Publications
“Variable-Size Batched LU for Small Matrices and Its Integration into Block-Jacobi Preconditioning,”
46th International Conference on Parallel Processing (ICPP), Bristol, United Kingdom, IEEE, August 2017.
DOI: 10.1109/ICPP.2017.18
“ParILUT – A Parallel Threshold ILU for GPUs,”
IEEE International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, IEEE, May 2019.
DOI: 10.1109/IPDPS.2019.00033 
(505.95 KB)
(505.95 KB)
MAGMA MIC: Optimizing Linear Algebra for Intel Xeon Phi
, Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, June 2015.
(2.03 MB)
(2.03 MB)
“GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement,”
EuroPar 2012 (also LAWN 260), Rhodes Island, Greece, August 2012.
(662.98 KB)
(662.98 KB)
“Fine-grained Bit-Flip Protection for Relaxation Methods,”
Journal of Computational Science, November 2016.
DOI: 10.1016/j.jocs.2016.11.013 (1.47 MB)
(1.47 MB)
“High-Performance GPU Implementation of PageRank with Reduced Precision based on Mantissa Segmentation,”
8th Workshop on Irregular Applications: Architectures and Algorithms, 2018.
“Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing,”
ACM Transactions on Mathematical Software, vol. 48, issue 12, pp. 1 - 33, March 2022.
DOI: 10.1145/3480935 (4.2 MB)
(4.2 MB)
“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)
“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.
DOI: 10.1002/cpe.4460 (341.54 KB)
(341.54 KB)
Gingko: A Sparse Linear Algebrea Library for HPC
: 2021 ECP Annual Meeting, April 2021.
(893.04 KB)
(893.04 KB)
“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)
“Incomplete Sparse Approximate Inverses for Parallel Preconditioning,”
Parallel Computing, vol. 71, pp. 1–22, January 2018.
DOI: 10.1016/j.parco.2017.10.003 (1.24 MB)
(1.24 MB)
“Variable-Size Batched Gauss-Jordan Elimination for Block-Jacobi Preconditioning on Graphics Processors,”
Parallel Computing, vol. 81, pp. 131-146, January 2019.
DOI: 10.1016/j.parco.2017.12.006 (1.9 MB)
(1.9 MB)
“Variable-Size Batched Condition Number Calculation on GPUs,”
SBAC-PAD, Lyon, France, September 2018.
(509.3 KB)
(509.3 KB)
“Towards Continuous Benchmarking,”
Platform for Advanced Scientific Computing Conference (PASC 2019), Zurich, Switzerland, ACM Press, June 2019.
DOI: 10.1145/3324989.3325719 (1.51 MB)
(1.51 MB)
“AI Benchmarking for Science: Efforts from the MLCommons Science Working Group,”
Lecture Notes in Computer Science, vol. 13387: Springer International Publishing, pp. 47 - 64, January 2023.
DOI: 10.1007/978-3-031-23220-610.1007/978-3-031-23220-6_4
“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)
“Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures,”
VECPAR 2014, Eugene, OR, June 2014.
(430.56 KB)
(430.56 KB)
“Optimization and Performance Evaluation of the IDR Iterative Krylov Solver on GPUs,”
The International Journal of High Performance Computing Applications, vol. 32, no. 2, pp. 220–230, March 2018.
DOI: 10.1177/1094342016646844 (2.08 MB)
(2.08 MB)
“A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs,”
SBAC-PAD, Lyon, France, IEEE, 2018.
(237.68 KB)
(237.68 KB)
“Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems,”
ICCS 2012, Omaha, NE, June 2012.
(608.95 KB)
(608.95 KB)
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)
(16.8 MB)
“Toward a Modular Precision Ecosystem for High-Performance Computing,”
The International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1069-1078, November 2019.
DOI: 10.1177/1094342019846547 (1.93 MB)
(1.93 MB)
“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
“ParILUT - A New Parallel Threshold ILU,”
SIAM Journal on Scientific Computing, vol. 40, issue 4: SIAM, pp. C503–C519, July 2018.
DOI: 10.1137/16M1079506 (19.26 MB)
(19.26 MB)
“Preconditioned Krylov Solvers on GPUs,”
Parallel Computing, June 2017.
DOI: 10.1016/j.parco.2017.05.006 (1.19 MB)
(1.19 MB)
“Are we Doing the Right Thing? – A Critical Analysis of the Academic HPC Community,”
2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Rio de Janeiro, Brazil, IEEE, May 2019.
DOI: 10.1109/IPDPSW.2019.00122 (622.32 KB)
(622.32 KB)
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)
