Publications
“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)
“ADAPT: An Event-Based Adaptive Collective Communication Framework,”
The 27th International Symposium on High-Performance Parallel and Distributed Computing (HPDC '18), Tempe, Arizona, ACM Press, June 2018.
DOI: 10.1145/3208040.3208054 (493.65 KB)
(493.65 KB)
“Achieving Numerical Accuracy and High Performance using Recursive Tile LU Factorization,”
University of Tennessee Computer Science Technical Report (also as a LAWN), no. ICL-UT-11-08, September 2011.
(618.53 KB)
(618.53 KB)
“Achieving numerical accuracy and high performance using recursive tile LU factorization with partial pivoting,”
Concurrency and Computation: Practice and Experience, vol. 26, issue 7, pp. 1408-1431, May 2014.
DOI: 10.1002/cpe.3110 (1.96 MB)
(1.96 MB)
“Accurate Cache and TLB Characterization Using Hardware Counters,”
International Conference on Computational Science (ICCS 2004), Krakow, Poland, Springer, June 2004.
DOI: 10.1007/978-3-540-24688-6_57 (167.1 KB)
(167.1 KB)
“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 the Reduction to Upper Hessenberg Form through Hybrid GPU-Based Computing,”
University of Tennessee Computer Science Technical Report, UT-CS-09-642 (also LAPACK Working Note 219), May 2009.
(2.37 MB)
(2.37 MB)
Accelerating Tensor Contractions in High-Order FEM with MAGMA Batched
, Atlanta, GA, SIAM Conference on Computer Science and Engineering (SIAM CSE17), Presentation, March 2017.
(9.29 MB)
(9.29 MB)
Accelerating Tensor Contractions for High-Order FEM on CPUs, GPUs, and KNLs
, Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC16), Poster, September 2016.
(4.29 MB)
(4.29 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 Restarted GMRES with Mixed Precision Arithmetic,”
IEEE Transactions on Parallel and Distributed Systems, June 2021.
DOI: 10.1109/TPDS.2021.3090757 (572.4 KB)
(572.4 KB)
“Accelerating NWChem Coupled Cluster through dataflow-based Execution,”
11th International Conference on Parallel Processing and Applied Mathematics (PPAM 2015), Krakow, Poland, Springer International Publishing, September 2015.
(452.82 KB)
(452.82 KB)
“Accelerating NWChem Coupled Cluster through Dataflow-Based Execution,”
The International Journal of High Performance Computing Applications, pp. 1–13, January 2017.
DOI: 10.1177/1094342016672543 (4.07 MB)
(4.07 MB)
“Accelerating NWChem Coupled Cluster through dataflow-based Execution,”
The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 540--551, July 2018.
DOI: 10.1177/1094342016672543 (1.68 MB)
(1.68 MB)
“Accelerating Multi - Process Communication for Parallel 3-D FFT,”
2021 Workshop on Exascale MPI (ExaMPI), St. Louis, MO, USA, IEEE, December 2021.
DOI: 10.1109/ExaMPI54564.2021.00011
“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 Linear Algebra with MAGMA
, Knoxville, TN, ECP Annual Meeting 2018, Tutorial, February 2018.
(35.27 MB)
(35.27 MB)
Accelerating Linear Algebra on Heterogeneous Architectures of Multicore and GPUs using MAGMA and DPLASMA and StarPU Schedulers
: 2010 Symposium on Application Accelerators in. High-Performance Computing (SAAHPC'10), Tutorial, July 2010.
(499.51 KB)
(499.51 KB)
“Accelerating GPU Kernels for Dense Linear Algebra,”
Proc. of VECPAR'10, Berkeley, CA, June 2010.
(615.07 KB)
(615.07 KB)
“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
“Accelerating Fusion Plasma Collision Operator Solves with Portable Batched Iterative Solvers on GPUs,”
ISC High Performance 2024 International Workshops , vol. 15058, Hamburg, Germany, Springer, Cham, pp. 127 - 140, December 2024.
DOI: 10.1007/978-3-031-73716-9
Accelerating FFT towards Exascale Computing
: NVIDIA GPU Technology Conference (GTC2021), 2021.
(27.23 MB)
(27.23 MB)
Accelerating 2D FFT: Exploit GPU Tensor Cores through Mixed-Precision
, Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), ACM Student Research Poster, November 2018.
(740.37 KB)
(740.37 KB)
“The 30th Anniversary of the Supercomputing Conference: Bringing the Future Closer—Supercomputing History and the Immortality of Now,”
Computer, vol. 51, issue 10, pp. 74–85, November 2018.
DOI: 10.1109/MC.2018.3971352 (1.73 MB)
(1.73 MB)
“2016 Dense Linear Algebra Software Packages Survey,”
University of Tennessee Computer Science Technical Report, no. UT-EECS-16-744 / LAWN 290: University of Tennessee, September 2016.
(366.43 KB)
(366.43 KB)
“20 years of computational science: Selected papers from 2020 International Conference on Computational Science,”
Journal of Computational Science, vol. 53, pp. 101395–101395, 2021.
DOI: 10.1016/j.jocs.2021.101395
