Publications

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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)
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
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)
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, A Fast Batched Cholesky Factorization on a GPU,” International Conference on Parallel Processing (ICPP-2014), Minneapolis, MN, September 2014.  (1.37 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
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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)
Buttari, A., J. Dongarra, J. Kurzak, J. Langou, J. Langou, P. Luszczek, and S. Tomov, Exploiting Mixed Precision Floating Point Hardware in Scientific Computations,” In High Performance Computing and Grids in Action (to appear), Amsterdam, IOS Press, 00 2007.  (122.01 KB)
Buttari, A., J. Dongarra, J. Kurzak, J. Langou, J. Langou, P. Luszczek, and S. Tomov, Exploiting Mixed Precision Floating Point Hardware in Scientific Computations,” in High Performance Computing and Grids in Action, Amsterdam, IOS Press, January 2008.  (92.95 KB)
Lopez, M. G., W. Joubert, V. Larrea, O. Hernandez, A. Haidar, S. Tomov, and J. Dongarra, Evaluation of Directive-Based Performance Portable Programming Models,” International Journal of High Performance Computing and Networking (to appear), 2019. DOI: 10.1504/IJHPCN.2017.10009064
Lopez, M. G., V. Larrea, W. Joubert, O. Hernandez, A. Haidar, S. Tomov, and J. Dongarra, Evaluation of Directive-based Performance Portable Programming Models,” International Journal of High Performance Computing and Networking (IJHPCN), vol. (In Press).
Tomov, S., A. Haidar, D. Schultz, and J. Dongarra, Evaluation and Design of FFT for Distributed Accelerated Systems,” ECP WBS 2.3.3.09 Milestone Report, no. FFT-ECP ST-MS-10-1216: Innovative Computing Laboratory, University of Tennessee, October 2018.  (7.53 MB)
Baboulin, M., J. Demmel, J. Dongarra, S. Tomov, and V. Volkov, Enhancing the Performance of Dense Linear Algebra Solvers on GPUs (in the MAGMA Project) , Austin, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC08), November 2008.  (5.28 MB)
Anzt, H., S. Tomov, and J. Dongarra, Energy Efficiency and Performance Frontiers for Sparse Computations on GPU Supercomputers,” Sixth International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM '15), San Francisco, CA, ACM, February 2015. DOI: 10.1145/2712386.2712387  (2.29 MB)
Song, F., S. Tomov, and J. Dongarra, Enabling and Scaling Matrix Computations on Heterogeneous Multi-Core and Multi-GPU Systems,” 26th ACM International Conference on Supercomputing (ICS 2012), San Servolo Island, Venice, Italy, ACM, June 2012.  (5.88 MB)
Song, F., S. Tomov, and J. Dongarra, Efficient Support for Matrix Computations on Heterogeneous Multi-core and Multi-GPU Architectures,” University of Tennessee Computer Science Technical Report, UT-CS-11-668, (also Lawn 250), June 2011.  (5.93 MB)
Solcà, R., A. Kozhevnikov, A. Haidar, S. Tomov, T. C. Schulthess, and J. Dongarra, Efficient Implementation Of Quantum Materials Simulations On Distributed CPU-GPU Systems,” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC15), Austin, TX, ACM, November 2015.  (1.09 MB)
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, Efficient Eigensolver Algorithms on Accelerator Based Architectures,” 2015 SIAM Conference on Applied Linear Algebra (SIAM LA), Atlanta, GA, SIAM, October 2015.  (6.98 MB)
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Donfack, S., S. Tomov, and J. Dongarra, Dynamically balanced synchronization-avoiding LU factorization with multicore and GPUs,” University of Tennessee Computer Science Technical Report, no. ut-cs-13-713, July 2013.  (659.77 KB)
Donfack, S., S. Tomov, and J. Dongarra, Dynamically balanced synchronization-avoiding LU factorization with multicore and GPUs,” Fourth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), IPDPS 2014, May 2014.  (490.08 KB)
Yamazaki, I., S. Rajamanickam, E. G. Boman, M. Hoemmen, M. A. Heroux, and S. Tomov, Domain Decomposition Preconditioners for Communication-Avoiding Krylov Methods on a Hybrid CPU/GPU Cluster,” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC 14), New Orleans, LA, IEEE, November 2014.
