Publications

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Danalis, A., H. Jagode, and J. Dongarra, Does your tool support PAPI SDEs yet? , Tahoe City, CA, 13th Scalable Tools Workshop, July 2019.  (3.09 MB)
Davis, J., T. Gao, S. Chandrasekaran, H. Jagode, A. Danalis, P. Balaji, J. Dongarra, and M. Taufer, Characterization of Power Usage and Performance in Data-Intensive Applications using MapReduce over MPI,” 2019 International Conference on Parallel Computing (ParCo2019), Prague, Czech Republic, September 2019.
Demmel, J., J. Dongarra, A. Fox, S. Williams, V. Volkov, and K. Yelick, Accelerating Time-To-Solution for Computational Science and Engineering,” SciDAC Review, 00 2009.  (739.11 KB)
Demmel, J., J. Dongarra, B.. Parlett, W. Kahan, M. Gu, D. Bindel, Y. Hida, X. Li, O. Marques, J. E. Riedy, et al., Prospectus for the Next LAPACK and ScaLAPACK Libraries,” PARA 2006, Umea, Sweden, June 2006.  (460.11 KB)
Demmel, J., and J. Dongarra, LAPACK 2005 Prospectus: Reliable and Scalable Software for Linear Algebra Computations on High End Computers : LAPACK Working Note 164, January 2005.  (172.59 KB)
Demmel, J., J. Dongarra, J. Langou, J. Langou, P. Luszczek, and M. Mahoney, Prospectus for the Next LAPACK and ScaLAPACK Libraries: Basic ALgebra LIbraries for Sustainable Technology with Interdisciplinary Collaboration (BALLISTIC),” LAPACK Working Notes, no. 297, ICL-UT-20-07: University of Tennessee.  (1.41 MB)
Demmel, J., J. Dongarra, V. Eijkhout, E. Fuentes, A. Petitet, R. Vuduc, C. Whaley, and K. Yelick, Self Adapting Linear Algebra Algorithms and Software,” IEEE Proceedings (to appear), 00 2004.  (587.67 KB)
Dempsey, B., and D. Weiss, Towards An Efficient, Scalable Replication Mechanism for the I2-DSI Project,” University of North Carolina School of Library and Information Science Technical Report, no. TR-1999-01, January 1999.
Deshmukh, S., R. Yokota, and G. Bosilca, Cache Optimization and Performance Modeling of Batched, Small, and Rectangular Matrix Multiplication on Intel, AMD, and Fujitsu Processors,” ACM Transactions on Mathematical Software, vol. 49, issue 3, pp. 1 - 29, September 2023.
Deshmukh, S., R. Yokota, G. Bosilca, and Q. Ma, O(N) distributed direct factorization of structured dense matrices using runtime systems,” 52nd International Conference on Parallel Processing (ICPP 2023), Salt Lake City, Utah, ACM, August 2023.
