Publications
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Sampling Algorithms to Update Truncated SVD,”
IEEE International Conference on Big Data, Boston, MA, IEEE, December 2017.
(700.79 KB)
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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)
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Reducing the Amount of out-of-core Data Access for GPU-Accelerated Randomized SVD,”
Concurrency and Computation: Practice and Experience, April 2020.
DOI: 10.1002/cpe.5754
(1.43 MB)
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QR Factorization on a Multicore Node Enhanced with Multiple GPU Accelerators,”
Proceedings of IPDPS 2011, no. ICL-UT-10-04, Anchorage, AK, October 2010.
(468.17 KB)
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A Python Library for Matrix Algebra on GPU and Multicore Architectures,”
2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS), Denver, CO, IEEE, December 2022.
DOI: 10.1109/MASS56207.2022.00121
(414.36 KB)
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Providing GPU Capability to LU and QR within the ScaLAPACK Framework,”
University of Tennessee Computer Science Technical Report (also LAWN 272), no. UT-CS-12-699, September 2012.
(7.48 MB)
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Project-Based Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning,”
The Journal of Computational Science Education, vol. 11, issue 1, pp. 36-44, January 2020.
DOI: 10.22369/issn.2153-4136/11/1/7
(4.4 MB)
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Progressive Optimization of Batched LU Factorization on GPUs,”
IEEE High Performance Extreme Computing Conference (HPEC’19), Waltham, MA, IEEE, September 2019.
(299.38 KB)
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Power-Aware HPC on Intel Xeon Phi KNL Processors
, Frankfurt, Germany, ISC High Performance (ISC17), Intel Booth Presentation, June 2017.
(5.87 MB)

Power-aware Computing on GPGPUs
, Gatlinburg, TN, Fall Creek Falls Conference, Poster, September 2011.
(2.89 MB)

Power-aware Computing: Measurement, Control, and Performance Analysis for Intel Xeon Phi,”
2017 IEEE High Performance Extreme Computing Conference (HPEC'17), Best Paper Finalist, Waltham, MA, IEEE, September 2017.
DOI: 10.1109/HPEC.2017.8091085
(908.84 KB)
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Power Aware Computing on GPUs,”
SAAHPC '12 (Best Paper Award), Argonne, IL, July 2012.
(658.06 KB)
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POMPEI: Programming with OpenMP4 for Exascale Investigations,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-17-09: University of Tennessee, December 2017.
(1.1 MB)
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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)
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Performance Portability of a GPU Enabled Factorization with the DAGuE Framework,”
IEEE Cluster: workshop on Parallel Programming on Accelerator Clusters (PPAC), June 2011.
(290.98 KB)
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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)
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On the performance and energy efficiency of sparse linear algebra on GPUs,”
International Journal of High Performance Computing Applications, October 2016.
DOI: 10.1177/1094342016672081
(1.19 MB)
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Performance Analysis of Parallel FFT on Large Multi-GPU Systems,”
2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Lyon, France, IEEE, August 2022.
DOI: 10.1109/IPDPSW55747.2022.00072
“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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Parallel Performance Measurement of Heterogeneous Parallel Systems with GPUs,”
International Conference on Parallel Processing (ICPP'11), Taipei, Taiwan, ACM, September 2011.
DOI: 10.1109/ICPP.2011.71
(1.41 MB)
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PAQR: Pivoting Avoiding QR factorization,”
ICL Technical Report, no. ICL-UT-22-06, June 2022.
(364.85 KB)
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Out of Memory SVD Solver for Big Data,”
2017 IEEE High Performance Extreme Computing Conference (HPEC'17), Waltham, MA, IEEE, September 2017.
(1.33 MB)
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Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices,”
International Conference on Computational Science (ICCS 2017), Zurich, Switzerland, Procedia Computer Science, June 2017.
DOI: 10.1016/j.procs.2017.05.237
(364.95 KB)
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Optimizing Symmetric Dense Matrix-Vector Multiplication on GPUs,”
ACM/IEEE Conference on Supercomputing (SC’11), Seattle, WA, November 2011.
(630.63 KB)
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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)
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Optimizing Batch HGEMM on Small Sizes Using Tensor Cores
, San Jose, CA, GPU Technology Conference (GTC), March 2019.
(2.47 MB)

OpenDIEL: A Parallel Workflow Engine and DataAnalytics Framework,”
Practice and Experience in Advanced Research Computing (PEARC ’19), Chicago, IL, ACM, July 2019.
(1.48 MB)
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One-Sided Dense Matrix Factorizations on a Multicore with Multiple GPU Accelerators,”
The International Conference on Computational Science (ICCS), June 2012.
“Numerical Linear Algebra on Hybrid Architectures: Recent Developments in the MAGMA Project
, Portland, Oregon, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC09), November 2009.
(1.41 MB)

Numerical Linear Algebra on Emerging Architectures: The PLASMA and MAGMA Projects
, Portland, OR, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC09), November 2009.
(3.53 MB)

Numerical Linear Algebra on Emerging Architectures: The PLASMA and MAGMA Projects,”
Journal of Physics: Conference Series, vol. 180, 00 2009.
(119.37 KB)
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