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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)

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)

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)

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)

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)

Farhan, M. Al, A. Abdelfattah, S. Tomov, M. Gates, D. Sukkari, A. Haidar, R. Rosenberg, and J. Dongarra, “MAGMA Templates for Scalable Linear Algebra on Emerging Architectures,” The International Journal of High Performance Computing Applications, vol. 34, issue 6, pp. 645-658, November 2020.

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.

(7.84 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., 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)

(8.72 MB)

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)

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)

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.

(911.88 KB)

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)

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., S. Tomov, and J. Dongarra, “Matrix Multiplication on Batches of Small Matrices in Half and Half-Complex Precisions,” Journal of Parallel and Distributed Computing, vol. 145, pp. 188-201, November 2020.

(1.3 MB)

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), Rio de Janeiro, Brazil, IEEE, May 2019.

(480.73 KB)

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.

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.

(2.4 MB)

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)

Barry, D., H. Jagode, A. Danalis, and J. Dongarra, “Memory Traffic and Complete Application Profiling with PAPI Multi-Component Measurements,” 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), St. Petersburg, Florida, IEEE, August 2023.

(1.81 MB)

Barry, D., H. Jagode, A. Danalis, and J. Dongarra, Memory Traffic and Complete Application Profiling with PAPI Multi-Component Measurements , St. Petersburg, FL, 28th HIPS Workshop, May 2023.

(3.99 MB)

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)

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)

Marin, G., J. Dongarra, and D. Terpstra, “MIAMI: A Framework for Application Performance Diagnosis ,” IPASS-2014, Monterey, CA, IEEE, March 2014.

(1010.75 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)

Cayrols, S., J. Li, G. Bosilca, S. Tomov, A. Ayala, and J. Dongarra, “Mixed precision and approximate 3D FFTs: Speed for accuracy trade-off with GPU-aware MPI and run-time data compression,” ICL Technical Report, no. ICL-UT-22-04, May 2022.

(706.14 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)

Tsai, Y. M., P. Luszczek, and J. Dongarra, “Mixed-Precision Algorithm for Finding Selected Eigenvalues and Eigenvectors of Symmetric and Hermitian Matrices,” ICL Technical Report, no. ICL-UT-21-05, August 2021.

(3.93 MB)

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)

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.

(374.8 KB)

Haidar, A., H. Bayraktar, S. Tomov, J. Dongarra, and N. J. Higham, “Mixed-Precision Iterative Refinement using Tensor Cores on GPUs to Accelerate Solution of Linear Systems,” Proceedings of the Royal Society A, vol. 476, issue 2243, November 2020.

(2.24 MB)

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, 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)

Haidar, A., H. Bayraktar, S. Tomov, J. Dongarra, and N. J. Higham, “Mixed-Precision Solution of Linear Systems Using Accelerator-Based Computing,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-05: University of Tennessee, May 2020.

(1.03 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)

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.

(5.06 MB)

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.

(1.86 MB)

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)

Sharp, D., M. Stoyanov, S. Tomov, and J. Dongarra, “A More Portable HeFFTe: Implementing a Fallback Algorithm for Scalable Fourier Transforms,” ICL Technical Report, no. ICL-UT-21-04: University of Tennessee, August 2021.

(493.17 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)

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,” ICL Technical Report, no. ICL-UT-06-11, 00 2006.

(308.39 KB)

Snir, M., S. Otto, S. Huss-Lederman, D. Walker, and J. Dongarra, MPI - The Complete Reference, Volume 1: The MPI Core , Second, Cambridge, MA, USA, MIT Press, pp. 426, August 1998.