Publications

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Benoit, A., A. Cavelan, Y. Robert, and H. Sun, Multi-Level Checkpointing and Silent Error Detection for Linear Workflows,” Journal of Computational Science, vol. 28, pp. 398–415, September 2018.
Bouteiller, A., F. Cappello, J. Dongarra, A. Guermouche, T. Herault, and Y. Robert, Multi-criteria Checkpointing Strategies: Response-Time versus Resource Utilization,” Euro-Par 2013, Aachen, Germany, Springer, August 2013.  (431.84 KB)
Bouteiller, A., F. Cappello, J. Dongarra, A. Guermouche, T. Herault, and Y. Robert, Multi-criteria checkpointing strategies: optimizing response-time versus resource utilization,” University of Tennessee Computer Science Technical Report, no. ICL-UT-13-01, February 2013.  (497.64 KB)
Danalis, A., L. Pollock, M. Swany, and J. Cavazos, MPI-aware Compiler Optimizations for Improving Communication-Computation Overlap,” Proceedings of the 23rd annual International Conference on Supercomputing (ICS '09), Yorktown Heights, NY, USA, ACM, pp. 316-325, June 2009.  (308.92 KB)
Pjesivac–Grbovic, J., G. Fagg, T. Angskun, G. Bosilca, and J. Dongarra, MPI Collective Algorithm Selection and Quadtree Encoding,” ICL Technical Report, no. ICL-UT-06-11, 00 2006.  (308.39 KB)
Pjesivac–Grbovic, J., G. Bosilca, G. Fagg, T. Angskun, and J. Dongarra, MPI Collective Algorithm Selection and Quadtree Encoding,” Parallel Computing (Special Edition: EuroPVM/MPI 2006): Elsevier, 00 2007.  (308.39 KB)
Pjesivac–Grbovic, J., G. Fagg, T. Angskun, G. Bosilca, and J. Dongarra, MPI Collective Algorithm Selection and Quadtree Encoding,” Lecture Notes in Computer Science, vol. 4192, no. ICL-UT-06-13: Springer Berlin / Heidelberg, pp. 40-48, September 2006.  (308.39 KB)
Supinski, B. R. de, S. Alam, D. Bailey, L. Carrington, C. Daley, A. Dubey, T. Gamblin, D. Gunter, P. D. Hovland, H. Jagode, et al., Modeling the Office of Science Ten Year Facilities Plan: The PERI Architecture Tiger Team,” SciDAC 2009, Journal of Physics: Conference Series, vol. 180(2009)012039, San Diego, California, IOP Publishing, July 2009.  (906.39 KB)
Song, F., S. Moore, and J. Dongarra, Modeling of L2 Cache Behavior for Thread-Parallel Scientific Programs on Chip Multi-Processors,” University of Tennessee Computer Science Technical Report, no. UT-CS-06-583, January 2006.  (652.93 KB)
Dongarra, J., A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and A. YarKhan, Model-Driven One-Sided Factorizations on Multicore, Accelerated Systems,” Supercomputing Frontiers and Innovations, vol. 1, issue 1, 2014. DOI: http://dx.doi.org/10.14529/jsfi1401  (1.86 MB)
Faverge, M., J. Herrmann, J. Langou, B. Lowery, Y. Robert, and J. Dongarra, Mixing LU-QR Factorization Algorithms to Design High-Performance Dense Linear Algebra Solvers,” Journal of Parallel and Distributed Computing, vol. 85, pp. 32-46, November 2015. DOI: doi:10.1016/j.jpdc.2015.06.007  (5.06 MB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, Mixed-Tool Performance Analysis on Hybrid Multicore Architectures,” First International Workshop on Parallel Software Tools and Tool Infrastructures (PSTI 2010), San Diego, CA, September 2010.  (1.24 MB)
Yamazaki, I., S. Tomov, T. Dong, and J. Dongarra, Mixed-precision orthogonalization scheme and adaptive step size for CA-GMRES on GPUs,” VECPAR 2014 (Best Paper), Eugene, OR, June 2014.  (438.54 KB)
Yamazaki, I., J. Barlow, S. Tomov, J. Kurzak, and J. Dongarra, Mixed-precision orthogonalization process Performance on multicore CPUs with GPUs,” 2015 SIAM Conference on Applied Linear Algebra, Atlanta, GA, SIAM, October 2015.  (301.01 KB)
