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Losada, N., A. Bouteiller, and G. Bosilca, Asynchronous Receiver-Driven Replay for Local Rollback of MPI Applications,” Fault Tolerance for HPC at eXtreme Scale (FTXS) Workshop at The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'19), November 2019.  (440.7 KB)
Losada, N., P. González, M. J. Martín, G. Bosilca, A. Bouteiller, and K. Teranishi, Fault Tolerance of MPI Applications in Exascale Systems: The ULFM Solution,” Future Generation Computer Systems, vol. 106, pp. 467-481, May 2020. DOI: 10.1016/j.future.2020.01.026  (2.06 MB)
Losada, N., G. Bosilca, A. Bouteiller, P. González, and M. J. Martín, Local Rollback for Resilient MPI Applications with Application-Level Checkpointing and Message Logging,” Future Generation Computer Systems, vol. 91, pp. 450-464, February 2019. DOI: 10.1016/j.future.2018.09.041  (1.16 MB)
Lopez, F., E. Chow, S. Tomov, and J. Dongarra, Asynchronous SGD for DNN Training on Shared-Memory Parallel Architectures,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-04: University of Tennessee, Knoxville, March 2020.  (188.51 KB)
Lopez, M. G., W. Joubert, V. Larrea, O. Hernandez, A. Haidar, S. Tomov, and J. Dongarra, Evaluation of Directive-Based Performance Portable Programming Models,” International Journal of High Performance Computing and Networking, vol. 14, issue 2, pp. 165-182. DOI: http://dx.doi.org/10.1504/IJHPCN.2017.10009064  (1.12 MB)
Lopez, M. G., V. Larrea, W. Joubert, O. Hernandez, A. Haidar, S. Tomov, and J. Dongarra, Towards Achieving Performance Portability Using Directives for Accelerators,” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC'16), Third Workshop on Accelerator Programming Using Directives (WACCPD), Salt Lake City, Utah, Innovative Computing Laboratory, University of Tennessee, November 2016.  (567.02 KB)
Lopez, F., E. Chow, S. Tomov, and J. Dongarra, Asynchronous SGD for DNN Training on Shared-Memory Parallel Architectures,” Workshop on Scalable Deep Learning over Parallel And Distributed Infrastructures (ScaDL 2020), May 2020.  (188.51 KB)
Lopez, F., and T. Mary, Mixed Precision LU Factorization on GPU Tensor Cores: Reducing Data Movement and Memory Footprint,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-13: University of Tennessee, September 2020.  (409 KB)
London, K., S. Moore, P. Mucci, K. Seymour, and R. Luczak, The PAPI Cross-Platform Interface to Hardware Performance Counters,” Department of Defense Users' Group Conference Proceedings, Biloxi, Mississippi, June 2001.  (328.56 KB)
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)
Lively, C., X. Wu, V. Taylor, S. Moore, H-C. Chang, C-Y. Su, and K. Cameron, Power-Aware Prediction Models of Hybrid (MPI/OpenMP) Scientific Applications,” International Conference on Energy-Aware High Performance Computing (EnA-HPC 2011), Hamburg, Germany, September 2011.  (479.49 KB)
Lively, C., X. Wu, V. Taylor, S. Moore, H-C. Chang, and K. Cameron, Energy and performance characteristics of different parallel implementations of scientific applications on multicore systems,” International Journal of High Performance Computing Applications, vol. 25, no. 3, pp. 342-350, 00 2011.  (467.18 KB)
Lindquist, N., P. Luszczek, and J. Dongarra, Replacing Pivoting in Distributed Gaussian Elimination with Randomized Techniques,” 2020 IEEE/ACM 11th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), Atlanta, GA, IEEE, November 2020.  (184.6 KB)
Lindquist, N., M. Gates, P. Luszczek, and J. Dongarra, Threshold Pivoting for Dense LU Factorization,” ScalAH22: 13th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems , Dallas, Texas, IEEE, November 2022. DOI: 10.1109/ScalAH56622.2022.00010  (721.77 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)
Lindquist, N., P. Luszczek, and J. Dongarra, Generalizing Random Butterfly Transforms to Arbitrary Matrix Sizes : arXiv, December 2023.
