Publications
A Set of Batched Basic Linear Algebra Subprograms,”
ACM Transactions on Mathematical Software, October 2020.
“SLATE: Software for Linear Algebra Targeting Exascale (POSTER)
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(546.56 KB)
SLATE Tutorial
, Houston, TX, 2020 ECP Annual Meeting, February 2020.
(12.14 MB)
SLATE Users' Guide,”
SLATE Working Notes, no. 10, ICL-UT-19-01: Innovative Computing Laboratory, University of Tennessee, July 2020.
(1.51 MB)
“An Empirical View of SLATE Algorithms on Scalable Hybrid System,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-19-08: University of Tennessee, Knoxville, September 2019.
(441.16 KB)
“Least Squares Solvers for Distributed-Memory Machines with GPU Accelerators,”
ACM International Conference on Supercomputing (ICS '19), Phoenix, Arizona, ACM, pp. 117–126, June 2019.
DOI: https://dl.acm.org/doi/abs/10.1145/3330345.3330356 (1.63 MB)
“Massively Parallel Automated Software Tuning,”
48th International Conference on Parallel Processing (ICPP 2019), Kyoto, Japan, ACM Press, August 2019.
DOI: 10.1145/3337821.3337908 (911.88 KB)
“PLASMA: Parallel Linear Algebra Software for Multicore Using OpenMP,”
ACM Transactions on Mathematical Software, vol. 45, issue 2, June 2019.
DOI: 10.1145/3264491 (7.5 MB)
“SLATE: Design of a Modern Distributed and Accelerated Linear Algebra Library
, Denver, CO, International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), November 2019.
(16.19 MB)
SLATE: Design of a Modern Distributed and Accelerated Linear Algebra Library,”
International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Denver, CO, ACM, November 2019.
DOI: 10.1145/3295500.3356223 (2.01 MB)
“SLATE Developers' Guide,”
SLATE Working Notes, no. 11, ICL-UT-19-02: Innovative Computing Laboratory, University of Tennessee, December 2019.
(1.68 MB)
“SLATE Mixed Precision Performance Report,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-19-03: University of Tennessee, April 2019.
(1.04 MB)
“SLATE Working Note 12: Implementing Matrix Inversions,”
SLATE Working Notes, no. 12, ICL-UT-19-04: Innovative Computing Laboratory, University of Tennessee, June 2019.
(1.95 MB)
“SLATE Working Note 13: Implementing Singular Value and Symmetric/Hermitian Eigenvalue Solvers,”
SLATE Working Notes, no. 13, ICL-UT-19-07: Innovative Computing Laboratory, University of Tennessee, September 2019.
(3.47 MB)
“Autotuning Numerical Dense Linear Algebra for Batched Computation With GPU Hardware Accelerators,”
Proceedings of the IEEE, vol. 106, issue 11, pp. 2040–2055, November 2018.
DOI: 10.1109/JPROC.2018.2868961 (2.53 MB)
“Autotuning Techniques for Performance-Portable Point Set Registration in 3D,”
Supercomputing Frontiers and Innovations, vol. 5, no. 4, December 2018.
DOI: 10.14529/jsfi180404 (720.15 KB)
“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)
“Least Squares Performance Report,”
SLATE Working Notes, no. 09, ICL-UT-18-10: Innovative Computing Laboratory, University of Tennessee, December 2018.
(1.76 MB)
“Linear Systems Performance Report,”
SLATE Working Notes, no. 08, ICL-UT-18-08: Innovative Computing Laboratory, University of Tennessee, September 2018.
(1.64 MB)
“Parallel BLAS Performance Report,”
SLATE Working Notes, no. 05, ICL-UT-18-01: University of Tennessee, April 2018.
(4.39 MB)
“Parallel Norms Performance Report,”
SLATE Working Notes, no. 06, ICL-UT-18-06: Innovative Computing Laboratory, University of Tennessee, June 2018.
(1.13 MB)
“The Singular Value Decomposition: Anatomy of Optimizing an Algorithm for Extreme Scale,”
SIAM Review, vol. 60, issue 4, pp. 808–865, November 2018.
DOI: 10.1137/17M1117732 (2.5 MB)
“Symmetric Indefinite Linear Solver using OpenMP Task on Multicore Architectures,”
IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 8, pp. 1879–1892, August 2018.
DOI: 10.1109/TPDS.2018.2808964 (2.88 MB)
“Task Based Cholesky Decomposition on Xeon Phi Architectures using OpenMP,”
International Journal of Computational Science and Engineering (IJCSE), vol. 17, no. 3, October 2018.
DOI: http://dx.doi.org/10.1504/IJCSE.2018.095851
“Autotuning Batch Cholesky Factorization in CUDA with Interleaved Layout of Matrices,”
Parallel and Distributed Processing Symposium Workshops (IPDPSW), Orlando, FL, IEEE, June 2017.
DOI: 10.1109/IPDPSW.2017.18
“Bringing High Performance Computing to Big Data Algorithms,”
Handbook of Big Data Technologies: Springer, 2017.
DOI: 10.1007/978-3-319-49340-4 (1.22 MB)
“C++ API for Batch BLAS,”
SLATE Working Notes, no. 04, ICL-UT-17-12: University of Tennessee, December 2017.
(1.89 MB)
“C++ API for BLAS and LAPACK,”
SLATE Working Notes, no. 02, ICL-UT-17-03: Innovative Computing Laboratory, University of Tennessee, June 2017.
(1.12 MB)
“The Case for Directive Programming for Accelerator Autotuner Optimization,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-17-07: University of Tennessee, October 2017.
(341.52 KB)
“Design and Implementation of the PULSAR Programming System for Large Scale Computing,”
Supercomputing Frontiers and Innovations, vol. 4, issue 1, 2017.
DOI: 10.14529/jsfi170101 (764.96 KB)
“Designing SLATE: Software for Linear Algebra Targeting Exascale,”
SLATE Working Notes, no. 03, ICL-UT-17-06: Innovative Computing Laboratory, University of Tennessee, October 2017.
(2.8 MB)
“PLASMA 17 Performance Report,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-17-11: University of Tennessee, June 2017.
(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)
“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)
“Scaling Point Set Registration in 3D Across Thread Counts on Multicore and Hardware Accelerator Platforms through Autotuning for Large Scale Analysis of Scientific Point Clouds,”
IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2017), Boston, MA, IEEE, December 2017.
DOI: 10.1109/BigData.2017.8258258 (6.71 MB)
“Towards Numerical Benchmark for Half-Precision Floating Point Arithmetic,”
2017 IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, IEEE, September 2017.
DOI: 10.1109/HPEC.2017.8091031 (1.67 MB)
“With Extreme Computing, the Rules Have Changed,”
Computing in Science & Engineering, vol. 19, issue 3, pp. 52-62, May 2017.
DOI: 10.1109/MCSE.2017.48 (485.34 KB)
“Linear Algebra Software for Large-Scale Accelerated Multicore Computing,”
Acta Numerica, vol. 25, pp. 1-160, May 2016.
DOI: 10.1017/S0962492916000015
“Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems,”
Supercomputing Frontiers and Innovations, vol. 2, no. 4, October 2015.
DOI: 10.14529/jsfi1504 (3.68 MB)
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