Yamazaki, I., S. Tomov, and J. Dongarra, Mixed-Precision Cholesky QR Factorization and its Case Studies on Multicore CPU with Multiple GPUs,” SIAM Journal on Scientific Computing, vol. 37, no. 3, pp. C203-C330, May 2015. DOI: DOI:10.1137/14M0973773  (374.8 KB)
Yamazaki, I., S. Tomov, J. Kurzak, J. Dongarra, and J. Barlow, Mixed-precision Block Gram Schmidt Orthogonalization,” 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Austin, TX, ACM, November 2015.  (235.69 KB)
Buttari, A., J. Dongarra, J. Langou, J. Langou, P. Luszczek, and J. Kurzak, Mixed Precision Iterative Refinement Techniques for the Solution of Dense Linear Systems,” International Journal of High Performance Computer Applications (to appear), August 2007.  (157.4 KB)
Beck, M., D. Arnold, A. Bassi, F. Berman, H. Casanova, J. Dongarra, T. Moore, G. Obertelli, J. Plank, M. Swany, et al., Middleware for the Use of Storage in Communication,” Parallel Computing, vol. 28, no. 12, pp. 1773-1788, August 2002.  (87.97 KB)
Marin, G., J. Dongarra, and D. Terpstra, MIAMI: A Framework for Application Performance Diagnosis ,” IPASS-2014, Monterey, CA, IEEE, March 2014. DOI: 10.1109/ISPASS.2014.6844480  (1010.75 KB)
Vadhiyar, S., and J. Dongarra, A Metascheduler For The Grid,” Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing (HPDC 2002), Edinburgh, Scotland, IEEE Computer Society, pp. 343-351, July 2002.  (99.53 KB)
Moore, S., D. Arnold, and D. Cronk, Metacomputing Support for the SARA3D Structural Acoustics Application,” Department of Defense Users' Group Conference (to appear), Biloxi, Mississippi, June 2001.  (64.58 KB)
Cronk, D., B. Ellis, and G. Fagg, Metacomputing: An Evaluation of Emerging Systems,” University of Tennessee Computer Science Department Technical Report, no. UT-CS-00-445, July 2000.  (280.21 KB)
Dongarra, J., G. Fagg, R. Hempel, and D. W. Walker, Message Passing Software Systems,” Encyclopedia of Electrical and Engineering, Supplement 1: John Wiley & Sons, Inc., 00 2000.  (289.38 KB)
Shende, S., A. D. Malony, S. Moore, and D. Cronk, Memory Leak Detection in Fortran Applications using TAU,” Proc. DoD HPCMP Users Group Conference (HPCMP-UGC'07), Pittsburgh, PA, IEEE Computer Society, January 2007.
Mucci, P., Memory Bandwidth and the Performance of Scientific Applications: A Study of the AMD Opteron Processor,” 2005 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) (submitted), January 2004.  (210.29 KB)
Weaver, V. M., M. Johnson, K. Kasichayanula, J. Ralph, P. Luszczek, D. Terpstra, and S. Moore, Measuring Energy and Power with PAPI,” International Workshop on Power-Aware Systems and Architectures, Pittsburgh, PA, September 2012. DOI: 10.1109/ICPPW.2012.39  (146.79 KB)
Dongarra, J., Measuring Computer Performance: A Practioner's Guide,” SIAM Review (book review), vol. 43, no. 2, pp. 383-384, 00 2001.  (558.9 KB)
Haidar, A., S. Tomov, A. Abdelfattah, I. Yamazaki, and J. Dongarra, MAtrix, TEnsor, and Deep-learning Optimized Routines (MATEDOR) , Washington, DC, NSF PI Meeting, Poster, April 2018. DOI: 10.6084/m9.figshare.6174143.v3  (2.4 MB)
Dongarra, J., J-F. Pineau, Y. Robert, and F. Vivien, Matrix Product on Heterogeneous Master Worker Platforms,” 2008 PPoPP Conference, Salt Lake City, Utah, January 2008.
Bai, Z., J. Dongarra, D. Lu, and I. Yamazaki, Matrix Powers Kernels for Thick-Restart Lanczos with Explicit External Deflation,” International Parallel and Distributed Processing Symposium (IPDPS), May 2019.
Tomov, S., Matrix Algebra on GPU and Multicore Architectures , Basel, Switzerland, Workshop on GPU-enabled Numerical Libraries, Presentation, May 2011.  (49.27 MB)
Agullo, E., G. Bosilca, C. Castagnède, J. Dongarra, H. Ltaeif, and S. Tomov, Matrices Over Runtime Systems at Exascale,” Supercomputing '12 (poster), Salt Lake City, Utah, November 2012.
