Publications
Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems,”
ICCS 2012, Omaha, NE, June 2012.
(608.95 KB)
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GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement,”
EuroPar 2012 (also LAWN 260), Rhodes Island, Greece, August 2012.
(662.98 KB)
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A Block-Asynchronous Relaxation Method for Graphics Processing Units,”
Journal of Parallel and Distributed Computing, vol. 73, issue 12, pp. 1613–1626, December 2013.
DOI: http://dx.doi.org/10.1016/j.jpdc.2013.05.008
(1.08 MB)
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Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures,”
VECPAR 2014, Eugene, OR, June 2014.
(430.56 KB)
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MAGMA MIC: Optimizing Linear Algebra for Intel Xeon Phi
, Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, June 2015.
(2.03 MB)

Fine-grained Bit-Flip Protection for Relaxation Methods,”
Journal of Computational Science, November 2016.
DOI: 10.1016/j.jocs.2016.11.013
(1.47 MB)
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Heterogeneous Streaming,”
The Sixth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), IPDPS 2016, Chicago, IL, IEEE, May 2016.
(2.73 MB)
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Linear Algebra Software for Large-Scale Accelerated Multicore Computing,”
Acta Numerica, vol. 25, pp. 1-160, May 2016.
DOI: 10.1017/S0962492916000015
“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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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)
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Flexible Batched Sparse Matrix Vector Product on GPUs
, Denver, Colorado, ScalA'17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, November 2017.
(16.8 MB)

Flexible Batched Sparse Matrix-Vector Product on GPUs,”
8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA '17), Denver, CO, ACM Press, November 2017.
DOI: http://dx.doi.org/10.1145/3148226.3148230
(583.4 KB)
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Preconditioned Krylov Solvers on GPUs,”
Parallel Computing, June 2017.
DOI: 10.1016/j.parco.2017.05.006
(1.19 MB)
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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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Variable-Size Batched Gauss-Huard for Block-Jacobi Preconditioning,”
International Conference on Computational Science (ICCS 2017), vol. 108, Zurich, Switzerland, Procedia Computer Science, pp. 1783-1792, June 2017.
DOI: 10.1016/j.procs.2017.05.186
(512.57 KB)
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Variable-Size Batched LU for Small Matrices and Its Integration into Block-Jacobi Preconditioning,”
46th International Conference on Parallel Processing (ICPP), Bristol, United Kingdom, IEEE, August 2017.
DOI: 10.1109/ICPP.2017.18
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