Publications
Export 190 results:
Filters: First Letter Of Last Name is A [Clear All Filters]
Scheduling Cholesky Factorization on Multicore Architectures with GPU Accelerators
, Knoxville, TN, 2010 Symposium on Application Accelerators in High-Performance Computing (SAAHPC'10), Poster, July 2010.
(3.86 MB)
(3.86 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)
(3.53 MB)
“LU Factorization for Accelerator-Based Systems,”
IEEE/ACS AICCSA 2011, Sharm-El-Sheikh, Egypt, December 2011.
(234.86 KB)
(234.86 KB)
“Faster, Cheaper, Better - A Hybridization Methodology to Develop Linear Algebra Software for GPUs,”
LAPACK Working Note, no. 230, 00 2010.
(334.48 KB)
(334.48 KB)
“A Hybridization Methodology for High-Performance Linear Algebra Software for GPUs,”
in GPU Computing Gems, Jade Edition, vol. 2: Elsevier, pp. 473-484, 00 2011.
“Resiliency in numerical algorithm design for extreme scale simulations,”
The International Journal of High Performance Computing Applications, vol. 36371337212766180823, issue 2, pp. 251 - 285, March 2022.
DOI: 10.1177/10943420211055188
“Numerical Linear Algebra on Emerging Architectures: The PLASMA and MAGMA Projects,”
Journal of Physics: Conference Series, vol. 180, 00 2009.
(119.37 KB)
(119.37 KB)
“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)
(468.17 KB)
“A Collection of White Papers from the BDEC2 Workshop in Bloomington, IN,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-18-15: University of Tennessee, Knoxville, November 2018.
(9.26 MB)
(9.26 MB)
“SLATE Performance Improvements: QR and Eigenvalues,”
SLATE Working Notes, no. 17, ICL-UT-21-02, April 2021.
(2 MB)
(2 MB)
“Compressed basis GMRES on high-performance graphics processing units,”
The International Journal of High Performance Computing Applications, May 2022.
DOI: 10.1177/10943420221115140 (13.52 MB)
(13.52 MB)
“Compression and load balancing for efficient sparse matrix‐vector product on multicore processors and graphics processing units,”
Concurrency and Computation: Practice and Experience, vol. 34, issue 14, June 2022.
DOI: 10.1002/cpe.6515 (749.82 KB)
(749.82 KB)
“Sparse matrix-vector and matrix-multivector products for the truncated SVD on graphics processors,”
Concurrency and Computation: Practice and Experience, August 2023.
DOI: 10.1002/cpe.7871
“Communication Avoiding LU with Tournament Pivoting in SLATE,”
SLATE Working Notes, no. 18, ICL-UT-22-01, January 2022.
(3.74 MB)
(3.74 MB)
“A Collection of White Papers from the BDEC2 Workshop in San Diego, CA,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-19-13: University of Tennessee, October 2019.
(8.25 MB)
(8.25 MB)
“Fast and Small Short Vector SIMD Matrix Multiplication Kernels for the CELL Processor,”
University of Tennessee Computer Science Technical Report, no. UT-CS-08-609, (also LAPACK Working Note 189), January 2008.
(500.99 KB)
(500.99 KB)
“Analysis and Optimization of Yee_Bench using Hardware Performance Counters,”
Proceedings of Parallel Computing 2005 (ParCo), Malaga, Spain, January 2005.
(72.27 KB)
(72.27 KB)
“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)
(5.82 MB)
Ginkgo: A Node-Level Sparse Linear Algebra Library for HPC (Poster)
, Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.
(699 KB)
(699 KB)
“Variable-Size Batched Gauss-Jordan Elimination for Block-Jacobi Preconditioning on Graphics Processors,”
Parallel Computing, vol. 81, pp. 131-146, January 2019.
DOI: 10.1016/j.parco.2017.12.006 (1.9 MB)
(1.9 MB)
“Towards Continuous Benchmarking,”
Platform for Advanced Scientific Computing Conference (PASC 2019), Zurich, Switzerland, ACM Press, June 2019.
DOI: 10.1145/3324989.3325719 (1.51 MB)
(1.51 MB)
“Are we Doing the Right Thing? – A Critical Analysis of the Academic HPC Community,”
2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Rio de Janeiro, Brazil, IEEE, May 2019.
DOI: 10.1109/IPDPSW.2019.00122 (622.32 KB)
(622.32 KB)
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)
(16.8 MB)
“Towards a New Peer Review Concept for Scientific Computing ensuring Technical Quality, Software Sustainability, and Result Reproducibility,”
Proceedings in Applied Mathematics and Mechanics, vol. 19, issue 1, November 2019.
DOI: 10.1002/pamm.201900490
“Load-Balancing Sparse Matrix Vector Product Kernels on GPUs,”
ACM Transactions on Parallel Computing, vol. 7, issue 1, March 2020.
DOI: 10.1145/3380930 (5.67 MB)
(5.67 MB)