Lindquist, N., P. Luszczek, and J. Dongarra, Using Additive Modifications in LU Factorization Instead of Pivoting,” 37th ACM International Conference on Supercomputing (ICS'23), Orlando, FL, ACM, June 2023. DOI: 10.1145/3577193.3593731  (624.18 KB)
Lindquist, N., P. Luszczek, and J. Dongarra, Accelerating Restarted GMRES with Mixed Precision Arithmetic,” IEEE Transactions on Parallel and Distributed Systems, June 2021. DOI: 10.1109/TPDS.2021.3090757  (572.4 KB)
Funk, Y., M. Götz, and H. Anzt, Prediction of Optimal Solvers for Sparse Linear Systems Using Deep Learning,” 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP), Philadelphia, PA, Society for Industrial and Applied Mathematics, pp. 14 - 24. DOI: 10.1137/1.978161197714110.1137/1.9781611977141.2
Li, J., G. Bosilca, A. Bouteiller, and B. Nicolae, Elastic deep learning through resilient collective operations,” SC-W 2023: Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, CO, ACM, November 2023. DOI: 10.1145/3624062.3626080
Li, Y., J. Dongarra, K. Seymour, and A. YarKhan, Request Sequencing: Enabling Workflow for Efficient Problem Solving in GridSolve,” International Conference on Grid and Cooperative Computing (GCC 2008) (submitted), Shenzhen, China, October 2008.  (1.64 MB)
Li, J., B. Nicolae, J. M. Wozniak, and G. Bosilca, Understanding Scalability and Fine-Grain Parallelism of Synchronous Data Parallel Training,” 2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC), Denver, CO, IEEE, November 2019. DOI: 10.1109/MLHPC49564.2019.00006  (696.89 KB)
Li, Y., and J. Dongarra, Request Sequencing: Enabling Workflow for Efficient Parallel Problem Solving in GridSolve,” ICL Technical Report, no. ICL-UT-08-01, April 2008.  (1.64 MB)
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)
Li, Y., J. Dongarra, and S. Tomov, A Note on Auto-tuning GEMM for GPUs,” 9th International Conference on Computational Science (ICCS 2009), no. 5544-5545, Baton Rouge, LA, pp. 884-892, May 2009. DOI: 10.1007/978-3-642-01970-8_89  (236.02 KB)
Lemariner, P., G. Bosilca, C. Coti, T. Herault, and J. Dongarra, Constructing Resilient Communication Infrastructure for Runtime Environments,” ParCo 2009, Lyon France, September 2009.
Lee, DW., and J. Dongarra, VisPerf: Monitoring Tool for Grid Computing,” Lecture Notes in Computer Science, vol. 2659: Springer Verlag, Heidelberg, pp. 233-243, 00 2003.  (835.09 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)
Le Fèvre, V., T. Herault, Y. Robert, A. Bouteiller, A. Hori, G. Bosilca, and J. Dongarra, Comparing the Performance of Rigid, Moldable, and Grid-Shaped Applications on Failure-Prone HPC Platforms,” Parallel Computing, vol. 85, pp. 1–12, July 2019. DOI: 10.1016/j.parco.2019.02.002  (865.18 KB)
,” 15th European PVM/MPI Users' Group Meeting, Recent Advances in Parallel Virtual Machine and Message Passing Interface, Lecture Notes in Computer Science, vol. 5205, Dublin Ireland, Springer Berlin, January 2008.
