anzt, J Dongarra, G Flegar, NJ Higham, ES Quintana‐Ortí Concurrency and Computation: Practice and Experience 31 (6), e4460, 2019 | 86 | 2019 |
Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing H Anzt, T Cojean, G Flegar, F Göbel, T Grützmacher, P Nayak, T Ribizel, ... ACM Transactions on Mathematical Software (TOMS) 48 (1), 1-33, 2022 | 78 | 2022 |
Incomplete sparse approximate inverses for parallel preconditioning H Anzt, TK Huckle, J Bräckle, J Dongarra Parallel Computing 71, 1-22, 2018 | 72 | 2018 |
An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action H Anzt, F Bach, S Druskat, F Löffler, A Loewe, BY Renard, G Seemann, ... F1000Research 9, 295, 2021 | 71 | 2021 |
Improving the performance of CA-GMRES on multicores with multiple GPUs I Yamazaki, H Anzt, S Tomov, M Hoemmen, J Dongarra 2014 IEEE 28th International Parallel and Distributed Processing Symposium …, 2014 | 71 | 2014 |
Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-σ formats on NVIDIA GPUs H Anzt, S Tomov, J Dongarra University of Tennessee, Tech. Rep. ut-eecs-14-727, 2014 | 62 | 2014 |
Using Jacobi iterations and blocking for solving sparse triangular systems in incomplete factorization preconditioning E Chow, H Anzt, J Scott, J Dongarra Journal of Parallel and Distributed Computing 119, 219-230, 2018 | 57 | 2018 |
Load-balancing sparse matrix vector product kernels on gpus H Anzt, T Cojean, C Yen-Chen, J Dongarra, G Flegar, P Nayak, S Tomov, ... ACM Transactions on Parallel Computing (TOPC) 7 (1), 1-26, 2020 | 54 | 2020 |
Preconditioned krylov solvers on GPUs H Anzt, M Gates, J Dongarra, M Kreutzer, G Wellein, M Köhler Parallel Computing 68, 32-44, 2017 | 52 | 2017 |
Asynchronous iterative algorithm for computing incomplete factorizations on GPUs E Chow, H Anzt, J Dongarra High Performance Computing: 30th International Conference, ISC High …, 2015 | 51 | 2015 |
HiFlow3 a flexible and hardware-aware parallel finite element package V Heuveline Proceedings of the 9th Workshop on Parallel/High-Performance Object-Oriented …, 2010 | 50 | 2010 |
Implementation and tuning of batched Cholesky factorization and solve for NVIDIA GPUs J Kurzak, H Anzt, M Gates, J Dongarra IEEE Transactions on Parallel and Distributed Systems 27 (7), 2036-2048, 2015 | 49 | 2015 |
Accelerating the LOBPCG method on GPUs using a blocked sparse matrix vector product. H Anzt, S Tomov, JJ Dongarra SpringSim (HPS), 75-82, 2015 | 49 | 2015 |
With extreme computing, the rules have changed J Dongarra, S Tomov, P Luszczek, J Kurzak, M Gates, I Yamazaki, H Anzt, ... Computing in Science & Engineering 19 (3), 52-62, 2017 | 45 | 2017 |
ParILUT---a new parallel threshold ILU factorization H Anzt, E Chow, J Dongarra SIAM Journal on Scientific Computing 40 (4), C503-C519, 2018 | 42 | 2018 |
Accelerating collaborative filtering using concepts from high performance computing M Gates, H Anzt, J Kurzak, J Dongarra 2015 IEEE International Conference on Big Data (Big Data), 667-676, 2015 | 41 | 2015 |
Acceleration of GPU-based Krylov solvers via data transfer reduction H Anzt, S Tomov, P Luszczek, W Sawyer, J Dongarra The International Journal of High Performance Computing Applications 29 (3 …, 2015 | 38 | 2015 |