Dewolfs, D., J. Broeckhove, V. Sunderam, and G. Fagg, FT-MPI, Fault-Tolerant Metacomputing and Generic Name Services: A Case Study,” Lecture Notes in Computer Science, vol. 4192, no. ICL-UT-06-14: Springer Berlin / Heidelberg, pp. 133-140, 00 2006.  (362.44 KB)
Donfack, S., J. Dongarra, M. Faverge, M. Gates, J. Kurzak, P. Luszczek, and I. Yamazaki, On Algorithmic Variants of Parallel Gaussian Elimination: Comparison of Implementations in Terms of Performance and Numerical Properties,” University of Tennessee Computer Science Technical Report, no. UT-CS-13-715, July 2013, 2012.  (358.98 KB)
Donfack, S., S. Tomov, and J. Dongarra, Performance evaluation of LU factorization through hardware counter measurements,” University of Tennessee Computer Science Technical Report, no. ut-cs-12-700, October 2012.  (794.82 KB)
Donfack, S., J. Dongarra, M. Faverge, M. Gates, J. Kurzak, P. Luszczek, and I. Yamazaki, A Survey of Recent Developments in Parallel Implementations of Gaussian Elimination,” Concurrency and Computation: Practice and Experience, vol. 27, issue 5, pp. 1292-1309, April 2015.  (783.45 KB)
Donfack, S., S. Tomov, and J. Dongarra, Dynamically balanced synchronization-avoiding LU factorization with multicore and GPUs,” University of Tennessee Computer Science Technical Report, no. ut-cs-13-713, July 2013.  (659.77 KB)
Donfack, S., S. Tomov, and J. Dongarra, Dynamically balanced synchronization-avoiding LU factorization with multicore and GPUs,” Fourth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), IPDPS 2014, May 2014.  (490.08 KB)
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices,” International Conference on Computational Science (ICCS 2017), Zurich, Switzerland, Procedia Computer Science, June 2017.  (364.95 KB)
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, Accelerating the SVD Bi-Diagonalization of a Batch of Small Matrices using GPUs,” Journal of Computational Science, vol. 26, pp. 237–245, May 2018.  (2.18 MB)
Dong, T., V. Dobrev, T. Kolev, R. Rieben, S. Tomov, and J. Dongarra, A Step towards Energy Efficient Computing: Redesigning A Hydrodynamic Application on CPU-GPU,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (1.01 MB)
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, A Fast Batched Cholesky Factorization on a GPU,” International Conference on Parallel Processing (ICPP-2014), Minneapolis, MN, September 2014.  (1.37 MB)
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)
Dong, T., T. Kolev, R. Rieben, V. Dobrev, S. Tomov, and J. Dongarra, Acceleration of the BLAST Hydro Code on GPU,” Supercomputing '12 (poster), Salt Lake City, Utah, SC12, November 2012.
Dong, T., A. Haidar, P. Luszczek, J. Harris, S. Tomov, and J. Dongarra, LU Factorization of Small Matrices: Accelerating Batched DGETRF on the GPU,” 16th IEEE International Conference on High Performance Computing and Communications (HPCC), Paris, France, IEEE, August 2014.  (684.73 KB)
Dong, T., A. Haidar, P. Luszczek, S. Tomov, A. Abdelfattah, and J. Dongarra, MAGMA Batched: A Batched BLAS Approach for Small Matrix Factorizations and Applications on GPUs,” Innovative Computing Laboratory Technical Report, no. ICL-UT-16-02: University of Tennessee, August 2016.  (929.79 KB)
Dongarra, J., K. London, S. Moore, P. Mucci, and D. Terpstra, Using PAPI for Hardware Performance Monitoring on Linux Systems,” Conference on Linux Clusters: The HPC Revolution, Urbana, Illinois, Linux Clusters Institute, June 2001.  (422.35 KB)
Dongarra, J., and A. Lastovetsky, An Overview of Heterogeneous High Performance and Grid Computing,” Engineering the Grid (to appear): Nova Science Publishers, Inc., 00 2004.  (199.93 KB)
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)
Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software,” University of Tennessee Computer Science Technical Report, no. cs-89-85, February 2013.  (539.24 KB)
Dongarra, J., P. Kacsuk, and N.. Podhorszki, Recent Advances in Parallel Virtual Machine and Message Passing Interface,” Lecture Notes in Computer Science: Proceedings of 7th European PVM/MPI Users' Group Meeting 2000, (Hungary: Springer Verlag), pp. V1908, January 2000.
Dongarra, J., M. A. Heroux, and P. Luszczek, A New Metric for Ranking High-Performance Computing Systems,” National Science Review, vol. 3, issue 1, pp. 30-35, January 2016.  (393.55 KB)
Dongarra, J., M. Faverge, T. Herault, J. Langou, and Y. Robert, 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)
Dongarra, J., A Not So Simple Matter of Software,” NCSA Access Online: NCSA, 00 2005.  (457.69 KB)
Dongarra, J., S. Moore, G. D. Peterson, S. Tomov, J. Allred, V. Natoli, and D. Richie, Exploring New Architectures in Accelerating CFD for Air Force Applications,” Proceedings of the DoD HPCMP User Group Conference, Seattle, Washington, January 2008.  (492.86 KB)
Dongarra, J., H. Meuer, H. D. Simon, and E. Strohmaier, High Performance Computing Trends,” HERMIS, vol. 2, pp. 155-163, November 2001.
