Publications
“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)
(3.6 MB)
“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)
(643.44 KB)
“Exploiting Block Structures of KKT Matrices for Efficient Solution of Convex Optimization Problems,”
IEEE Access, 2021.
DOI: 10.1109/ACCESS.2021.3106054 (1.35 MB)
(1.35 MB)
“Evaluation of Directive-Based Performance Portable Programming Models,”
International Journal of High Performance Computing and Networking, vol. 14, issue 2, pp. 165-182.
DOI: http://dx.doi.org/10.1504/IJHPCN.2017.10009064 (1.12 MB)
(1.12 MB)
“Efficient exascale discretizations: High-order finite element methods,”
The International Journal of High Performance Computing Applications, pp. 10943420211020803, 2021.
DOI: 10.1177/10943420211020803
“Divide & Conquer on Hybrid GPU-Accelerated Multicore Systems,”
SIAM Journal on Scientific Computing (submitted), August 2010.
“Divide and Conquer on Hybrid GPU-Accelerated Multicore Systems,”
SIAM Journal on Scientific Computing, vol. 34(2), pp. C70-C82, April 2012.
“Computational Benefit of GPU Optimization for Atmospheric Chemistry Modeling,”
Journal of Advances in Modeling Earth Systems, vol. 10, issue 8, pp. 1952–1969, August 2018.
DOI: 10.1029/2018MS001276 (3.4 MB)
(3.4 MB)
“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)
(1.08 MB)
“Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems,”
ICCS 2012, Omaha, NE, June 2012.
(608.95 KB)
(608.95 KB)
“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)
(3.73 MB)
“Autotuning GEMM Kernels for the Fermi GPU,”
IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 11, November 2012.
DOI: 10.1109/TPDS.2011.311 (742.5 KB)
(742.5 KB)
“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)
(2.53 MB)
“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)
(3.27 MB)
“Accelerating the SVD Two Stage Bidiagonal Reduction and Divide and Conquer Using GPUs,”
Parallel Computing, vol. 74, pp. 3–18, May 2018.
DOI: 10.1016/j.parco.2017.10.004 (1.34 MB)
(1.34 MB)
“Accelerating the SVD Bi-Diagonalization of a Batch of Small Matrices using GPUs,”
Journal of Computational Science, vol. 26, pp. 237–245, May 2018.
DOI: 10.1016/j.jocs.2018.01.007 (2.18 MB)
(2.18 MB)
“Accelerating the Reduction to Upper Hessenberg, Tridiagonal, and Bidiagonal Forms through Hybrid GPU-Based Computing,”
Parallel Computing, vol. 36, no. 12, pp. 645-654, 00 2010.
(1.39 MB)
(1.39 MB)
“Accelerating Scientific Computations with Mixed Precision Algorithms,”
Computer Physics Communications, vol. 180, issue 12, pp. 2526-2533, December 2009.
DOI: 10.1016/j.cpc.2008.11.005 (402.69 KB)
(402.69 KB)
“Accelerating Linear System Solutions Using Randomization Techniques,”
ACM Transactions on Mathematical Software (also LAWN 246), vol. 39, issue 2, February 2013.
DOI: 10.1145/2427023.2427025 (358.79 KB)
(358.79 KB)
“Accelerating GPU Kernels for Dense Linear Algebra,”
Proc. of VECPAR'10, Berkeley, CA, June 2010.
(615.07 KB)
(615.07 KB)
“Some Issues in Dense Linear Algebra for Multicore and Special Purpose Architectures,”
PARA 2008, 9th International Workshop on State-of-the-Art in Scientific and Parallel Computing, Trondheim Norway, May 2008.
“Scalability Issues in FFT Computation,”
International Conference on Parallel Computing Technologies: Springer, pp. 279–287, 2021.
DOI: 10.1007/978-3-030-86359-3_21
“QR Factorization on a Multicore Node Enhanced with Multiple GPU Accelerators,”
Proceedings of IPDPS 2011, no. ICL-UT-10-04, Anchorage, AK, October 2010.
(468.17 KB)
(468.17 KB)
“Optimizing Symmetric Dense Matrix-Vector Multiplication on GPUs,”
ACM/IEEE Conference on Supercomputing (SC’11), Seattle, WA, November 2011.
(630.63 KB)
(630.63 KB)
“One-Sided Dense Matrix Factorizations on a Multicore with Multiple GPU Accelerators,”
The International Conference on Computational Science (ICCS), June 2012.
“Numerical Linear Algebra on Emerging Architectures: The PLASMA and MAGMA Projects,”
Journal of Physics: Conference Series, vol. 180, 00 2009.
(119.37 KB)
(119.37 KB)
“A Note on Auto-tuning GEMM for GPUs,”
9th International Conference on Computational Science (ICCS 2009), no. 5544-5545, Baton Rouge, LA, pp. 884-892, May 2009.
DOI: 10.1007/978-3-642-01970-8_89 (236.02 KB)
(236.02 KB)
“Mixed-Tool Performance Analysis on Hybrid Multicore Architectures,”
First International Workshop on Parallel Software Tools and Tool Infrastructures (PSTI 2010), San Diego, CA, September 2010.
(1.24 MB)
(1.24 MB)
“Lossy all-to-all exchange for accelerating parallel 3-D FFTs on hybrid architectures with GPUs,”
2022 IEEE International Conference on Cluster Computing (CLUSTER), pp. 152-160, September 2022.
DOI: 10.1109/CLUSTER51413.2022.00029
“Exploring New Architectures in Accelerating CFD for Air Force Applications,”
Proceedings of the DoD HPCMP User Group Conference, Seattle, Washington, January 2008.
(492.86 KB)
(492.86 KB)
“Enabling and Scaling Matrix Computations on Heterogeneous Multi-Core and Multi-GPU Systems,”
26th ACM International Conference on Supercomputing (ICS 2012), San Servolo Island, Venice, Italy, ACM, June 2012.
(5.88 MB)
(5.88 MB)
