Publications

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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)
Haidar, A., H. Jagode, A. YarKhan, P. Vaccaro, S. Tomov, and J. Dongarra, Power-aware Computing: Measurement, Control, and Performance Analysis for Intel Xeon Phi,” 2017 IEEE High Performance Extreme Computing Conference (HPEC'17), Best Paper Finalist, Waltham, MA, IEEE, September 2017.  (908.84 KB)
Zunger, A., A. Franceschetti, G. Bester, W. B. Jones, K. Kim, P. A. Graf, L-W. Wang, A. Canning, O. Marques, C. Voemel, et al., Predicting the electronic properties of 3D, million-atom semiconductor nanostructure architectures,” J. Phys.: Conf. Ser. 46, vol. :101088/1742-6596/46/1/040, pp. 292-298, January 2006.  (644.1 KB)
Kurzak, J., P. Luszczek, S. Tomov, and J. Dongarra, Preliminary Results of Autotuning GEMM Kernels for the NVIDIA Kepler Architecture,” LAWN 267, 00-2012.  (1.14 MB)
Demmel, J., J. Dongarra, B.. Parlett, W. Kahan, M. Gu, D. Bindel, Y. Hida, X. Li, O. Marques, J. E. Riedy, et al., Prospectus for the Next LAPACK and ScaLAPACK Libraries,” PARA 2006, Umea, Sweden, June 2006.  (460.11 KB)
Du, P., S. Tomov, and J. Dongarra, Providing GPU Capability to LU and QR within the ScaLAPACK Framework,” University of Tennessee Computer Science Technical Report (also LAWN 272), no. UT-CS-12-699, September 2012.  (7.48 MB)
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Agullo, E., C. Augonnet, J. Dongarra, M. Faverge, H. Ltaeif, S. Thibault, and S. Tomov, QR Factorization on a Multicore Node Enhanced with Multiple GPU Accelerators,” Proceedings of IPDPS 2011, no. ICL-UT-10-04, Anchorage, AK, October 2010.  (468.17 KB)
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Yamazaki, I., S. Tomov, and J. Dongarra, Sampling Algorithms to Update Truncated SVD,” IEEE International Conference on Big Data, December 2017.
Bernholc, J., M. Hodak, W. Lu, S. Moore, and S. Tomov, Scalability Study of a Quantum Simulation Code,” PARA 2010, Reykjavik, Iceland, June 2010.
Bosilca, G., A. Bouteiller, A. Danalis, T. Herault, J. Kurzak, P. Luszczek, S. Tomov, and J. Dongarra, Scalable Dense Linear Algebra on Heterogeneous Hardware,” HPC: Transition Towards Exascale Processing, in the series Advances in Parallel Computing, 2013.  (760.32 KB)
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)
Anzt, H., D. Lukarski, S. Tomov, and J. Dongarra, Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures,” VECPAR 2014, Eugene, OR, June 2014.  (430.56 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.
Abdelfattah, A., M. Baboulin, V. Dobrev, J. Dongarra, A. Haidar, I. Karlin, T. Kolev, I. Masliah, and S. Tomov, Small Tensor Operations on Advanced Architectures for High-Order Applications,” University of Tennessee Computer Science Technical Report, no. UT-EECS-17-749: Innovative Computing Laboratory, University of Tennessee, April 2017.  (1.09 MB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, Soft Error Resilient QR Factorization for Hybrid System,” University of Tennessee Computer Science Technical Report, no. UT-CS-11-675, Knoxville, TN, July 2011.  (1.39 MB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, Soft Error Resilient QR Factorization for Hybrid System,” UT-CS-11-675 (also LAPACK Working Note #252), no. ICL-CS-11-675, July 2011.  (1.39 MB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, Soft Error Resilient QR Factorization for Hybrid System with GPGPU,” Journal of Computational Science, vol. 4, issue 6, pp. 457–464, November 2013.  (995.45 KB)
Du, P., P. Luszczek, S. Tomov, and J. Dongarra, Soft Error Resilient QR Factorization for Hybrid System with GPGPU,” Journal of Computational Science, Seattle, WA, Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems at SC11, November 2011.  (965.88 KB)
Jagode, H., A. Danalis, H. Anzt, I. Yamazaki, M. Hoemmen, E. Boman, S. Tomov, and J. Dongarra, Software-Defined Events (SDEs) in MAGMA-Sparse,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-12: University of Tennessee, December 2018.  (481.69 KB)
Baboulin, M., J. Dongarra, A. Remy, S. Tomov, and I. Yamazaki, Solving Dense Symmetric Indefinite Systems using GPUs,” Concurrency and Computation: Practice and Experience, vol. 29, issue 9, March 2017.  (1.94 MB)
Zaitsev, D., S. Tomov, and J. Dongarra, Solving Linear Diophantine Systems on Parallel Architectures,” IEEE Transactions on Parallel and Distributed Systems, October 2018.
Baboulin, M., S. Tomov, and J. Dongarra, Some Issues in Dense Linear Algebra for Multicore and Special Purpose Architectures,” PARA 2008, 9th International Workshop on State-of-the-Art in Scientific and Parallel Computing, Trondheim Norway, May 2008.
