Publications
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Distributed Dense Numerical Linear Algebra Algorithms on Massively Parallel Architectures: DPLASMA,”
University of Tennessee Computer Science Technical Report, UT-CS-10-660, September 2010.
(366.26 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)
“Design of an Interactive Environment for Numerically Intensive Parallel Linear Algebra Calculations,”
International Conference on Computational Science, Poland, Springer Verlag, June 2004.
DOI: 10.1007/978-3-540-25944-2_35 (88.31 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)
“Design and Implementation of a Large Scale Tree-Based QR Decomposition Using a 3D Virtual Systolic Array and a Lightweight Runtime,”
Workshop on Large-Scale Parallel Processing, IPDPS 2014, Phoenix, AZ, IEEE, May 2014.
(398.16 KB)
“Dense Linear Algebra on Distributed Heterogeneous Hardware with a Symbolic DAG Approach,”
Scalable Computing and Communications: Theory and Practice: John Wiley & Sons, pp. 699-735, March 2013.
(1.01 MB)
“Dense Linear Algebra on Accelerated Multicore Hardware,”
High Performance Scientific Computing: Algorithms and Applications, London, UK, Springer-Verlag, 00 2012.
“DARPA's HPCS Program: History, Models, Tools, Languages,”
in Advances in Computers, vol. 72: Elsevier, January 2008.
(3.61 MB)
“Cray X1 Evaluation Status Report,”
Oak Ridge National Laboratory Report, vol. /-2004/13, January 2004.
(817.33 KB)
“CPU-GPU Hybrid Bidiagonal Reduction With Soft Error Resilience,”
ScalA '13 Proceedings of the Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Montpellier, France, November 2013.
(238.58 KB)
“A Comprehensive Study of Task Coalescing for Selecting Parallelism Granularity in a Two-Stage Bidiagonal Reduction,”
IPDPS 2012, Shanghai, China, May 2012.
(480.43 KB)
“Comparing performance of s-step and pipelined GMRES on distributed-memory multicore CPUs
, Pittsburgh, Pennsylvania, SIAM Annual Meeting, July 2017.
(748 KB)
Communication Avoiding 2D Stencil Implementations over PaRSEC Task-Based Runtime,”
2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), New Orleans, LA, IEEE, May 2020.
DOI: 10.1109/IPDPSW50202.2020.00127 (1.33 MB)
“A Collection of White Papers from the BDEC2 Workshop in Poznan, Poland,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-19-10: University of Tennessee, Knoxville, May 2019.
(5.82 MB)
“Clover: Computational Libraries Optimized via Exascale Research
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(872 KB)
clMAGMA: High Performance Dense Linear Algebra with OpenCL,”
University of Tennessee Technical Report (Lawn 275), no. UT-CS-13-706: University of Tennessee, March 2013.
(526.6 KB)
“clMAGMA: High Performance Dense Linear Algebra with OpenCL ,”
International Workshop on OpenCL, Bristol University, England, May 2014.
(460.91 KB)
“CholeskyQR with Randomization and Pivoting for Tall Matrices (CQRRPT)
: arXiv, February 2024.
Cholesky Across Accelerators,”
17th IEEE International Conference on High Performance Computing and Communications (HPCC 2015), Elizabeth, NJ, IEEE, August 2015.
“Changes in Dense Linear Algebra Kernels - Decades Long Perspective,”
in Solving the Schrodinger Equation: Has everything been tried? (to appear): Imperial College Press, 00 2011.
“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)
“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)
“C++ API for Batch BLAS,”
SLATE Working Notes, no. 04, ICL-UT-17-12: University of Tennessee, December 2017.
(1.89 MB)
“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)
“BlackjackBench: Portable Hardware Characterization with Automated Results Analysis,”
The Computer Journal, March 2013.
DOI: 10.1093/comjnl/bxt057 (408.45 KB)
“BlackjackBench: Hardware Characterization with Portable Micro-Benchmarks and Automatic Statistical Analysis of Results,”
IEEE International Parallel and Distributed Processing Symposium (submitted), Anchorage, AK, May 2011.
“Batched matrix computations on hardware accelerators based on GPUs,”
International Journal of High Performance Computing Applications, February 2015.
DOI: 10.1177/1094342014567546 (2.16 MB)
“Batched Matrix Computations on Hardware Accelerators,”
EuroMPI/Asia 2015 Workshop, Bordeaux, France, September 2015.
(589.05 KB)
“Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification
, July 2018.
(483.05 KB)
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)
“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 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
“Anatomy of a Globally Recursive Embedded LINPACK Benchmark,”
2012 IEEE High Performance Extreme Computing Conference, Waltham, MA, pp. 1-6, September 2012.
DOI: 10.1109/HPEC.2012.6408679 (204.74 KB)
“Analysis of Various Scalar, Vector, and Parallel Implementations of RandomAccess,”
Innovative Computing Laboratory (ICL) Technical Report, no. ICL-UT-10-03, June 2010.
(226.9 KB)
“Analysis of the Communication and Computation Cost of FFT Libraries towards Exascale,”
ICL Technical Report, no. ICL-UT-22-07: Innovative Computing Laboratory, July 2022.
(5.91 MB)
“On Algorithmic Variants of Parallel Gaussian Elimination: Comparison of Implementations in Terms of Performance and Numerical Properties,”
University of Tennessee Computer Science Technical Report, no. UT-CS-13-715, July 2013, 2012.
(358.98 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)
“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)
“Acceleration of GPU-based Krylov solvers via Data Transfer Reduction,”
International Journal of High Performance Computing Applications, 2015.
“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)
“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)
“Accelerating Numerical Dense Linear Algebra Calculations with GPUs,”
Numerical Computations with GPUs: Springer International Publishing, pp. 3-28, 2014.
DOI: 10.1007/978-3-319-06548-9_1 (1.06 MB)
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