Publications

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Poster
Nath, R., J. Dongarra, S. Tomov, H. Ltaeif, and P. Du, Numerical Linear Algebra on Hybrid Architectures: Recent Developments in the MAGMA Project , Portland, Oregon, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC09), November 2009.  (1.41 MB)
Abdelfattah, A., S. Tomov, and J. Dongarra, Optimizing Batch HGEMM on Small Sizes Using Tensor Cores , San Jose, CA, GPU Technology Conference (GTC), March 2019.  (2.47 MB)
Dongarra, J., H. Jagode, A. Danalis, D. Barry, and V. Weaver, Performance Application Programming Interface for Extreme-Scale Environments (PAPI-EX) (Poster) , Seattle, WA, 2020 NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) Principal Investigator Meeting, 20 2020.  (2.53 MB)
Luszczek, P., and J. Dongarra, The PLASMA Library on CORAL Systems and Beyond (Poster) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (550.86 KB)
Agullo, E., C. Augonnet, J. Dongarra, H. Ltaeif, R. Namyst, R. Nath, J. Roman, S. Thibault, and S. Tomov, Scheduling Cholesky Factorization on Multicore Architectures with GPU Accelerators , Knoxville, TN, 2010 Symposium on Application Accelerators in High-Performance Computing (SAAHPC'10), Poster, July 2010.  (3.86 MB)
Gates, M., A. Charara, J. Kurzak, A. YarKhan, M. Al Farhan, D. Sukkari, and J. Dongarra, SLATE: Software for Linear Algebra Targeting Exascale (POSTER) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (546.56 KB)
Valero-Lara, P., J. Dongarra, A. Haidar, S. D. Relton, S. Tomov, and M. Zounon, A Standard for Batched BLAS Routines , Paris, France, 17th SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP16), April 2016.  (1.93 MB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, Tensor Contractions using Optimized Batch GEMM Routines , San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.  (1.64 MB)
Baboulin, M., V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, T. Kolev, I. Masliah, and S. Tomov, Towards a High-Performance Tensor Algebra Package for Accelerators , Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC15), September 2015.  (1.76 MB)
Zhong, D., G. Bosilca, Q. Cao, and J. Dongarra, Using Advanced Vector Extensions AVX-512 for MPI Reduction (Poster) , Austin, TX, EuroMPI/USA '20: 27th European MPI Users' Group Meeting, September 2020.  (708.68 KB)
Haidar, A., S. Tomov, A. Abdelfattah, M. Zounon, and J. Dongarra, Using GPU FP16 Tensor Cores Arithmetic to Accelerate Mixed-Precision Iterative Refinement Solvers and Reduce Energy Consumption , Frankfurt, Germany, ISC High Performance (ISC18), Best Poster Award, June 2018.  (3.01 MB)
Tsai, Y., P. Luszczek, and J. Dongarra, Using Quantized Integer in LU Factorization with Partial Pivoting (Poster) , Seattle, WA, SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP20), February 2020.  (6.65 MB)
Preprint
Reed, D., and J. Dongarra, “ Exascale Computing and Big Data,” Communications of the ACM, vol. 58, no. 7: ACM, pp. 56-68, July 2015.  (7.3 MB)
Lindquist, N., P. Luszczek, and J. Dongarra, Generalizing Random Butterfly Transforms to Arbitrary Matrix Sizes : arXiv, December 2023.
Brown, C., A. Abdelfattah, S. Tomov, and J. Dongarra, hipMAGMA v1.0 : Zenodo, March 2020.
Brown, C., A. Abdelfattah, S. Tomov, and J. Dongarra, hipMAGMA v2.0 : Zenodo, July 2020.
Dongarra, J., The HPL Benchmark: Past, Present & Future , ISC High Performance, Frankfurt, Germany, July 2016.  (3.41 MB)
Hoefler, T., M. Copik, P. Beckman, A. Jones, I. Foster, M. Parashar, D. Reed, M. Troyer, T. Schulthess, D. Ernst, et al., XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing : arXiv, January 2024.
