Publications

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Bai, Z., J. Demmel, J. Dongarra, J. Langou, and J. Wang, LAPACK,” Handbook of Linear Algebra, Second, Boca Raton, FL, CRC Press, 2013.  (223.21 KB)
Song, F., S. Moore, and J. Dongarra, L2 Cache Modeling for Scientific Applications on Chip Multi-Processors,” Proceedings of the 2007 International Conference on Parallel Processing, Xi'an, China, IEEE Computer Society, January 2007.  (654.11 KB)
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Ma, T., G. Bosilca, A. Bouteiller, and J. Dongarra, Kernel-assisted and topology-aware MPI collective communications on multi-core/many-core platforms,” Journal of Parallel and Distributed Computing, vol. 73, issue 7, pp. 1000-1010, July 2013.  (1.4 MB)
Ma, T., G. Bosilca, A. Bouteiller, B. Goglin, J.. Squyres, and J. Dongarra, Kernel Assisted Collective Intra-node MPI Communication Among Multi-core and Many-core CPUs,” Int'l Conference on Parallel Processing (ICPP '11), Taipei, Taiwan, September 2011.
Ma, T., G. Bosilca, A. Bouteiller, B. Goglin, J.. Squyres, and J. Dongarra, Kernel Assisted Collective Intra-node Communication Among Multicore and Manycore CPUs,” University of Tennessee Computer Science Technical Report, UT-CS-10-663, November 2010.  (384.75 KB)
Vetter, J., R. Glassbrook, K. Schwan, S. Yalamanchili, M. Horton, A. Gavrilovska, M. Slawinska, J. Dongarra, J. Meredith, P. Roth, et al., Keeneland: Computational Science Using Heterogeneous GPU Computing,” Contemporary High Performance Computing: From Petascale Toward Exascale, Boca Raton, FL, Taylor and Francis, 2013.  (2.7 MB)
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.  (932.57 KB)
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Doolin, D., J. Dongarra, and K. Seymour, JLAPACK - Compiling LAPACK Fortran to Java,” Scientific Programming, vol. 7, no. 2, pp. 111-138, October 2002.  (307.46 KB)
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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Anzt, H., E. Chow, and J. Dongarra, Iterative Sparse Triangular Solves for Preconditioning,” EuroPar 2015, Vienna, Austria, Springer Berlin, August 2015.  (322.36 KB)
Dongarra, J., V. Eijkhout, and H. van der Vorst, Iterative Solver Benchmark (LAPACK Working Note 152),” Scientific Programming, vol. 9, no. 4, pp. 223-231, 00 2001.  (168.05 KB)
Dongarra, J., V. Eijkhout, and H. van der Vorst, An Iterative Solver Benchmark,” Scientific Programming (to appear), 00 2002.  (142.67 KB)
Jagode, H., S. Moore, D. Terpstra, J. Dongarra, A. Knuepfer, M. Jurenz, M. S. Mueller, and W. E. Nagel, I/O Performance Analysis for the Petascale Simulation Code FLASH,” ISC'09, Hamburg, Germany, June 2009.  (88.88 KB)
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.  (702.38 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.  (1.2 MB)
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)
Dongarra, J., and S. Tomov, An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra : NVIDIA Webinar, June 2010.
Dongarra, J., and P. Luszczek, Introduction to the HPCChallenge Benchmark Suite,” ICL Technical Report, no. ICL-UT-05-01, January 2005.  (124.86 KB)
Luszczek, P., J. Dongarra, D. Koester, R. Rabenseifner, B. Lucas, J. Kepner, J. McCalpin, D. Bailey, and D. Takahashi, Introduction to the HPC Challenge Benchmark Suite , March 2005.  (124.86 KB)
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.
