Publications
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)
(2.55 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.
Tensor Contractions using Optimized Batch GEMM Routines
, San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.
(1.64 MB)
(1.64 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)
“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.
“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)
(3.6 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)
(299.38 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.
“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)
(2.8 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)
(1.3 MB)
“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)
(729.87 KB)
“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)
Optimizing Batch HGEMM on Small Sizes Using Tensor Cores
, San Jose, CA, GPU Technology Conference (GTC), March 2019.
(2.47 MB)
(2.47 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)
“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)
(1.04 MB)
“A Set of Batched Basic Linear Algebra Subprograms,”
ACM Transactions on Mathematical Software, October 2020.
“GPU algorithms for Efficient Exascale Discretizations,”
Parallel Computing, vol. 108, pp. 102841, 2021.
“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)
“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)
“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.