Dongarra, J., High Performance Computing Trends, Supercomputers, Clusters, and Grids,” Information Processing Society of Japan Symposium Series, vol. 2003, no. 14, pp. 55-58, January 2003.
Dongarra, J., E. Jeannot, E. Saule, and Z. Shi, Bi-objective Scheduling Algorithms for Optimizing Makespan and Reliability on Heterogeneous Systems,” 19th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA) (submitted), San Diego, CA, June 2007.  (223.82 KB)
Dongarra, J., S. Hammarling, N. J. Higham, S. Relton, and M. Zounon, Optimized Batched Linear Algebra for Modern Architectures,” Euro-Par 2017, Santiago de Compostela, Spain, Springer, August 2017.  (618.33 KB)
Dongarra, J., and P. Beckman, International Exascale Software Project Roadmap v1.0,” University of Tennessee Computer Science Technical Report, UT-CS-10-654, May 2010.  (719.74 KB)
Dongarra, J., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and I. Yamazaki, Accelerating Numerical Dense Linear Algebra Calculations with GPUs,” Numerical Computations with GPUs: Springer International Publishing, pp. 3-28, 2014.  (1.06 MB)
Dongarra, J., T. Herault, and Y. Robert, Fault Tolerance Techniques for High-performance Computing,” University of Tennessee Computer Science Technical Report (also LAWN 289), no. UT-EECS-15-734: University of Tennessee, May 2015.
Dongarra, J., T. Herault, and Y. Robert, Revisiting the Double Checkpointing Algorithm,” 15th Workshop on Advances in Parallel and Distributed Computational Models, at the IEEE International Parallel & Distributed Processing Symposium, Boston, MA, May 2013.  (591.1 KB)
Dongarra, J., S. Moore, and A. Trefethen, Numerical Libraries and Tools for Scalable Parallel Cluster Computing,” International Journal of High Performance Applications and Supercomputing, vol. 15, no. 2, pp. 175-180, January 2001.  (37.38 KB)
Dongarra, J., Report on the Fujitsu Fugaku System,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-06: University of Tennessee, June 2020.  (3.3 MB)
Dongarra, J., P. Luszczek, and A. Petitet, The LINPACK Benchmark: Past, Present, and Future,” Concurrency: Practice and Experience, vol. 15, pp. 803-820, 00 2008.  (94.86 KB)
Dongarra, J., and V. Eijkhout, Numerical Linear Algebra Algorithms and Software,” Journal of Computational and Applied Mathematics, vol. 123, no. 1-2, pp. 489-514, October 1999.  (258.62 KB)
Dongarra, J., M. A. Heroux, and P. Luszczek, High Performance Conjugate Gradient Benchmark: A new Metric for Ranking High Performance Computing Systems,” International Journal of High Performance Computing Applications, vol. 30, issue 1, pp. 3 - 10, February 2016.  (277.51 KB)
Dongarra, J., and V. Eijkhout, Finite-choice Algorithm Optimization in Conjugate Gradients (LAPACK Working Note 159),” University of Tennessee Computer Science Technical Report, UT-CS-03-502, January 2003.  (64.52 KB)
Dongarra, J., G. H. Golub, C. Moler, and K. Moore, Netlib and NA-Net: building a scientific computing community,” In IEEE Annals of the History of Computing (to appear), August 2007.  (352.71 KB)
Dongarra, J., V. Eijkhout, and H. van der Vorst, An Iterative Solver Benchmark,” Scientific Programming (to appear), 00 2002.  (142.67 KB)
Dongarra, J., L. Grigori, and N. J. Higham, Numerical Algorithms for High-Performance Computational Science,” Philosophical Transactions of the Royal Society A, vol. 378, issue 2166, 2020.  (724.37 KB)

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