Publications

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Penchoff, D. A., E. Valeev, H. Jagode, P. Luszczek, A. Danalis, G. Bosilca, R. J. Harrison, J. Dongarra, and T. L. Windus, “An Introduction to High Performance Computing and Its Intersection with Advances in Modeling Rare Earth Elements and Actinides,” Rare Earth Elements and Actinides: Progress in Computational Science Applications, vol. 1388, Washington, DC, American Chemical Society, pp. 3-53, October 2021. DOI: 10.1021/bk-2021-1388.ch001
Dongarra, J., and P. Luszczek, “Introduction to the HPCChallenge Benchmark Suite,” ICL Technical Report, no. ICL-UT-05-01, January 2005.  (124.86 KB)
Dongarra, J., and S. Tomov, An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra : NVIDIA Webinar, June 2010.
Haidar, A., P. Wu, S. Tomov, and J. Dongarra, “Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers,” ScalA17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, ACM.  (766.35 KB)
Haidar, A., H. Jagode, P. Vaccaro, A. YarKhan, S. Tomov, and J. Dongarra, “Investigating Power Capping toward Energy-Efficient Scientific Applications,” Concurrency Computation: Practice and Experience, vol. 2018, issue e4485, pp. 1-14, April 2018. DOI: 10.1002/cpe.4485  (1.2 MB)
Abdelfattah, A., S. Tomov, and J. Dongarra, “Investigating the Benefit of FP16-Enabled Mixed-Precision Solvers for Symmetric Positive Definite Matrices using GPUs,” International Conference on Computational Science (ICCS 2020), Amsterdam, Netherlands, Springer, Cham, June 2020. DOI: 10.1007/978-3-030-50417-5_18  (702.38 KB)
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Anzt, H., and J. Dongarra, “A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs,” SBAC-PAD, Lyon, France, IEEE, 2018.  (237.68 KB)
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Vetter, J., R. Glassbrook, J. Dongarra, K. Schwan, B. Loftis, S. McNally, J. Meredith, J. Rogers, P. Roth, K. Spafford, et al., “Keeneland: Bringing Heterogeneous GPU Computing to the Computational Science Community,” IEEE Computing in Science & Engineering, vol. 13, issue 5, pp. 90-95, August 2011. DOI: 10.1109/MCSE.2011.83  (932.57 KB)
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Yamazaki, I., and J. Dongarra, “LAWN 294: Aasen's Symmetric Inde nite Linear Solvers in LAPACK,” LAPACK Working Note, no. LAWN 294, ICL-UT-17-13: University of Tennessee, December 2017.  (854.1 KB)
Gates, M., A. Charara, J. Kurzak, A. YarKhan, I. Yamazaki, and J. Dongarra, “Least Squares Performance Report,” SLATE Working Notes, no. 09, ICL-UT-18-10: Innovative Computing Laboratory, University of Tennessee, December 2018.  (1.76 MB)
Kurzak, J., M. Gates, A. Charara, A. YarKhan, and J. Dongarra, “Least Squares Solvers for Distributed-Memory Machines with GPU Accelerators,” ACM International Conference on Supercomputing (ICS '19), Phoenix, Arizona, ACM, pp. 117–126, June 2019. DOI: https://dl.acm.org/doi/abs/10.1145/3330345.3330356  (1.63 MB)
Cao, Q., Y. Pei, K. Akbudak, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, “Leveraging PaRSEC Runtime Support to Tackle Challenging 3D Data-Sparse Matrix Problems,” 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), Portland, OR, IEEE, May 2021.  (1.08 MB)
Abdelfattah, A., H. Anzt, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, , and A. YarKhan, “Linear Algebra Software for Large-Scale Accelerated Multicore Computing,” Acta Numerica, vol. 25, pp. 1-160, May 2016. DOI: 10.1017/S0962492916000015
Kurzak, J., M. Gates, I. Yamazaki, A. Charara, A. YarKhan, J. Finney, G. Ragghianti, P. Luszczek, and J. Dongarra, “Linear Systems Performance Report,” SLATE Working Notes, no. 08, ICL-UT-18-08: Innovative Computing Laboratory, University of Tennessee, September 2018.  (1.64 MB)
Kurzak, J., M. Gates, A. Charara, A. YarKhan, I. Yamazaki, and J. Dongarra, “Linear Systems Solvers for Distributed-Memory Machines with GPU Accelerators,” Euro-Par 2019: Parallel Processing, vol. 11725: Springer, pp. 495–506, August 2019. DOI: 10.1007/978-3-030-29400-7_35
Anzt, H., T. Cojean, C. Yen-Chen, J. Dongarra, G. Flegar, P. Nayak, S. Tomov, Y. M. Tsai, and W. Wang, “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)
Bell, G., D. Bailey, A. H. Karp, J. Dongarra, and K. Walsh, “A Look Back on 30 Years of the Gordon Bell Prize,” International Journal of High Performance Computing and Networking, vol. 31, issue 6, pp. 469–484, 2017.
Agullo, E., C. Augonnet, J. Dongarra, M. Faverge, J. Langou, H. Ltaeif, and S. Tomov, “LU Factorization for Accelerator-Based Systems,” IEEE/ACS AICCSA 2011, Sharm-El-Sheikh, Egypt, December 2011.  (234.86 KB)
Kurzak, J., P. Luszczek, and J. Dongarra, “LU Factorization with Partial Pivoting for a Multicore System with Accelerators,” IEEE Transactions on Parallel and Distributed Computing, vol. 24, issue 8, pp. 1613-1621, August 2013. DOI: http://doi.ieeecomputersociety.org/10.1109/TPDS.2012.242  (1.08 MB)
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Tomov, S., J. Dongarra, A. Haidar, I. Yamazaki, T. Dong, T. Schulthess, and R. Solcà, MAGMA: A Breakthrough in Solvers for Eigenvalue Problems , San Jose, CA, GPU Technology Conference (GTC12), Presentation, May 2012.  (9.23 MB)
Dongarra, J., T. Dong, M. Gates, A. Haidar, S. Tomov, and I. Yamazaki, MAGMA: A New Generation of Linear Algebra Library for GPU and Multicore Architectures , Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), Presentation, November 2012.  (4.69 MB)

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