Publications

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F
Kabir, K., A. Haidar, S. Tomov, A. Bouteiller, and J. Dongarra, A Framework for Out of Memory SVD Algorithms,” ISC High Performance 2017, pp. 158–178, June 2017. DOI: 10.1007/978-3-319-58667-0_9  (393.22 KB)
Jagode, H., A. Danalis, and J. Dongarra, Formulation of Requirements for New PAPI++ Software Package: Part I: Survey Results,” PAPI++ Working Notes, no. 1, ICL-UT-20-02: Innovative Computing Laboratory, University of Tennessee Knoxville, January 2020.  (1.49 MB)
Bosilca, G., A. Bouteiller, A. Danalis, M. Faverge, A. Haidar, T. Herault, J. Kurzak, J. Langou, P. Lemariner, H. Ltaeif, et al., Flexible Development of Dense Linear Algebra Algorithms on Massively Parallel Architectures with DPLASMA,” Proceedings of the Workshops of the 25th IEEE International Symposium on Parallel and Distributed Processing (IPDPS 2011 Workshops), Anchorage, Alaska, USA, IEEE, pp. 1432-1441, May 2011.  (1.26 MB)
Cao, Q., G. Bosilca, W. Wu, D. Zhong, A. Bouteiller, and J. Dongarra, Flexible Data Redistribution in a Task-Based Runtime System,” IEEE International Conference on Cluster Computing (Cluster 2020), Kobe, Japan, IEEE, September 2020. DOI: 10.1109/CLUSTER49012.2020.00032  (354.8 KB)
Anzt, H., G. Collins, J. Dongarra, G. Flegar, and E. S. Quintana-Orti, Flexible Batched Sparse Matrix-Vector Product on GPUs,” 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA '17), Denver, CO, ACM Press, November 2017. DOI: http://dx.doi.org/10.1145/3148226.3148230  (583.4 KB)
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)
Anzt, H., J. Dongarra, and E. S. Quintana-Orti, Fine-grained Bit-Flip Protection for Relaxation Methods,” Journal of Computational Science, November 2016. DOI: 10.1016/j.jocs.2016.11.013  (1.47 MB)
Tomov, S., A. Haidar, A. Ayala, H. Shaiek, and J. Dongarra, FFT-ECP Implementation Optimizations and Features Phase,” Innovative Computing Laboratory Technical Report, no. ICL-UT-19-12: University of Tennessee, October 2019.  (4.14 MB)
Tomov, S., A. Haidar, A. Ayala, D. Schultz, and J. Dongarra, FFT-ECP Fast Fourier Transform , Houston, TX, 2019 ECP Annual Meeting (Research Poster), January 2019.  (1.51 MB)
Tomov, S., A. Ayala, A. Haidar, and J. Dongarra, FFT-ECP API and High-Performance Library Prototype for 2-D and 3-D FFTs on Large-Scale Heterogeneous Systems with GPUs,” ECP Milestone Report, no. FFT-ECP STML13-27: Innovative Computing Laboratory, University of Tennessee, January 2020.  (9.71 MB)
Wang, L., W. Wu, J. Zhang, H. Liu, G. Bosilca, M. Herlihy, and R. Fonseca, FFT-Based Gradient Sparsification for the Distributed Training of Deep Neural Networks,” 9th International Symposium on High-Performance Parallel and Distributed Computing (HPDC 20), Stockholm, Sweden, ACM, June 2020. DOI: 10.1145/3369583.3392681  (4.72 MB)
Ayala, A., S. Tomov, P. Luszczek, S. Cayrols, G. Ragghianti, and J. Dongarra, FFT Benchmark Performance Experiments on Systems Targeting Exascale,” ICL Technical Report, no. ICL-UT-22-02, March 2022.  (5.87 MB)
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)
Agullo, E., C. Augonnet, J. Dongarra, H. Ltaeif, R. Namyst, S. Thibault, and S. Tomov, Faster, Cheaper, Better - A Hybridization Methodology to Develop Linear Algebra Software for GPUs,” LAPACK Working Note, no. 230, 00 2010.  (334.48 KB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, Fast Cholesky Factorization on GPUs for Batch and Native Modes in MAGMA,” Journal of Computational Science, vol. 20, pp. 85–93, May 2017. DOI: 10.1016/j.jocs.2016.12.009  (3.6 MB)
Abdelfattah, A., S. Tomov, and J. Dongarra, Fast Batched Matrix Multiplication for Small Sizes using Half Precision Arithmetic on GPUs,” 33rd IEEE International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, IEEE, May 2019.  (675.5 KB)
Alvaro, W., J. Kurzak, and J. Dongarra, Fast and Small Short Vector SIMD Matrix Multiplication Kernels for the CELL Processor,” University of Tennessee Computer Science Technical Report, no. UT-CS-08-609, (also LAPACK Working Note 189), January 2008.  (500.99 KB)
Bosilca, G., A. Bouteiller, A. Guermouche, T. Herault, Y. Robert, P. Sens, and J. Dongarra, A Failure Detector for HPC Platforms,” The International Journal of High Performance Computing Applications, vol. 32, issue 1, pp. 139–158, January 2018. DOI: 10.1177/1094342017711505  (1.04 MB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, Factorization and Inversion of a Million Matrices using GPUs: Challenges and Countermeasures,” Procedia Computer Science, vol. 108, pp. 606–615, June 2017. DOI: 10.1016/j.procs.2017.05.250  (643.44 KB)
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Cao, Q., Y. Pei, K. Akbudak, A. Mikhalev, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, Extreme-Scale Task-Based Cholesky Factorization Toward Climate and Weather Prediction Applications,” Platform for Advanced Scientific Computing Conference (PASC20), Geneva, Switzerland, ACM, June 2020. DOI: 10.1145/3394277.3401846  (2.71 MB)
Fortenberry, A., S. Tomov, and K. Wong, Extending MAGMA Portability with OneAPI , Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC22), ACM Student Research Competition, November 2022.  (1.33 MB)
Fortenberry, A., and S. Tomov, Extending MAGMA Portability with OneAPI,” The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC22), Ninth Workshop on Accelerator Programming Using Directives (WACCPD 2022), Dallas, TX, November 2022.  (999.19 KB)
Dongarra, J., S. Moore, G. D. Peterson, S. Tomov, J. Allred, V. Natoli, and D. Richie, Exploring New Architectures in Accelerating CFD for Air Force Applications,” Proceedings of the DoD HPCMP User Group Conference, Seattle, Washington, January 2008.  (492.86 KB)
Dongarra, J., M. Faverge, H. Ltaeif, and P. Luszczek, Exploiting Fine-Grain Parallelism in Recursive LU Factorization,” Proceedings of PARCO'11, no. ICL-UT-11-04, Gent, Belgium, April 2011.
Iqbal, Z., S. Nooshabadi, I. Yamazaki, S. Tomov, and J. Dongarra, Exploiting Block Structures of KKT Matrices for Efficient Solution of Convex Optimization Problems,” IEEE Access, 2021. DOI: 10.1109/ACCESS.2021.3106054  (1.35 MB)

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