Baboulin, M., J. Dongarra, and S. Tomov, Some Issues in Dense Linear Algebra for Multicore and Special Purpose Architectures,” University of Tennessee Computer Science Technical Report, UT-CS-08-615 (also LAPACK Working Note 200), January 2008.  (289.93 KB)
Yamazaki, I., S. Tomov, and J. Dongarra, Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU,” ACM Transactions on Mathematical Software (TOMS), vol. 43, issue 2, October 2016.
Voemel, C., S. Tomov, O. Marques, A. Canning, L-W. Wang, and J. Dongarra, State-of-the-Art Eigensolvers for Electronic Structure Calculations of Large Scale Nano-Systems,” Journal of Computational Physics, vol. 227, no. 15, pp. 7113-7124, January 2008.
Dong, T., V. Dobrev, T. Kolev, R. Rieben, S. Tomov, and J. Dongarra, A Step towards Energy Efficient Computing: Redesigning A Hydrodynamic Application on CPU-GPU,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (1.01 MB)
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.  (339.11 KB)
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Haidar, A., M. Gates, S. Tomov, and J. Dongarra, Toward a scalable multi-GPU eigensolver via compute-intensive kernels and efficient communication,” Proceedings of the 27th ACM International Conference on Supercomputing (ICS '13), Eugene, Oregon, USA, ACM Press, June 2013.  (1.27 MB)
Lopez, M., V. Larrea, W. Joubert, O. Hernandez, A. Haidar, S. Tomov, and J. Dongarra, Towards Achieving Performance Portability Using Directives for Accelerators,” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC'16), Third Workshop on Accelerator Programming Using Directives (WACCPD), Salt Lake City, Utah, Innovative Computing Laboratory, University of Tennessee, November 2016.  (567.02 KB)
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, Towards Batched Linear Solvers on Accelerated Hardware Platforms,” 8th Workshop on General Purpose Processing Using GPUs (GPGPU 8) co-located with PPOPP 2015, San Francisco, CA, ACM, February 2015.  (403.74 KB)
Canning, A., J. Dongarra, J. Langou, O. Marques, S. Tomov, C. Voemel, and L-W. Wang, Towards bulk based preconditioning for quantum dot computations,” IEEE/ACM Proceedings of HPCNano SC06 (to appear), January 2006.  (172.46 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)
Tomov, S., J. Dongarra, and M. Baboulin, Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems,” University of Tennessee Computer Science Technical Report, UT-CS-08-632 (also LAPACK Working Note 210), January 2008.  (606.41 KB)
Yamazaki, I., T. Dong, R. Solcà, S. Tomov, J. Dongarra, and T. C. Schulthess, Tridiagonalization of a dense symmetric matrix on multiple GPUs and its application to symmetric eigenvalue problems,” Concurrency and Computation: Practice and Experience, October 2013.  (1.71 MB)
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Haidar, A., C. Cao, J. Dongarra, P. Luszczek, and S. Tomov, Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (1.51 MB)
Bosilca, G., A. Bouteiller, T. Herault, P. Lemariner, N. Ohm Saengpatsa, S. Tomov, and J. Dongarra, A Unified HPC Environment for Hybrid Manycore/GPU Distributed Systems,” IEEE International Parallel and Distributed Processing Symposium (submitted), Anchorage, AK, May 2011.
Voemel, C., S. Tomov, L-W. Wang, O. Marques, and J. Dongarra, The use of bulk states to accelerate the band edge state calculation of a semiconductor quantum dot,” Journal of Computational Physics (submitted), January 2006.  (337.08 KB)
Voemel, C., S. Tomov, L-W. Wang, O. Marques, and J. Dongarra, The Use of Bulk States to Accelerate the Band Edge State Calculation of a Semiconductor Quantum Dot,” Journal of Computational Physics, vol. 223, pp. 774-782, 00-2007.  (452.6 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,” ISC High Performance (ISC'18), Best Poster, Frankfurt, Germany, June 2018.  (3.01 MB)
Tomov, S., M. Faverge, P. Luszczek, and J. Dongarra, Using MAGMA with PGI Fortran,” PGI Insider, November 2010.  (176.67 KB)
Buttari, A., J. Dongarra, J. Kurzak, P. Luszczek, and S. Tomov, Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy,” ACM Transactions on Mathematical Software, vol. 34, no. 4, pp. 17-22, 00-2008.  (364.48 KB)
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Anzt, H., S. Tomov, J. Dongarra, and V. Heuveline, Weighted Block-Asynchronous Iteration on GPU-Accelerated Systems,” Tenth International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (Best Paper), Rhodes Island, Greece, August 2012.  (764.02 KB)
Haidar, A., Y. Jia, P. Luszczek, S. Tomov, A. YarKhan, and J. Dongarra, Weighted Dynamic Scheduling with Many Parallelism Grains for Offloading of Numerical Workloads to Multiple Varied Accelerators,” Proceedings of the 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA'15), vol. No. 5, Austin, TX, ACM, November 2015.  (347.6 KB)

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