Publications
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Filters: Author is Dongarra, Jack [Clear All Filters]
High Performance Bidiagonal Reduction using Tile Algorithms on Homogeneous Multicore Architectures,”
University of Tennessee Computer Science Technical Report, UT-CS-11-673, (also Lawn 247), May 2011.
(424.93 KB)
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Hierarchical QR Factorization Algorithms for Multi-Core Cluster Systems,”
University of Tennessee Computer Science Technical Report (also Lawn 257), no. UT-CS-11-684, October 2011.
(405.71 KB)
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Hierarchical QR Factorization Algorithms for Multi-Core Cluster Systems,”
IPDPS 2012, the 26th IEEE International Parallel and Distributed Processing Symposium, Shanghai, China, IEEE Computer Society Press, May 2012.
(405.71 KB)
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Hierarchical QR Factorization Algorithms for Multi-core Cluster Systems,”
Parallel Computing, vol. 39, issue 4-5, pp. 212-232, May 2013.
(1.43 MB)
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Hierarchical DAG scheduling for Hybrid Distributed Systems,”
29th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Hyderabad, India, IEEE, May 2015.
(1.11 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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heFFTe: Highly Efficient FFT for Exascale (Poster)
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(6.2 MB)

heFFTe: Highly Efficient FFT for Exascale (Poster)
, Seattle, WA, SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP20), February 2020.
(1.54 MB)

heFFTe: Highly Efficient FFT for Exascale (Poster)
: NVIDIA GPU Technology Conference (GTC2020), October 2020.
(866.88 KB)

heFFTe: Highly Efficient FFT for Exascale,”
International Conference on Computational Science (ICCS 2020), Amsterdam, Netherlands, June 2020.
DOI: 10.1007/978-3-030-50371-0_19
(2.62 MB)
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Harnessing the Computing Continuum for Programming Our World,”
Fog Computing: Theory and Practice: John Wiley & Sons, Inc., 2020.
DOI: 10.1002/9781119551713.ch7
(1.4 MB)
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Harnessing GPU's Tensor Cores Fast FP16 Arithmetic to Speedup Mixed-Precision Iterative Refinement Solvers and Achieve 74 Gflops/Watt on Nvidia V100
, San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.
(2.96 MB)

Harnessing GPU Tensor Cores for Fast FP16 Arithmetic to Speed up Mixed-Precision Iterative Refinement Solvers,”
The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Dallas, TX, IEEE, November 2018.
DOI: 10.1109/SC.2018.00050
(642.51 KB)
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Hands-on Research and Training in High-Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments,”
ISC High Performance, Frankfurt, Germany, Springer International Publishing, June 2019.
(1016.52 KB)
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HAN: A Hierarchical AutotuNed Collective Communication Framework,”
IEEE Cluster Conference, Kobe, Japan, Best Paper Award, IEEE Computer Society Press, September 2020.
(764.05 KB)
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A Guide for Achieving High Performance with Very Small Matrices on GPUs: A Case Study of Batched LU and Cholesky Factorizations,”
IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 5, pp. 973–984, May 2018.
DOI: 10.1109/TPDS.2017.2783929
(832.92 KB)
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GPUDirect MPI Communications and Optimizations to Accelerate FFTs on Exascale Systems,”
EuroMPI'19 Posters, Zurich, Switzerland, no. icl-ut-19-06: ICL, September 2019.
(2.25 MB)
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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.
DOI: 10.1145/3624062.3624247
“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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Ginkgo: A Node-Level Sparse Linear Algebra Library for HPC (Poster)
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(699 KB)

Generic Matrix Multiplication for Multi-GPU Accelerated Distributed-Memory Platforms over PaRSEC,”
ScalA'19: 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, IEEE, November 2019.
(260.69 KB)
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Generalizing Random Butterfly Transforms to Arbitrary Matrix Sizes
: arXiv, December 2023.