Publications

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Conference Proceedings
Li, Y., J. Dongarra, and S. Tomov, A Note on Auto-tuning GEMM for GPUs,” 9th International Conference on Computational Science (ICCS 2009), no. 5544-5545, Baton Rouge, LA, pp. 884-892, May 2009. DOI: 10.1007/978-3-642-01970-8_89  (236.02 KB)
Agullo, E., J. Demmel, J. Dongarra, B. Hadri, J. Kurzak, J. Langou, H. Ltaeif, P. Luszczek, and S. Tomov, Numerical Linear Algebra on Emerging Architectures: The PLASMA and MAGMA Projects,” Journal of Physics: Conference Series, vol. 180, 00 2009.  (119.37 KB)
Yamazaki, I., S. Tomov, and J. Dongarra, One-Sided Dense Matrix Factorizations on a Multicore with Multiple GPU Accelerators,” The International Conference on Computational Science (ICCS), June 2012.
Du, P., P. Luszczek, and J. Dongarra, OpenCL Evaluation for Numerical Linear Algebra Library Development,” Symposium on Application Accelerators in High-Performance Computing (SAAHPC '10), Knoxville, TN, July 2010.  (2.69 MB)
Nath, R., S. Tomov, T. Dong, and J. Dongarra, Optimizing Symmetric Dense Matrix-Vector Multiplication on GPUs,” ACM/IEEE Conference on Supercomputing (SC’11), Seattle, WA, November 2011.  (630.63 KB)
Haidar, A., H. Ltaeif, and J. Dongarra, Parallel Reduction to Condensed Forms for Symmetric Eigenvalue Problems using Aggregated Fine-Grained and Memory-Aware Kernels,” Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC11), Seattle, WA, November 2011.  (636.01 KB)
Castain, R. H., D. Solt, J. Hursey, and A. Bouteiller, PMIx: Process Management for Exascale Environments,” Proceedings of the 24th European MPI Users' Group Meeting, New York, NY, USA, ACM, pp. 14:1–14:10, 2017. DOI: 10.1145/3127024.3127027
Tsai, Y. M., T. Cojean, and H. Anzt, Porting Sparse Linear Algebra to Intel GPUs,” Euro-Par 2021: Parallel Processing Workshops, vol. 13098, Lisbon, Portugal, Springer International Publishing, pp. 57 - 68, June 2022. DOI: 10.1007/978-3-031-06156-1_5
Jagode, H., A. YarKhan, A. Danalis, and J. Dongarra, Power Management and Event Verification in PAPI,” Tools for High Performance Computing 2015: Proceedings of the 9th International Workshop on Parallel Tools for High Performance Computing, September 2015, Dresden, Germany, Dresden, Germany, Springer International Publishing, pp. pp. 41-51, 2016. DOI: 10.1007/978-3-319-39589-0_4  (565.14 KB)
Funk, Y., M. Götz, and H. Anzt, Prediction of Optimal Solvers for Sparse Linear Systems Using Deep Learning,” 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP), Philadelphia, PA, Society for Industrial and Applied Mathematics, pp. 14 - 24. DOI: 10.1137/1.978161197714110.1137/1.9781611977141.2
Kurzak, J., P. Luszczek, M. Faverge, and J. Dongarra, Programming the LU Factorization for a Multicore System with Accelerators,” Proceedings of VECPAR’12, Kobe, Japan, April 2012.  (414.33 KB)
Agullo, E., C. Augonnet, J. Dongarra, M. Faverge, H. Ltaeif, S. Thibault, and S. Tomov, 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)
Cao, Q., S. Abdulah, R. Alomairy, Y. Pei, P. Nag, G. Bosilca, J. Dongarra, M. G. Genton, D. Keyes, H. Ltaief, et al., Reshaping Geostatistical Modeling and Prediction for Extreme-Scale Environmental Applications,” 2022 International Conference for High Performance Computing, Networking, Storage and Analysis (SC22), Dallas, TX, IEEE Press, November 2022.

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