Voemel, C., S. Tomov, and J. Dongarra, Divide & Conquer on Hybrid GPU-Accelerated Multicore Systems,” SIAM Journal on Scientific Computing (submitted), August 2010.
Voemel, C., S. Tomov, and J. Dongarra, Divide and Conquer on Hybrid GPU-Accelerated Multicore Systems,” SIAM Journal on Scientific Computing, vol. 34(2), pp. C70-C82, April 2012.
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, On the Development of Variable Size Batched Computation for Heterogeneous Parallel Architectures,” The 17th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC 2016), IPDPS 2016, Chicago, IL, IEEE, May 2016.  (708.62 KB)
Haidar, A., A. Abdelfattah, M. Zounon, P. Wu, S. Pranesh, S. Tomov, and J. Dongarra, The Design of Fast and Energy-Efficient Linear Solvers: On the Potential of Half-Precision Arithmetic and Iterative Refinement Techniques,” International Conference on Computational Science (ICCS 2018), vol. 10860, Wuxi, China, Springer, pp. 586–600, June 2018. DOI: 10.1007/978-3-319-93698-7_45
Kabir, K., A. Haidar, S. Tomov, and J. Dongarra, On the Design, Development, and Analysis of Optimized Matrix-Vector Multiplication Routines for Coprocessors,” ISC High Performance 2015, Frankfurt, Germany, July 2015.  (1.49 MB)
Tomov, S., A. Haidar, A. Ayala, D. Schultz, and J. Dongarra, Design and Implementation for FFT-ECP on Distributed Accelerated Systems,” Innovative Computing Laboratory Technical Report, no. ICL-UT-19-05: University of Tennessee, April 2019.  (3.19 MB)
Baboulin, M., J. Dongarra, A. Remy, S. Tomov, and I. Yamazaki, Dense Symmetric Indefinite Factorization on GPU Accelerated Architectures,” Lecture Notes in Computer Science, vol. 9573: Springer International Publishing, pp. 86-95, September 2015, 2016. DOI: 10.1007/978-3-319-32149-3_9  (327.14 KB)
Tomov, S., Dense Linear Algebra Solvers for Multicore with GPU Accelerators , Atlanta, GA, International Parallel and Distributed Processing Symposium (IPDPS 2010), April 2010.  (956.68 KB)
Tomov, S., R. Nath, H. Ltaeif, and J. Dongarra, Dense Linear Algebra Solvers for Multicore with GPU Accelerators,” Parallel Distributed Processing, Workshops and Phd Forum (IPDPSW), 2010 IEEE International Symposium on, Atlanta, GA, pp. 1-8, 2010. DOI: 10.1109/IPDPSW.2010.5470941  (1 MB)
Dongarra, J., J. Kurzak, P. Luszczek, and S. Tomov, Dense Linear Algebra on Accelerated Multicore Hardware,” High Performance Scientific Computing: Algorithms and Applications, London, UK, Springer-Verlag, 00 2012.
Tomov, S., and J. Dongarra, Dense Linear Algebra for Hybrid GPU-based Systems,” Scientific Computing with Multicore and Accelerators, Boca Raton, Florida, CRC Press, 2010.
