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Anzt, H., Y. M. Tsai, A. Abdelfattah, T. Cojean, and J. Dongarra, Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse and Batched Computations,” 2020 IEEE/ACM Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS): IEEE, November 2020.  (1.9 MB)
Gabriel, E., G. Fagg, and J. Dongarra, Evaluating The Performance Of MPI-2 Dynamic Communicators And One-Sided Communication,” Lecture Notes in Computer Science, Recent Advances in Parallel Virtual Machine and Message Passing Interface, 10th European PVM/MPI User's Group Meeting, vol. 2840, Venice, Italy, Springer-Verlag, Berlin, pp. 88-97, September 2003.  (254.08 KB)
Cao, Q., G. Bosilca, N. Losada, W. Wu, D. Zhong, and J. Dongarra, Evaluating Data Redistribution in PaRSEC,” IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 8, pp. 1856-1872, August 2022. DOI: 10.1109/TPDS.2021.3131657  (3.19 MB)
Baboulin, M., J. Demmel, J. Dongarra, S. Tomov, and V. Volkov, Enhancing the Performance of Dense Linear Algebra Solvers on GPUs (in the MAGMA Project) , Austin, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC08), November 2008.  (5.28 MB)
Hadri, B., H. Ltaeif, E. Agullo, and J. Dongarra, Enhancing Parallelism of Tile QR Factorization for Multicore Architectures,” Submitted to Transaction on Parallel and Distributed Systems, December 2009.  (464.23 KB)
Ltaeif, H., P. Luszczek, and J. Dongarra, Enhancing Parallelism of Tile Bidiagonal Transformation on Multicore Architectures using Tree Reduction,” Lecture Notes in Computer Science, vol. 7203, pp. 661-670, September 2012.  (185.77 KB)
Hiroyasu, T., M. Miki, S. Ogura, K. Aoi, T. Yoshida, Y. Okamoto, and J. Dongarra, Energy Minimization of Protein Tertiary Structure by Parallel Simulated Annealing using Genetic Crossover,” Special Issue on Biological Applications of Genetic and Evolutionary Computation (submitted), March 2003.  (438.68 KB)
Dongarra, J., H. Ltaeif, P. Luszczek, and V. M. Weaver, Energy Footprint of Advanced Dense Numerical Linear Algebra using Tile Algorithms on Multicore Architecture,” The 2nd International Conference on Cloud and Green Computing (submitted), Xiangtan, Hunan, China, November 2012.  (329.5 KB)
Anzt, H., S. Tomov, and J. Dongarra, Energy Efficiency and Performance Frontiers for Sparse Computations on GPU Supercomputers,” Sixth International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM '15), San Francisco, CA, ACM, February 2015. DOI: 10.1145/2712386.2712387  (2.29 MB)
London, K., J. Dongarra, S. Moore, P. Mucci, K. Seymour, and T. Spencer, End-user Tools for Application Performance Analysis, Using Hardware Counters,” International Conference on Parallel and Distributed Computing Systems, Dallas, TX, August 2001.  (306.54 KB)
Li, Y., A. YarKhan, J. Dongarra, K. Seymour, and A. Hurault, Enabling Workflows in GridSolve: Request Sequencing and Service Trading,” Journal of Supercomputing, vol. 64, issue 3, pp. 1133-1152, June 2013. DOI: 10.1007/s11227-010-0549-1  (821.29 KB)
Song, F., S. Tomov, and J. Dongarra, Enabling and Scaling Matrix Computations on Heterogeneous Multi-Core and Multi-GPU Systems,” 26th ACM International Conference on Supercomputing (ICS 2012), San Servolo Island, Venice, Italy, ACM, June 2012.  (5.88 MB)
YarKhan, A., J. Kurzak, A. Abdelfattah, and J. Dongarra, An Empirical View of SLATE Algorithms on Scalable Hybrid System,” Innovative Computing Laboratory Technical Report, no. ICL-UT-19-08: University of Tennessee, Knoxville, September 2019.  (441.16 KB)
You, H., K. Seymour, J. Dongarra, and S. Moore, Empirical Tuning of a Multiresolution Analysis Kernel using a Specialized Code Generator,” ICL Technical Report, no. ICL-UT-07-02, January 2007.  (123.34 KB)
Dongarra, J., and S. Moore, Empirical Performance Tuning of Dense Linear Algebra Software,” in Performance Tuning of Scientific Applications (to appear), 00 2010.
