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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. DOI: 10.1109/IPDPSW59300.2023.00070  (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)
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)
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)
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. DOI: 10.1016/j.jpdc.2020.07.001  (1.3 MB)
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. DOI: 10.1145/3337821.3337908  (911.88 KB)
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. DOI: 10.1007/978-3-030-34356-9_37  (1.37 MB) (8.72 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)
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)
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. DOI: 10.1177/1094342020938421
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)
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)
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)
Tomov, S., J. Dongarra, A. Haidar, I. Yamazaki, T. Dong, T. Schulthess, and R. Solcà, MAGMA: A Breakthrough in Solvers for Eigenvalue Problems , San Jose, CA, GPU Technology Conference (GTC12), Presentation, May 2012.  (9.23 MB)
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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)
Agullo, E., C. Augonnet, J. Dongarra, M. Faverge, J. Langou, H. Ltaeif, and S. Tomov, “LU Factorization for Accelerator-Based Systems,” IEEE/ACS AICCSA 2011, Sharm-El-Sheikh, Egypt, December 2011.  (234.86 KB)
Bell, G., D. Bailey, A. H. Karp, J. Dongarra, and K. Walsh, “A Look Back on 30 Years of the Gordon Bell Prize,” International Journal of High Performance Computing and Networking, vol. 31, issue 6, pp. 469–484, 2017.
Anzt, H., T. Cojean, C. Yen-Chen, J. Dongarra, G. Flegar, P. Nayak, S. Tomov, Y. M. Tsai, and W. Wang, “Load-Balancing Sparse Matrix Vector Product Kernels on GPUs,” ACM Transactions on Parallel Computing, vol. 7, issue 1, March 2020. DOI: 10.1145/3380930  (5.67 MB)
Kurzak, J., M. Gates, A. Charara, A. YarKhan, I. Yamazaki, and J. Dongarra, “Linear Systems Solvers for Distributed-Memory Machines with GPU Accelerators,” Euro-Par 2019: Parallel Processing, vol. 11725: Springer, pp. 495–506, August 2019. DOI: 10.1007/978-3-030-29400-7_35
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)
Abdelfattah, A., H. Anzt, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, , and A. YarKhan, “Linear Algebra Software for Large-Scale Accelerated Multicore Computing,” Acta Numerica, vol. 25, pp. 1-160, May 2016. DOI: 10.1017/S0962492916000015
Cao, Q., Y. Pei, K. Akbudak, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, “Leveraging PaRSEC Runtime Support to Tackle Challenging 3D Data-Sparse Matrix Problems,” 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), Portland, OR, IEEE, May 2021.  (1.08 MB)
Kurzak, J., M. Gates, A. Charara, A. YarKhan, and J. Dongarra, “Least Squares Solvers for Distributed-Memory Machines with GPU Accelerators,” ACM International Conference on Supercomputing (ICS '19), Phoenix, Arizona, ACM, pp. 117–126, June 2019. DOI: https://dl.acm.org/doi/abs/10.1145/3330345.3330356  (1.63 MB)
Gates, M., A. Charara, J. Kurzak, A. YarKhan, I. Yamazaki, and J. Dongarra, “Least Squares Performance Report,” SLATE Working Notes, no. 09, ICL-UT-18-10: Innovative Computing Laboratory, University of Tennessee, December 2018.  (1.76 MB)
Yamazaki, I., and J. Dongarra, “LAWN 294: Aasen's Symmetric Inde nite Linear Solvers in LAPACK,” LAPACK Working Note, no. LAWN 294, ICL-UT-17-13: University of Tennessee, December 2017.  (854.1 KB)

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