Publications
“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)
(299.38 KB)
“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)
(3.73 MB)
“Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs,”
Concurrency and Computation: Practice and Experience, vol. 28, issue 12, pp. 3447 - 3465, May 2016.
(3.21 MB)
(3.21 MB)
“On the Development of Variable Size Batched Computation for Heterogeneous Parallel Architectures,”
The 17th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC 2016), IPDPS 2016, Chicago, IL, IEEE, May 2016.
(708.62 KB)
(708.62 KB)
“Performance, Design, and Autotuning of Batched GEMM for GPUs,”
High Performance Computing: 31st International Conference, ISC High Performance 2016, Frankfurt, Germany, June 19-23, 2016, Proceedings, no. 9697: Springer International Publishing, pp. 21–38, 2016.
(1.98 MB)
(1.98 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)
(3.98 MB)
“Investigating the Benefit of FP16-Enabled Mixed-Precision Solvers for Symmetric Positive Definite Matrices using GPUs,”
International Conference on Computational Science (ICCS 2020), Amsterdam, Netherlands, Springer, Cham, June 2020.
(702.38 KB)
(702.38 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.
(2.53 MB)
(2.53 MB)
Optimizing Batch HGEMM on Small Sizes Using Tensor Cores
, San Jose, CA, GPU Technology Conference (GTC), March 2019.
(2.47 MB)
(2.47 MB)
“Performance, Design, and Autotuning of Batched GEMM for GPUs,”
University of Tennessee Computer Science Technical Report, no. UT-EECS-16-739: University of Tennessee, February 2016.
(1.27 MB)
(1.27 MB)
“Performance, Design, and Autotuning of Batched GEMM for GPUs,”
The International Supercomputing Conference (ISC High Performance 2016), Frankfurt, Germany, June 2016.
(1.27 MB)
(1.27 MB)
“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)
(2.36 MB)
“C++ API for Batch BLAS,”
SLATE Working Notes, no. 04, ICL-UT-17-12: University of Tennessee, December 2017.
(1.89 MB)
(1.89 MB)
“Towards Half-Precision Computation for Complex Matrices: A Case Study for Mixed Precision Solvers on GPUs,”
ScalA19: 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, IEEE, November 2019.
(523.87 KB) (3.42 MB)
(523.87 KB) (3.42 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)
(1.57 MB)
“Fast Batched Matrix Multiplication for Small Sizes using Half Precision Arithmetic on GPUs,”
33rd IEEE International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, IEEE, May 2019.
(675.5 KB)
(675.5 KB)
“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.
“Implementation of the C++ API for Batch BLAS,”
SLATE Working Notes, no. 07, ICL-UT-18-04: Innovative Computing Laboratory, University of Tennessee, June 2018.
(1.07 MB)
(1.07 MB)
“Small Tensor Operations on Advanced Architectures for High-Order Applications,”
University of Tennessee Computer Science Technical Report, no. UT-EECS-17-749: Innovative Computing Laboratory, University of Tennessee, April 2017.
(1.09 MB)
(1.09 MB)
“Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems,”
Supercomputing Frontiers and Innovations, vol. 2, no. 4, October 2015.
(3.68 MB)
(3.68 MB)
“PLASMA 17 Performance Report,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-17-11: University of Tennessee, June 2017.
(7.57 MB)
(7.57 MB)
“PLASMA 17.1 Functionality Report,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-17-10: University of Tennessee, June 2017.
(1.8 MB)
(1.8 MB)
“The Future of Supercomputing: An Interim Report,”
National Research Council, Washington, D.C., The National Academies Press, January 2003.