Langou, J., J. Langou, P. Luszczek, J. Kurzak, A. Buttari, and J. Dongarra, Exploiting the Performance of 32 bit Floating Point Arithmetic in Obtaining 64 bit Accuracy,” University of Tennessee Computer Science Tech Report, no. UT-CS-06-574, LAPACK Working Note #175, April 2006.  (221.39 KB)
Langou, J., Z. Chen, G. Bosilca, and J. Dongarra, Recovery Patterns for Iterative Methods in a Parallel Unstable Environment,” SIAM SISC (to appear), May 2007.  (241.36 KB)
Langou, J., and J. Dongarra, The Problem with the Linpack Benchmark Matrix Generator,” International Journal of High Performance Computing Applications, vol. 23, no. 1, pp. 5-14, 00 2009.  (136.41 KB)
Langou, J., B. Hoffman, and B. King, How LAPACK library enables Microsoft Visual Studio support with CMake and LAPACKE,” University of Tennessee Computer Science Technical Report (also LAWN 270), no. UT-CS-12-698, July 2012.  (501.53 KB)
Lacoste, X., M. Faverge, P. Ramet, S. Thibault, and G. Bosilca, Taking Advantage of Hybrid Systems for Sparse Direct Solvers via Task-Based Runtimes,” 23rd International Heterogeneity in Computing Workshop, IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (807.33 KB)
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Kurzak, J., P. Luszczek, M. Faverge, and J. Dongarra, Programming the LU Factorization for a Multicore System with Accelerators,” Proceedings of VECPAR’12, Kobe, Japan, April 2012.  (414.33 KB)
Kurzak, J., and J. Dongarra, Implementation of the Mixed-Precision High Performance LINPACK Benchmark on the CELL Processor,” University of Tennessee Computer Science Tech Report, no. UT-CS-06-580, LAPACK Working Note #177, September 2006.  (506.18 KB)
Kurzak, J., A. Buttari, P. Luszczek, and J. Dongarra, The PlayStation 3 for High Performance Scientific Computing,” Computing in Science and Engineering, pp. 80-83, January 2008.  (2.45 MB)
Kurzak, J., H. Ltaeif, J. Dongarra, and R. M. Badia, Scheduling Dense Linear Algebra Operations on Multicore Processors,” Concurrency and Computation: Practice and Experience, vol. 22, no. 1, pp. 15-44, January 2010.  (1.23 MB)
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., S. Tomov, and J. Dongarra, Autotuning GEMMs for Fermi,” University of Tennessee Computer Science Technical Report, UT-CS-11-671, (also Lawn 245), April 2011.  (397.45 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)
Kurzak, J., Y. Tsai, M. Gates, A. Abdelfattah, and J. Dongarra, Massively Parallel Automated Software Tuning,” 48th International Conference on Parallel Processing (ICPP 2019), Kyoto, Japan, ACM Press, August 2019. DOI: 10.1145/3337821.3337908  (911.88 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)
Kurzak, J., S. Tomov, and J. Dongarra, Autotuning GEMM Kernels for the Fermi GPU,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 11, November 2012. DOI: 10.1109/TPDS.2011.311  (742.5 KB)
Kurzak, J., and J. Dongarra, QR Factorization for the CELL Processor,” Scientific Programming, vol. 17, no. 1-2, pp. 31-42, 00 2010.  (194.95 KB)
Kurzak, J., H. Ltaeif, J. Dongarra, and R. M. Badia, Scheduling Linear Algebra Operations on Multicore Processors,” Concurrency Practice and Experience (to appear), 00 2009.  (716.18 KB)
Kurzak, J., P. Luszczek, M. Gates, I. Yamazaki, and J. Dongarra, Virtual Systolic Array for QR Decomposition,” 15th Workshop on Advances in Parallel and Distributed Computational Models, IEEE International Parallel & Distributed Processing Symposium (IPDPS 2013), Boston, MA, IEEE, May 2013. DOI: 10.1109/IPDPS.2013.119  (749.84 KB)
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)
Kurzak, J., A. Buttari, P. Luszczek, and J. Dongarra, The PlayStation 3 for High Performance Scientific Computing,” University of Tennessee Computer Science Technical Report, no. UT-CS-08-608, January 2008.  (2.45 MB)

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