Publications

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Journal Article
Dongarra, J., M. Gates, P. Luszczek, and S. Tomov, Translational process: Mathematical software perspective,” Journal of Computational Science, vol. 52, pp. 101216, 2021. DOI: 10.1016/j.jocs.2020.101216
Dongarra, J., M. Gates, P. Luszczek, and S. Tomov, Translational Process: Mathematical Software Perspective,” Journal of Computational Science, September 2020. DOI: 10.1016/j.jocs.2020.101216  (752.59 KB)
Tomov, S., J. Dongarra, and M. Baboulin, Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems,” Parallel Computing, vol. 36, no. 5-6, pp. 232-240, 00 2010.  (606.41 KB)
Yamazaki, I., S. Nooshabadi, S. Tomov, and J. Dongarra, Structure-aware Linear Solver for Realtime Convex Optimization for Embedded Systems,” IEEE Embedded Systems Letters, vol. 9, issue 3, pp. 61–64, May 2017. DOI: 10.1109/LES.2017.2700401  (339.11 KB)
Zaitsev, D., S. Tomov, and J. Dongarra, Solving Linear Diophantine Systems on Parallel Architectures,” IEEE Transactions on Parallel and Distributed Systems, vol. 30, issue 5, pp. 1158-1169, May 2019. DOI: http://dx.doi.org/10.1109/TPDS.2018.2873354  (802.97 KB)
Dongarra, J., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and I. Yamazaki, The Singular Value Decomposition: Anatomy of Optimizing an Algorithm for Extreme Scale,” SIAM Review, vol. 60, issue 4, pp. 808–865, November 2018. DOI: 10.1137/17M1117732  (2.5 MB)
Abdelfattah, A., T. Costa, J. Dongarra, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Kurzak, P. Luszczek, S. Tomov, et al., A Set of Batched Basic Linear Algebra Subprograms and LAPACK Routines,” ACM Transactions on Mathematical Software (TOMS), vol. 47, no. 3, pp. 1–23, 2021. DOI: 10.1145/3431921
Abdelfattah, A., T. Costa, J. Dongarra, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Kurzak, P. Luszczek, S. Tomov, et al., A Set of Batched Basic Linear Algebra Subprograms,” ACM Transactions on Mathematical Software, October 2020.
Ltaeif, H., S. Tomov, R. Nath, P. Du, and J. Dongarra, A Scalable High Performant Cholesky Factorization for Multicore with GPU Accelerators,” Proc. of VECPAR'10 (to appear), Berkeley, CA, June 2010.  (870.46 KB)
Lu, Y., I. Yamazaki, F. Ino, Y. Matsushita, S. Tomov, and J. Dongarra, Reducing the Amount of out-of-core Data Access for GPU-Accelerated Randomized SVD,” Concurrency and Computation: Practice and Experience, April 2020. DOI: 10.1002/cpe.5754  (1.43 MB)
Wong, K., S. Tomov, and J. Dongarra, Project-Based Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning,” The Journal of Computational Science Education, vol. 11, issue 1, pp. 36-44, January 2020. DOI: 10.22369/issn.2153-4136/11/1/7  (4.4 MB)
Kasichayanula, K., D. Terpstra, P. Luszczek, S. Tomov, S. Moore, and G. D. Peterson, Power Aware Computing on GPUs,” SAAHPC '12 (Best Paper Award), Argonne, IL, July 2012.  (658.06 KB)
Bosilca, G., A. Bouteiller, T. Herault, P. Lemariner, N. Ohm Saengpatsa, S. Tomov, and J. Dongarra, Performance Portability of a GPU Enabled Factorization with the DAGuE Framework,” IEEE Cluster: workshop on Parallel Programming on Accelerator Clusters (PPAC), June 2011.  (290.98 KB)
Anzt, H., S. Tomov, and J. Dongarra, On the performance and energy efficiency of sparse linear algebra on GPUs,” International Journal of High Performance Computing Applications, October 2016. DOI: 10.1177/1094342016672081  (1.19 MB)
Abalenkovs, M., A. Abdelfattah, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, I. Yamazaki, and A. YarKhan, Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems,” Supercomputing Frontiers and Innovations, vol. 2, no. 4, October 2015. DOI: 10.14529/jsfi1504  (3.68 MB)
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. DOI: 10.1098/rspa.2020.0110  (2.24 MB)
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)
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
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)
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)
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
Brown, J., A. Abdelfattah, V. Barra, N. Beams, J-S. Camier, V. Dobrev, Y. Dudouit, L. Ghaffari, T. Kolev, D. Medina, et al., libCEED: Fast algebra for high-order element-based discretizations,” Journal of Open Source Software, vol. 6, no. 63, pp. 2945, 2021. DOI: 10.21105/joss.02945
Haidar, A., H. Jagode, P. Vaccaro, A. YarKhan, S. Tomov, and J. Dongarra, Investigating Power Capping toward Energy-Efficient Scientific Applications,” Concurrency Computation: Practice and Experience, vol. 2018, issue e4485, pp. 1-14, April 2018. DOI: 10.1002/cpe.4485  (1.2 MB)
Nath, R., S. Tomov, and J. Dongarra, An Improved MAGMA GEMM for Fermi GPUs,” International Journal of High Performance Computing, vol. 24, no. 4, pp. 511-515, 00 2010.
Buttari, A., J. Dongarra, J. Kurzak, J. Langou, P. Luszczek, and S. Tomov, The Impact of Multicore on Math Software,” PARA 2006, Umea, Sweden, June 2006.  (223.53 KB)
Agullo, E., C. Augonnet, J. Dongarra, H. Ltaeif, R. Namyst, S. Thibault, and S. Tomov, A Hybridization Methodology for High-Performance Linear Algebra Software for GPUs,” in GPU Computing Gems, Jade Edition, vol. 2: Elsevier, pp. 473-484, 00 2011.
Ltaeif, H., S. Tomov, R. Nath, and J. Dongarra, Hybrid Multicore Cholesky Factorization with Multiple GPU Accelerators,” IEEE Transaction on Parallel and Distributed Systems (submitted), March 2010.  (3.75 MB)
Haidar, A., A. Abdelfattah, M. Zounon, S. Tomov, and J. Dongarra, A Guide for Achieving High Performance with Very Small Matrices on GPUs: A Case Study of Batched LU and Cholesky Factorizations,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 5, pp. 973–984, May 2018. DOI: 10.1109/TPDS.2017.2783929  (832.92 KB)
Du, P., R. Weber, P. Luszczek, S. Tomov, G. D. Peterson, and J. Dongarra, From CUDA to OpenCL: Towards a Performance-portable Solution for Multi-platform GPU Programming,” Parallel Computing, vol. 38, no. 8, pp. 391-407, August 2012.  (1.64 MB)
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)

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