Abdelfattah, A., J. Dongarra, A. Haidar, S. Tomov, and I. Yamazaki, MATEDOR: MAtrix, TEnsor, and Deep-learning Optimized Routines , Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Research Poster, November 2018.  (2.55 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.
Strohmaier, E., J. Dongarra, H. Meuer, and H. D. Simon, The Marketplace for High-Performance Computers,” Parallel Computing, vol. 25, no. 13-14, pp. 1517-1545, October 2002.  (285.78 KB)
Agullo, E., L. Giraud, A. Guermouche, A. Haidar, J. Roman, and Y. Lee-Tin-Yien, MaPHyS or the Development of a Parallel Algebraic Domain Decomposition Solver in the Course of the Solstice Project,” Sparse Days 2010 Meeting at CERFACS, Toulouse, France, June 2010.
Portillo, R., P. J. Teller, D. Cronk, and S. Moore, Making Performance Analysis and Tuning Part of the Software Development Cycle,” Proceedings of DoD HPCMP UGC 2009, San Diego, CA, IEEE, June 2009.
Anzt, H., E. Boman, J. Dongarra, G. Flegar, M. Gates, M. Heroux, M. Hoemmen, J. Kurzak, P. Luszczek, S. Rajamanickam, et al., MAGMA-sparse Interface Design Whitepaper,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-05, September 2017.  (1.28 MB)
Nichols, D., N-S. Tomov, F. Betancourt, S. Tomov, K. Wong, and J. Dongarra, MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing,” ISC High Performance, Frankfurt, Germany, Springer International Publishing, June 2019.  (1.37 MB)
Ng, L., K. Wong, A. Haidar, S. Tomov, and J. Dongarra, MagmaDNN – High-Performance Data Analytics for Manycore GPUs and CPUs , Knoxville, TN, 2017 Summer Research Experiences for Undergraduate (REU), Presentation, December 2017.  (5.06 MB)
Nichols, D., K. Wong, S. Tomov, L. Ng, S. Chen, and A. Gessinger, MagmaDNN: Accelerated Deep Learning Using MAGMA,” Practice and Experience in Advanced Research Computing (PEARC ’19), Chicago, IL, ACM, July 2019.  (1.09 MB)
Ng, L., S. Chen, A. Gessinger, D. Nichols, S. Cheng, A. Meenasorna, K. Wong, S. Tomov, A. Haidar, E. D'Azevedo, et al., MagmaDNN 0.2 High-Performance Data Analytics for Manycore GPUs and CPUs : University of Tennessee, January 2019. DOI: 10.13140/RG.2.2.14906.64961  (7.84 MB)
Gates, M., MAGMA Tutorial , Atlanta, GA, Keeneland Workshop, February 2012.  (2.47 MB)
Tomov, S., and A. Haidar, MAGMA Tensors and Batched Computing for Accelerating Applications on GPUs , San Jose, CA, GPU Technology Conference (GTC17), Presentation in Session S7728, May 2017.  (11.12 MB)
Anzt, H., J. Dongarra, M. Gates, A. Haidar, K. Kabir, P. Luszczek, S. Tomov, and I. Yamazaki, MAGMA MIC: Optimizing Linear Algebra for Intel Xeon Phi , Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, June 2015.  (2.03 MB)
Dongarra, J., M. Gates, Y. Jia, K. Kabir, P. Luszczek, and S. Tomov, MAGMA MIC: Linear Algebra Library for Intel Xeon Phi Coprocessors , Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), November 2012.  (6.4 MB)
Tomov, S., and J. Dongarra, MAGMA - LAPACK for HPC on Heterogeneous Architectures , Oak Ridge, TN, Titan Summit at Oak Ridge National Laboratory, Presentation, August 2011.  (20.43 MB)
Tomov, S., MAGMA - LAPACK for GPUs , Atlanta, GA, Keeneland GPU Tutorial, April 2011.  (742.14 KB)
Haidar, A., S. Tomov, P. Luszczek, and J. Dongarra, MAGMA Embedded: Towards a Dense Linear Algebra Library for Energy Efficient Extreme Computing,” 2015 IEEE High Performance Extreme Computing Conference (HPEC ’15), (Best Paper Award), Waltham, MA, IEEE, September 2015.  (678.86 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)

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