Song, F., S. Tomov, and J. Dongarra, Efficient Support for Matrix Computations on Heterogeneous Multi-core and Multi-GPU Architectures,” University of Tennessee Computer Science Technical Report, UT-CS-11-668, (also Lawn 250), June 2011.  (5.93 MB)
Wolf, F., B. Mohr, J. Dongarra, and S. Moore, Efficient Pattern Search in Large Traces through Successive Refinement,” Proceedings of Euro-Par 2004, Pisa, Italy, Springer-Verlag, August 2004.  (177.46 KB)
Turchenko, V., G. Bosilca, A. Bouteiller, and J. Dongarra, Efficient Parallelization of Batch Pattern Training Algorithm on Many-core and Cluster Architectures,” 7th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, Berlin, Germany, September 2013.  (102.51 KB)
Solcà, R., A. Kozhevnikov, A. Haidar, S. Tomov, T. C. Schulthess, and J. Dongarra, Efficient Implementation Of Quantum Materials Simulations On Distributed CPU-GPU Systems,” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC15), Austin, TX, ACM, November 2015.  (1.09 MB)
Kolev, T., P. Fischer, M. Min, J. Dongarra, J. Brown, V. Dobrev, T. Warburton, S. Tomov, M. S. Shephard, A. Abdelfattah, et al., Efficient exascale discretizations: High-order finite element methods,” The International Journal of High Performance Computing Applications, pp. 10943420211020803, 2021. DOI: 10.1177/10943420211020803
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, Efficient Eigensolver Algorithms on Accelerator Based Architectures,” 2015 SIAM Conference on Applied Linear Algebra (SIAM LA), Atlanta, GA, SIAM, October 2015.  (6.98 MB)
Baboulin, M., D. Becker, G. Bosilca, A. Danalis, and J. Dongarra, An efficient distributed randomized solver with application to large dense linear systems,” ICL Technical Report, no. ICL-UT-12-02, July 2012.  (626.26 KB)
Baboulin, M., D. Becker, G. Bosilca, A. Danalis, and J. Dongarra, An Efficient Distributed Randomized Algorithm for Solving Large Dense Symmetric Indefinite Linear Systems,” Parallel Computing, vol. 40, issue 7, pp. 213-223, July 2014. DOI: 10.1016/j.parco.2013.12.003  (1.42 MB)
Anzt, H., J. Dongarra, M. Kreutzer, G. Wellein, and M. Kohler, Efficiency of General Krylov Methods on GPUs – An Experimental Study,” 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 683-691, May 2016. DOI: 10.1109/IPDPSW.2016.45
Anzt, H., J. Dongarra, M. Kreutzer, G. Wellein, and M. Kohler, Efficiency of General Krylov Methods on GPUs – An Experimental Study,” The Sixth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), Chicago, IL, IEEE, May 2016. DOI: 10.1109/IPDPSW.2016.45  (285.28 KB)
You, H., K. Seymour, and J. Dongarra, An Effective Empirical Search Method for Automatic Software Tuning,” ICL Technical Report, no. ICL-UT-05-02, January 2005.  (74.66 KB)
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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)
Song, F., A. YarKhan, and J. Dongarra, Dynamic Task Scheduling for Linear Algebra Algorithms on Distributed-Memory Multicore Systems,” International Conference for High Performance Computing, Networking, Storage, and Analysis (SC '09), Portland, OR, November 2009.  (502.49 KB)
Hoque, R., T. Herault, G. Bosilca, and J. Dongarra, Dynamic Task Discovery in PaRSEC- A data-flow task-based Runtime,” ScalA17, Denver, ACM, September 2017. DOI: 10.1145/3148226.3148233  (1.15 MB)
Bosilca, G., T. Herault, and J. Dongarra, DTE: PaRSEC Systems and Interfaces (Poster) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (840.54 KB)
Bosilca, G., T. Herault, and J. Dongarra, DTE: PaRSEC Enabled Libraries and Applications (Poster) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (979.27 KB)
Bosilca, G., T. Herault, and J. Dongarra, DTE: PaRSEC Enabled Libraries and Applications : 2021 Exascale Computing Project Annual Meeting, April 2021.  (3.24 MB)
Anzt, H., E. Chow, D. Szyld, and J. Dongarra, Domain Overlap for Iterative Sparse Triangular Solves on GPUs,” Software for Exascale Computing - SPPEXA, vol. 113: Springer International Publishing, pp. 527–545, September 2016. DOI: 10.1007/978-3-319-40528-5_24
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)
Bosilca, G., A. Bouteiller, T. Herault, P. Lemariner, and J. Dongarra, Dodging the Cost of Unavoidable Memory Copies in Message Logging Protocols,” Proceedings of EuroMPI 2010, Stuttgart, Germany, Springer, September 2010.  (202.87 KB)
Bosilca, G., A. Bouteiller, T. Herault, P. Lemariner, and J. Dongarra, Dodging the Cost of Unavoidable Memory Copies in Message Logging Protocols,” Proceedings of EuroMPI 2010, Stuttgart, Germany, Springer, September 2010.  (202.87 KB)
Le Fèvre, V., G. Bosilca, A. Bouteiller, T. Herault, A. Hori, Y. Robert, and J. Dongarra, Do moldable applications perform better on failure-prone HPC platforms?,” 11th Workshop on Resiliency in High Performance Computing in Clusters, Clouds, and Grids, Turin, Italy, Springer Verlag, August 2018.  (360.72 KB)
Voemel, C., S. Tomov, and J. Dongarra, Divide & Conquer on Hybrid GPU-Accelerated Multicore Systems,” SIAM Journal on Scientific Computing (submitted), August 2010.