Presentation
Abdelfattah, A., M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, T. Kolev, I. Masliah, et al., Accelerating Tensor Contractions in High-Order FEM with MAGMA Batched , Atlanta, GA, SIAM Conference on Computer Science and Engineering (SIAM CSE17), Presentation, March 2017.  (9.29 MB)
Nath, R., S. Tomov, E. Agullo, and J. Dongarra, Autotuning Dense Linear Algebra Libraries on GPUs , Basel, Switzerland, Sixth International Workshop on Parallel Matrix Algorithms and Applications (PMAA 2010), June 2010.  (579.44 KB)
Yamazaki, I., M. Hoemmen, P. Luszczek, and J. Dongarra, Comparing performance of s-step and pipelined GMRES on distributed-memory multicore CPUs , Pittsburgh, Pennsylvania, SIAM Annual Meeting, July 2017.  (748 KB)
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)
Anzt, H., G. Collins, J. Dongarra, G. Flegar, and E. S. Quintana-Orti, Flexible Batched Sparse Matrix Vector Product on GPUs , Denver, Colorado, ScalA'17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, November 2017.  (16.8 MB)
Tomov, S., and J. Dongarra, The Future of Computing: Software Libraries , Savannah, GA, DOD CREATE Developers' Review, Keynote Presentation, February 2012.  (6.76 MB)
Tomov, S., K. Wong, J. Dongarra, R. Archibald, E. Chow, E. D'Azevedo, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, et al., Integrating Deep Learning in Domain Science at Exascale (MagmaDNN) , virtual, DOD HPCMP seminar, December 2020.  (11.12 MB)
Dongarra, J., and S. Tomov, An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra : NVIDIA Webinar, June 2010.
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)
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., 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)
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)
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)
Danalis, A., H. Jagode, and J. Dongarra, PAPI: Counting outside the Box , Barcelona, Spain, 8th JLESC Meeting, April 2018.
Jagode, H., A. Danalis, and J. Dongarra, PAPI's New Software-Defined Events for In-Depth Performance Analysis , Lyon, France, CCDSC 2018: Workshop on Clusters, Clouds, and Data for Scientific Computing, September 2018.
Danalis, A., H. Jagode, and J. Dongarra, PAPI's new Software-Defined Events for in-depth Performance Analysis , Dresden, Germany, 13th Parallel Tools Workshop, September 2019.  (3.14 MB)
Haidar, A., H. Jagode, A. YarKhan, P. Vaccaro, S. Tomov, and J. Dongarra, Power-Aware HPC on Intel Xeon Phi KNL Processors , Frankfurt, Germany, ISC High Performance (ISC17), Intel Booth Presentation, June 2017.  (5.87 MB)
Gates, M., J. Kurzak, A. Charara, A. YarKhan, and J. Dongarra, SLATE: Design of a Modern Distributed and Accelerated Linear Algebra Library , Denver, CO, International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), November 2019.  (16.19 MB)
Gates, M., J. Kurzak, A. YarKhan, A. Charara, J. Finney, D. Sukkari, M. Al Farhan, I. Yamazaki, P. Wu, and J. Dongarra, SLATE Tutorial , Houston, TX, 2020 ECP Annual Meeting, February 2020.  (12.14 MB)
Danalis, A., H. Jagode, and J. Dongarra, Software-Defined Events through PAPI for In-Depth Analysis of Application Performance , Basel, Switzerland, 5th Platform for Advanced Scientific Computing Conference (PASC18), July 2018.
Danalis, A., H. Jagode, D. Barry, and J. Dongarra, Understanding Native Event Semantics , Knoxville, TN, 9th JLESC Workshop, April 2019.  (2.33 MB)
Jagode, H., A. Danalis, and J. Dongarra, What it Takes to keep PAPI Instrumental for the HPC Community , Collegeville, MN, The 2019 Collegeville Workshop on Sustainable Scientific Software (CW3S19), July 2019.  (3.29 MB)
Danalis, A., H. Jagode, and J. Dongarra, Is your scheduling good? How would you know? , Bordeaux, France, 14th Scheduling for Large Scale Systems Workshop, June 2019.  (2.5 MB)
Report
Dongarra, J., I. Duff, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Hogg, P. Valero Lara, P. Luszczek, M. Zounon, et al., Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification , July 2018.  (483.05 KB)
Reed, D., D. Gannon, and J. Dongarra, “Reinventing High Performance Computing: Challenges and Opportunities,” ICL Technical Report, no. ICL-UT-22-03, March 2022.  (1.36 MB)
Tech Report
Dongarra, J., J. Demmel, J. Langou, and J. Langou, “2016 Dense Linear Algebra Software Packages Survey,” University of Tennessee Computer Science Technical Report, no. UT-EECS-16-744 / LAWN 290: University of Tennessee, September 2016.  (366.43 KB)
Anzt, H., S. Tomov, and J. Dongarra, “Accelerating the LOBPCG method on GPUs using a blocked Sparse Matrix Vector Product,” University of Tennessee Computer Science Technical Report, no. UT-EECS-14-731: University of Tennessee, October 2014.  (1.83 MB)
Tomov, S., and J. Dongarra, “Accelerating the Reduction to Upper Hessenberg Form through Hybrid GPU-Based Computing,” University of Tennessee Computer Science Technical Report, UT-CS-09-642 (also LAPACK Working Note 219), May 2009.  (2.37 MB)
Dongarra, J., M. Faverge, H. Ltaeif, and P. Luszczek, “Achieving Numerical Accuracy and High Performance using Recursive Tile LU Factorization,” University of Tennessee Computer Science Technical Report (also as a LAWN), no. ICL-UT-11-08, September 2011.  (618.53 KB)

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