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., 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.  (719.74 KB)
Dongarra, J., P. Beckman, P. Aerts, F. Cappello, T. Lippert, S. Matsuoka, P. Messina, T. Moore, R. Stevens, A. Trefethen, et al., The International Exascale Software Project: A Call to Cooperative Action by the Global High Performance Community,” International Journal of High Performance Computing Applications (to appear), July 2009.  (203.04 KB)
Canning, A., J. Dongarra, J. Langou, O. Marques, S. Tomov, C. Voemel, and L-W. Wang, Interior State Computation of Nano Structures,” PARA 2008, 9th International Workshop on State-of-the-Art in Scientific and Parallel Computing, Trondheim, Norway, May 2008.  (137.12 KB)
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)
Hardt, M., K. Seymour, J. Dongarra, M. Zapf, and N. Ruiter, Interactive Grid-Access Using Gridsolve and Giggle,” Computing and Informatics, vol. 27, no. 2, pp. 233-248,ISSN1335-9150, 00 2008.  (533.4 KB)
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.
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)
Arnold, D., H. Casanova, and J. Dongarra, Innovations of the NetSolve Grid Computing System,” Concurrency: Practice and Experience, vol. 14, no. 13-15, pp. 1457-1479, January 2002.  (311.31 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)
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)
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)
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.  (1.24 MB)
Moore, S., F. Wolf, J. Dongarra, and B. Mohr, Improving Time to Solution with Automated Performance Analysis,” Second Workshop on Productivity and Performance in High-End Computing (P-PHEC) at 11th International Symposium on High Performance Computer Architecture (HPCA-2005), San Francisco, February 2005.  (112.63 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)
Yamazaki, I., H. Anzt, S. Tomov, M. Hoemmen, and J. Dongarra, Improving the performance of CA-GMRES on multicores with multiple GPUs,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (333.82 KB)
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.  (453.66 KB)
Eidson, T., V. Eijkhout, and J. Dongarra, Improvements in the Efficient Composition of Applications,” IPDPS 2004, NGS Workshop (to appear), Sante Fe, 00 2004.  (42.85 KB)
Turchenko, V., L. Grandinetti, G. Bosilca, and J. Dongarra, Improvement of parallelization efficiency of batch pattern BP training algorithm using Open MPI,” Proceedings of International Conference on Computational Science, ICCS 2010 (to appear), Amsterdam The Netherlands, Elsevier, June 2010.  (125.01 KB)
Jeannot, E., K. Seymour, A. YarKhan, and J. Dongarra, Improved Runtime and Transfer Time Prediction Mechanisms in a Network Enabled Servers Middleware,” Parallel Processing Letters, vol. 17, no. 1, pp. 47-59, March 2007.  (718.4 KB)
Jeannot, E., K. Seymour, A. YarKhan, and J. Dongarra, Improved Runtime and Transfer Time Prediction Mechanisms in a Network Enabled Server,” Parallel Processing Letters, vol. 17, no. 1, pp. 47-59, March 2006.  (718.4 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)
Haidar, A., P. Luszczek, J. Kurzak, and J. Dongarra, An Improved Parallel Singular Value Algorithm and Its Implementation for Multicore Hardware,” Supercomputing 2013, Denver, CO, November 2013.
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)
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.
Kurzak, J., and J. Dongarra, Implementing Linear Algebra Routines on Multi-Core Processors with Pipelining and a Look Ahead,” University of Tennessee Computer Science Tech Report, UT-CS-06-581, LAPACK Working Note #178, January 2006.  (304.4 KB)
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)
Anzt, H., S. Tomov, and J. Dongarra, Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-σ formats on NVIDIA GPUs,” University of Tennessee Computer Science Technical Report, no. UT-EECS-14-727: University of Tennessee, April 2014.  (578.11 KB)
Yamazaki, I., D. Becker, J. Dongarra, A. Druinsky, I.. Peled, S. Toledo, G. Ballard, J. Demmel, and O. Schwartz, Implementing a Blocked Aasen’s Algorithm with a Dynamic Scheduler on Multicore Architectures,” IPDPS 2013 (submitted), Boston, MA, 00 2013.  (1.22 MB)

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