Voemel, C., S. Tomov, and J. Dongarra, Divide and Conquer on Hybrid GPU-Accelerated Multicore Systems,” SIAM Journal on Scientific Computing, vol. 34(2), pp. C70-C82, April 2012.
Bosilca, G., A. Bouteiller, A. Danalis, M. Faverge, A. Haidar, T. Herault, J. Kurzak, J. Langou, P. Lemariner, H. Ltaeif, et al., Distributed-Memory Task Execution and Dependence Tracking within DAGuE and the DPLASMA Project,” Innovative Computing Laboratory Technical Report, no. ICL-UT-10-02, 00 2010.  (400.75 KB)
Herault, T., Y. Robert, G. Bosilca, R. Harrison, C. Lewis, E. Valeev, and J. Dongarra, Distributed-Memory Multi-GPU Block-Sparse Tensor Contraction for Electronic Structure,” 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), Portland, OR, IEEE, May 2021.
Yamazaki, I., A. Ida, R. Yokota, and J. Dongarra, Distributed-Memory Lattice H-Matrix Factorization,” The International Journal of High Performance Computing Applications, vol. 33, issue 5, pp. 1046–1063, August 2019. DOI: 10.1177/1094342019861139  (1.14 MB)
Bosilca, G., A. Bouteiller, T. Herault, V. Le Fèvre, Y. Robert, and J. Dongarra, Distributed Termination Detection for HPC Task-Based Environments,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-14: University of Tennessee, June 2018.
Hiroyasu, T., M. Miki, M. Sano, H. Shimosaka, S. Tsutsui, and J. Dongarra, Distributed Probablistic Model-Building Genetic Algorithm,” Lecture Notes in Computer Science, vol. 2723: Springer-Verlag, Heidelberg, pp. 1015-1028, January 2003.  (288.91 KB)
Bosilca, G., A. Bouteiller, A. Danalis, M. Faverge, A. Haidar, T. Herault, J. Kurzak, J. Langou, P. Lemariner, H. Ltaeif, et al., Distributed Dense Numerical Linear Algebra Algorithms on Massively Parallel Architectures: DPLASMA,” University of Tennessee Computer Science Technical Report, UT-CS-10-660, September 2010.  (366.26 KB)
Dongarra, J., Z. Chen, G. Bosilca, and J. Langou, Disaster Survival Guide in Petascale Computing: An Algorithmic Approach,” in Petascale Computing: Algorithms and Applications (to appear): Chapman & Hall - CRC Press, 00 2007.  (260.18 KB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, On the Development of Variable Size Batched Computation for Heterogeneous Parallel Architectures,” The 17th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC 2016), IPDPS 2016, Chicago, IL, IEEE, May 2016.  (708.62 KB)
Arnold, D., and J. Dongarra, Developing an Architecture to Support the Implementation and Development of Scientific Computing Applications,” to appear in Proceedings of Working Conference 8: Software Architecture for Scientific Computing Applications, Ottawa, Canada, October 2000.  (176.25 KB)
Kurzak, J., P. Wu, M. Gates, I. Yamazaki, P. Luszczek, G. Ragghianti, and J. Dongarra, Designing SLATE: Software for Linear Algebra Targeting Exascale,” SLATE Working Notes, no. 03, ICL-UT-17-06: Innovative Computing Laboratory, University of Tennessee, October 2017.  (2.8 MB)

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