Publications
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With Extreme Computing, the Rules Have Changed,”
Computing in Science & Engineering, vol. 19, issue 3, pp. 52-62, May 2017.
DOI: 10.1109/MCSE.2017.48 (485.34 KB)
“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
“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)
“Variable-Size Batched Gauss-Huard for Block-Jacobi Preconditioning,”
International Conference on Computational Science (ICCS 2017), vol. 108, Zurich, Switzerland, Procedia Computer Science, pp. 1783-1792, June 2017.
DOI: 10.1016/j.procs.2017.05.186 (512.57 KB)
“Variable-Size Batched Condition Number Calculation on GPUs,”
SBAC-PAD, Lyon, France, September 2018.
(509.3 KB)
“Using Jacobi Iterations and Blocking for Solving Sparse Triangular Systems in Incomplete Factorization Preconditioning,”
Journal of Parallel and Distributed Computing, vol. 119, pp. 219–230, November 2018.
DOI: 10.1016/j.jpdc.2018.04.017 (273.53 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)
“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
“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)
“A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic,”
SLATE Working Notes, no. 15, ICL-UT-20-08: University of Tennessee, July 2020.
(3.98 MB)
“Sparse matrix-vector and matrix-multivector products for the truncated SVD on graphics processors,”
Concurrency and Computation: Practice and Experience, August 2023.
DOI: 10.1002/cpe.7871
“Sparse Linear Algebra on AMD and NVIDIA GPUs—The Race is On,”
ISC High Performance: Springer, June 2020.
DOI: 10.1007/978-3-030-50743-5_16 (5.63 MB)
“Solver Interface & Performance on Cori,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-18-05: University of Tennessee, June 2018.
(188.05 KB)
“Software-Defined Events (SDEs) in MAGMA-Sparse,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-18-12: University of Tennessee, December 2018.
(481.69 KB)
“Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures,”
VECPAR 2014, Eugene, OR, June 2014.
(430.56 KB)
“Scalable Data Generation for Evaluating Mixed-Precision Solvers,”
2020 IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, USA, IEEE, September 2020.
DOI: 10.1109/HPEC43674.2020.9286145 (1.3 MB)
“Roadmap for the Development of a Linear Algebra Library for Exascale Computing: SLATE: Software for Linear Algebra Targeting Exascale,”
SLATE Working Notes, no. 01, ICL-UT-17-02: Innovative Computing Laboratory, University of Tennessee, June 2017.
(2.8 MB)
“Preconditioned Krylov Solvers on GPUs,”
Parallel Computing, June 2017.
DOI: 10.1016/j.parco.2017.05.006 (1.19 MB)
“On the performance and energy efficiency of sparse linear algebra on GPUs,”
International Journal of High Performance Computing Applications, October 2016.
DOI: 10.1177/1094342016672081 (1.19 MB)
“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)
“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)
“Parallel Selection on GPUs,”
Parallel Computing, vol. 91, March 2020, 2019.
DOI: 10.1016/j.parco.2019.102588 (1.43 MB)
“PAPI Software-Defined Events for in-Depth Performance Analysis,”
The International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1113-1127, November 2019.
(442.39 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)
“Multiprecision Block-Jacobi for Iterative Triangular Solves,”
European Conference on Parallel Processing (Euro-Par 2020): Springer, August 2020.
DOI: 10.1007/978-3-030-57675-2_34
“MAGMA MIC: Optimizing Linear Algebra for Intel Xeon Phi
, Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, June 2015.
(2.03 MB)
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)
“Linear Algebra Software for Large-Scale Accelerated Multicore Computing,”
Acta Numerica, vol. 25, pp. 1-160, May 2016.
DOI: 10.1017/S0962492916000015
“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)
“Heterogeneous Streaming,”
The Sixth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), IPDPS 2016, Chicago, IL, IEEE, May 2016.
(2.73 MB)
“GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement,”
EuroPar 2012 (also LAWN 260), Rhodes Island, Greece, August 2012.
(662.98 KB)
“Ginkgo—A math library designed for platform portability,”
Parallel Computing, vol. 111, pp. 102902, February 2022.
DOI: 10.1016/j.parco.2022.102902
“Ginkgo: A Node-Level Sparse Linear Algebra Library for HPC (Poster)
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(699 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)
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