Publications
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Performance, Design, and Autotuning of Batched GEMM for GPUs,”
The International Supercomputing Conference (ISC High Performance 2016), Frankfurt, Germany, June 2016.
(1.27 MB)
“A Set of Batched Basic Linear Algebra Subprograms and LAPACK Routines,”
ACM Transactions on Mathematical Software (TOMS), vol. 47, no. 3, pp. 1–23, 2021.
“Factorization and Inversion of a Million Matrices using GPUs: Challenges and Countermeasures,”
Procedia Computer Science, vol. 108, pp. 606–615, June 2017.
(643.44 KB)
“High-Performance Tensor Contractions for GPUs,”
University of Tennessee Computer Science Technical Report, no. UT-EECS-16-738: University of Tennessee, January 2016.
(2.36 MB)
“Addressing Irregular Patterns of Matrix Computations on GPUs and Their Impact on Applications Powered by Sparse Direct Solvers,”
2022 International Conference for High Performance Computing, Networking, Storage and Analysis (SC22), Dallas, TX, IEEE Computer Society, pp. 354-367, November 2022.
(1.57 MB)
“A survey of numerical linear algebra methods utilizing mixed-precision arithmetic,”
The International Journal of High Performance Computing Applications, vol. 35, no. 4, pp. 344–369, 2021.
“Performance Tuning and Optimization Techniques of Fixed and Variable Size Batched Cholesky Factorization on GPUs,”
International Conference on Computational Science (ICCS'16), San Diego, CA, June 2016.
(626.21 KB)
“Cholesky Factorization on Batches of Matrices with Fixed and Variable Sizes
, San Jose, CA, GPU Technology Conference (GTC16), Poster, April 2016.
(480.51 KB)
GPU-based LU Factorization and Solve on Batches of Matrices with Band Structure,”
SC-W 2023: Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, CO, ACM, November 2023.
“Fast Cholesky Factorization on GPUs for Batch and Native Modes in MAGMA,”
Journal of Computational Science, vol. 20, pp. 85–93, May 2017.
(3.6 MB)
“Matrix Multiplication on Batches of Small Matrices in Half and Half-Complex Precisions,”
Journal of Parallel and Distributed Computing, vol. 145, pp. 188-201, November 2020.
(1.3 MB)
“MATEDOR: MAtrix, TEnsor, and Deep-learning Optimized Routines
, Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Research Poster, November 2018.
(2.55 MB)
Optimizing Memory-Bound Numerical Kernels on GPU Hardware Accelerators,”
VECPAR 2012, Kobe, Japan, July 2012.
(737.28 KB)
“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)
“Tensor Contractions using Optimized Batch GEMM Routines
, San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.
(1.64 MB)
Linear Algebra Software for Large-Scale Accelerated Multicore Computing,”
Acta Numerica, vol. 25, pp. 1-160, May 2016.
“Progressive Optimization of Batched LU Factorization on GPUs,”
IEEE High Performance Extreme Computing Conference (HPEC’19), Waltham, MA, IEEE, September 2019.
(299.38 KB)
“High-Performance Tensor Contractions for GPUs,”
International Conference on Computational Science (ICCS'16), San Diego, CA, June 2016.
(2.36 MB)
“A Set of Batched Basic Linear Algebra Subprograms,”
ACM Transactions on Mathematical Software, October 2020.
“Optimizing GPU Kernels for Irregular Batch Workloads: A Case Study for Cholesky Factorization,”
IEEE High Performance Extreme Computing Conference (HPEC’18), Waltham, MA, IEEE, September 2018.
(729.87 KB)
“GPU algorithms for Efficient Exascale Discretizations,”
Parallel Computing, vol. 108, pp. 102841, 2021.
“Novel HPC Techniques to Batch Execution of Many Variable Size BLAS Computations on GPUs,”
International Conference on Supercomputing (ICS '17), Chicago, Illinois, ACM, June 2017.
(1.04 MB)
“SLATE Port to AMD and Intel Platforms,”
SLATE Working Notes, no. 16, ICL-UT-21-01, April 2021.
(890.75 KB)
“Optimizing Batch HGEMM on Small Sizes Using Tensor Cores
, San Jose, CA, GPU Technology Conference (GTC), March 2019.
(2.47 MB)
Batched One-Sided Factorizations of Tiny Matrices Using GPUs: Challenges and Countermeasures,”
Journal of Computational Science, vol. 26, pp. 226–236, May 2018.
(3.73 MB)
“PLASMA 17 Performance Report,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-17-11: University of Tennessee, June 2017.
(7.57 MB)
“Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems,”
Supercomputing Frontiers and Innovations, vol. 2, no. 4, October 2015.
(3.68 MB)
“PLASMA 17.1 Functionality Report,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-17-10: University of Tennessee, June 2017.
(1.8 MB)
“The Future of Supercomputing: An Interim Report,”
National Research Council, Washington, D.C., The National Academies Press, January 2003.
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