Publications

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Ltaeif, H., S. Tomov, R. Nath, and J. Dongarra, “Hybrid Multicore Cholesky Factorization with Multiple GPU Accelerators,” IEEE Transaction on Parallel and Distributed Systems (submitted), March 2010.  (3.75 MB)
Agullo, E., C. Augonnet, J. Dongarra, H. Ltaeif, R. Namyst, S. Thibault, and S. Tomov, “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.
Dong, T., V. Dobrev, T. Kolev, R. Rieben, S. Tomov, and J. Dongarra, “Hydrodynamic Computation with Hybrid Programming on CPU-GPU Clusters,” University of Tennessee Computer Science Technical Report, no. ut-cs-13-714, July 2013.  (866.68 KB)
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Dongarra, J., D. Gannon, G. Fox, and K. Kennedy, “The Impact of Multicore on Computational Science Software,” CTWatch Quarterly, vol. 3, issue 1, February 2007.
Buttari, A., J. Dongarra, J. Kurzak, J. Langou, P. Luszczek, and S. Tomov, “The Impact of Multicore on Math Software,” PARA 2006, Umea, Sweden, June 2006.  (223.53 KB)
Ayala, A., S. Tomov, X. Luo, H. Shaiek, A. Haidar, G. Bosilca, and J. Dongarra, “Impacts of Multi-GPU MPI Collective Communications on Large FFT Computation,” Workshop on Exascale MPI (ExaMPI) at SC19, Denver, CO, November 2019.  (1.6 MB)
Abdelfattah, A., M. Gates, J. Kurzak, P. Luszczek, and J. Dongarra, “Implementation of the C++ API for Batch BLAS,” SLATE Working Notes, no. 07, ICL-UT-18-04: Innovative Computing Laboratory, University of Tennessee, June 2018.  (1.07 MB)
Aupy, G., M. Faverge, Y. Robert, J. Kurzak, P. Luszczek, and J. Dongarra, “Implementing a systolic algorithm for QR factorization on multicore clusters with PaRSEC,” Lawn 277, no. UT-CS-13-709, May 2013.  (298.63 KB)
Nath, R., S. Tomov, and J. Dongarra, “An Improved MAGMA GEMM for Fermi GPUs,” International Journal of High Performance Computing, vol. 24, no. 4, pp. 511-515, 00 2010.
Nath, R., S. Tomov, and J. Dongarra, “An Improved MAGMA GEMM for Fermi GPUs,” University of Tennessee Computer Science Technical Report, no. UT-CS-10-655 (also LAPACK working note 227), July 2010.  (486.71 KB)
Haidar, A., P. Luszczek, J. Kurzak, and J. Dongarra, “An Improved Parallel Singular Value Algorithm and Its Implementation for Multicore Hardware,” University of Tennessee Computer Science Technical Report (also LAWN 283), no. ut-eecs-13-720: University of Tennessee, October 2013.  (1.23 MB)
Yamazaki, I., M. Hoemmen, P. Luszczek, and J. Dongarra, “Improving Performance of GMRES by Reducing Communication and Pipelining Global Collectives,” Proceedings of The 18th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC 2017), Best Paper Award, Orlando, FL, June 2017. DOI: 10.1109/IPDPSW.2017.65  (453.66 KB)
Lindquist, N., P. Luszczek, and J. Dongarra, “Improving the Performance of the GMRES Method using Mixed-Precision Techniques,” Smoky Mountains Computational Sciences & Engineering Conference (SMC2020), August 2020.  (600.33 KB)
Anzt, H., T. Huckle, J. Bräckle, and J. Dongarra, “Incomplete Sparse Approximate Inverses for Parallel Preconditioning,” Parallel Computing, vol. 71, pp. 1–22, January 2018. DOI: 10.1016/j.parco.2017.10.003  (1.24 MB)
Luszczek, P., I. Yamazaki, and J. Dongarra, “Increasing Accuracy of Iterative Refinement in Limited Floating-Point Arithmetic on Half-Precision Accelerators,” IEEE High Performance Extreme Computing Conference (HPEC 2019), Best Paper Finalist, Waltham, MA, IEEE, September 2019.  (470.21 KB)
Ghysels, P., S. Li, A. YarKhan, and J. Dongarra, “Initial Integration and Evaluation of SLATE and STRUMPACK,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-11: University of Tennessee, December 2018.  (249.78 KB)
YarKhan, A., G. Ragghianti, J. Dongarra, M. Cawkwell, D. Perez, and A. Voter, “Initial Integration and Evaluation of SLATE Parallel BLAS in LATTE,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-07: Innovative Computing Laboratory, University of Tennessee, June 2018.  (366.6 KB)
Tomov, S., K. Wong, J. Dongarra, R. Archibald, E. Chow, E. D'Azevedo, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, et al., Integrating Deep Learning in Domain Science at Exascale (MagmaDNN) , virtual, DOD HPCMP seminar, December 2020.  (11.12 MB)
Archibald, R., E. Chow, E. D'Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, et al., “Integrating Deep Learning in Domain Sciences at Exascale,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-10: University of Tennessee, August 2020.  (1.09 MB)
Archibald, R., E. Chow, E. D'Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, et al., “Integrating Deep Learning in Domain Sciences at Exascale,” 2020 Smoky Mountains Computational Sciences and Engineering Conference (SMC 2020), August 2020.
Ayala, A., S. Tomov, P. Luszczek, S. Cayrols, G. Ragghianti, and J. Dongarra, “Interim Report on Benchmarking FFT Libraries on High Performance Systems,” Innovative Computing Laboratory Technical Report, no. ICL-UT-21-03: University of Tennessee, July 2021.  (2.68 MB)
Dongarra, J., P. Beckman, T. Moore, P. Aerts, G. Aloisio, J-C. Andre, D. Barkai, J-Y. Berthou, T. Boku, B. Braunschweig, et al., “The International Exascale Software Project Roadmap,” International Journal of High Performance Computing, vol. 25, no. 1, pp. 3-60, January 2011. DOI: 10.1177/1094342010391989  (719.74 KB)

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