Publications
Accelerating Geostatistical Modeling and Prediction With Mixed-Precision Computations: A High-Productivity Approach With PaRSEC,”
IEEE Transactions on Parallel and Distributed Systems, vol. 33, issue 4, pp. 964 - 976, April 2022.
DOI: 10.1109/TPDS.2021.3084071
“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)
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Algorithms and Optimization Techniques for High-Performance Matrix-Matrix Multiplications of Very Small Matrices,”
Parallel Computing, vol. 81, pp. 1–21, January 2019.
DOI: 10.1016/j.parco.2018.10.003
(3.27 MB)
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Analysis and Design Techniques towards High-Performance and Energy-Efficient Dense Linear Solvers on GPUs,”
IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 12, pp. 2700–2712, December 2018.
DOI: 10.1109/TPDS.2018.2842785
(2.53 MB)
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Argobots: A Lightweight Low-Level Threading and Tasking Framework,”
IEEE Transactions on Parallel and Distributed Systems, October 2017.
DOI: 10.1109/TPDS.2017.2766062
“Batched One-Sided Factorizations of Tiny Matrices Using GPUs: Challenges and Countermeasures,”
Journal of Computational Science, vol. 26, pp. 226–236, May 2018.
DOI: 10.1016/j.jocs.2018.01.005
(3.73 MB)
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Batched sparse and mixed-precision linear algebra interface for efficient use of GPU hardware accelerators in scientific applications,”
Future Generation Computer Systems, vol. 160, pp. 359 - 374, November 2024.
DOI: 10.1016/j.future.2024.06.004
“Batched sparse and mixed-precision linear algebra interface for efficient use of GPU hardware accelerators in scientific applications,”
Future Generation Computer Systems, vol. 160, pp. 359 - 374, November 2024.
DOI: 10.1016/j.future.2024.06.004
“Big Data and Extreme-Scale Computing: Pathways to Convergence - Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry,”
The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 435–479, July 2018.
DOI: 10.1177/1094342018778123
(1.29 MB)
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Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems,”
ICCS 2012, Omaha, NE, June 2012.
(608.95 KB)
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A Block-Asynchronous Relaxation Method for Graphics Processing Units,”
Journal of Parallel and Distributed Computing, vol. 73, issue 12, pp. 1613–1626, December 2013.
DOI: http://dx.doi.org/10.1016/j.jpdc.2013.05.008
(1.08 MB)
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Checkpointing Strategies for Shared High-Performance Computing Platforms,”
International Journal of Networking and Computing, vol. 9, no. 1, pp. 28–52, 2019.
(490.5 KB)
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Compressed basis GMRES on high-performance graphics processing units,”
The International Journal of High Performance Computing Applications, May 2022.
DOI: 10.1177/10943420221115140
(13.52 MB)
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Compressed basis GMRES on high-performance graphics processing units,”
The International Journal of High Performance Computing Applications, May 2022.
DOI: 10.1177/10943420221115140
(13.52 MB)
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Compression and load balancing for efficient sparse matrix‐vector product on multicore processors and graphics processing units,”
Concurrency and Computation: Practice and Experience, vol. 34, issue 14, June 2022.
DOI: 10.1002/cpe.6515
(749.82 KB)
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Compression and load balancing for efficient sparse matrix‐vector product on multicore processors and graphics processing units,”
Concurrency and Computation: Practice and Experience, vol. 34, issue 14, June 2022.
DOI: 10.1002/cpe.6515
(749.82 KB)
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Co-Scheduling Amdhal Applications on Cache-Partitioned Systems,”
International Journal of High Performance Computing Applications, vol. 32, issue 1, pp. 123–138, January 2018.
DOI: 10.1177/1094342017710806
(672.52 KB)
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Co-Scheduling HPC Workloads on Cache-Partitioned CMP Platforms,”
International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1221-1239, November 2019.
DOI: 10.1177/1094342019846956
(930.28 KB)
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A Customized Precision Format Based on Mantissa Segmentation for Accelerating Sparse Linear Algebra,”
Concurrency and Computation: Practice and Experience, vol. 40319, issue 262, January 2019.
DOI: 10.1002/cpe.5418
“Efficient exascale discretizations: High-order finite element methods,”
The International Journal of High Performance Computing Applications, pp. 10943420211020803, 2021.
DOI: 10.1177/10943420211020803
“Enhancing Parallelism of Tile QR Factorization for Multicore Architectures,”
Submitted to Transaction on Parallel and Distributed Systems, December 2009.
(464.23 KB)
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Evaluating Asynchronous Schwarz Solvers on GPUs,”
International Journal of High Performance Computing Applications, August 2020.
DOI: 10.1177/1094342020946814
“Evolution of the computational science community: The dynamics of topics and collaborations in 24 years of ICCS and JoCS publications,”
Journal of Computational Science, vol. 89, July 2025.
DOI: 10.1016/j.jocs.2025.102609
“Evolution of the SLATE linear algebra library,”
The International Journal of High Performance Computing Applications, September 2024.
DOI: 10.1177/10943420241286531
“Evolution of the SLATE linear algebra library,”
The International Journal of High Performance Computing Applications, September 2024.
DOI: 10.1177/10943420241286531
“Evolution of the SLATE linear algebra library,”
The International Journal of High Performance Computing Applications, September 2024.
DOI: 10.1177/10943420241286531
“Factorization and Inversion of a Million Matrices using GPUs: Challenges and Countermeasures,”
Procedia Computer Science, vol. 108, pp. 606–615, June 2017.
DOI: 10.1016/j.procs.2017.05.250
(643.44 KB)
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Fast Cholesky Factorization on GPUs for Batch and Native Modes in MAGMA,”
Journal of Computational Science, vol. 20, pp. 85–93, May 2017.
DOI: 10.1016/j.jocs.2016.12.009
(3.6 MB)
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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)
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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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Ginkgo - A math library designed to accelerate Exascale Computing Project science applications,”
The International Journal of High Performance Computing Applications, August 2024.
DOI: 10.1177/10943420241268323
“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)
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Ginkgo—A math library designed for platform portability,”
Parallel Computing, vol. 111, pp. 102902, February 2022.
DOI: 10.1016/j.parco.2022.102902
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