Yamazaki, I., S. Tomov, and J. Dongarra, Deflation Strategies to Improve the Convergence of Communication-Avoiding GMRES,” 5th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, New Orleans, LA, November 2014.  (465.52 KB)
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Tomov, S., J. Langou, J. Dongarra, A. Canning, and L-W. Wang, Conjugate-Gradient Eigenvalue Solvers in Computing Electronic Properties of Nanostructure Architectures,” International Journal of Computational Science and Engineering, vol. 2, no. 3/4, pp. 205-212, 00 2006.  (428.21 KB)
Tomov, S., J. Langou, A. Canning, L-W. Wang, and J. Dongarra, Conjugate-Gradient Eigenvalue Solvers in Computing Electronic Properties of Nanostructure Architectures,” International Journal of Computational Science and Engineering (to appear), January 2005.  (428.21 KB)
Yamazaki, I., S. Tomov, and J. Dongarra, Computing Low-rank Approximation of a Dense Matrix on Multicore CPUs with a GPU and its Application to Solving a Hierarchically Semiseparable Linear System of Equations,” Scientific Programming, 2015.  (648.87 KB)
Sun, J., J. Fu, J. Drake, Q. Zhu, A. Haidar, M. Gates, S. Tomov, and J. Dongarra, Computational Benefit of GPU Optimization for Atmospheric Chemistry Modeling,” Journal of Advances in Modeling Earth Systems, vol. 10, issue 8, pp. 1952–1969, August 2018. DOI: 10.1029/2018MS001276
Tomov, S., J. Langou, A. Canning, L-W. Wang, and J. Dongarra, Comparison of Nonlinear Conjugate-Gradient methods for computing the Electronic Properties of Nanostructure Architectures,” Proceedings of 5th International Conference on Computational Science (ICCS), Atlanta, GA, USA, Springer's Lecture Notes in Computer Science, pp. 317-325, January 2005.  (172.86 KB)
Gates, M., S. Tomov, and A. Haidar, Comparing Hybrid CPU-GPU and Native GPU-only Acceleration for Linear Algebra,” 2015 SIAM Conference on Applied Linear Algebra, Atlanta, GA, SIAM, October 2015.  (4.7 MB)
Cao, C., J. Dongarra, P. Du, M. Gates, P. Luszczek, and S. Tomov, clMAGMA: High Performance Dense Linear Algebra with OpenCL ,” International Workshop on OpenCL, Bristol University, England, May 2014.  (460.91 KB)
Cao, C., J. Dongarra, P. Du, M. Gates, P. Luszczek, and S. Tomov, clMAGMA: High Performance Dense Linear Algebra with OpenCL,” University of Tennessee Technical Report (Lawn 275), no. UT-CS-13-706: University of Tennessee, March 2013.  (526.6 KB)
Horton, M., S. Tomov, and J. Dongarra, A Class of Hybrid LAPACK Algorithms for Multicore and GPU Architectures,” Symposium for Application Accelerators in High Performance Computing (SAAHPC'11), Knoxville, TN, July 2011.  (329.68 KB)
Baboulin, M., S. Donfack, J. Dongarra, L. Grigori, A. Remi, and S. Tomov, A Class of Communication-Avoiding Algorithms for Solving General Dense Linear Systems on CPU/GPU Parallel Machines,” Proc. of the International Conference on Computational Science (ICCS), vol. 9, pp. 17-26, June 2012.
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, Cholesky Factorization on Batches of Matrices with Fixed and Variable Sizes , San Jose, CA, GPU Technology Conference (GTC16), Poster, April 2016.  (480.51 KB)
YarKhan, A., A. Haidar, C. Cao, P. Luszczek, S. Tomov, and J. Dongarra, Cholesky Across Accelerators,” 17th IEEE International Conference on High Performance Computing and Communications (HPCC 2015), Elizabeth, NJ, IEEE, August 2015.
Abdelfattah, A., K. Arturov, C. Cecka, J. Dongarra, C. Freitag, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, et al., C++ API for Batch BLAS,” SLATE Working Notes, no. 4, ICL-UT-17-12: University of Tennessee, December 2017.  (1.89 MB)
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Anzt, H., J. Dongarra, M. Gates, J. Kurzak, P. Luszczek, S. Tomov, and I. Yamazaki, Bringing High Performance Computing to Big Data Algorithms,” Handbook of Big Data Technologies: Springer, 2017. DOI: 10.1007/978-3-319-49340-4
Anzt, H., S. Tomov, J. Dongarra, and V. Heuveline, A Block-Asynchronous Relaxation Method for Graphics Processing Units,” Journal of Parallel and Distributed Computing, vol. 73, issue 12, pp. 1613–1626, December 2013. DOI: http://dx.doi.org/10.1016/j.jpdc.2013.05.008  (1.08 MB)
Anzt, H., S. Tomov, J. Dongarra, and V. Heuveline, A Block-Asynchronous Relaxation Method for Graphics Processing Units,” University of Tennessee Computer Science Technical Report, no. UT-CS-11-687 / LAWN 258, November 2011.  (1.08 MB)

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