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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)
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)
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)
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., M. Gates, and A. Haidar, Accelerating Linear Algebra with MAGMA , Knoxville, TN, ECP Annual Meeting 2018, Tutorial, February 2018.  (35.27 MB)
Tomov, S., K. Wong, R. Febbo, and J. Halloy, Linear Algebra Prepara.on for Emergent Neural Network Architectures: MAGMA, BLAS, and Batched GPU Computing , Virtual, LAPENNA Workshop, November 2021.  (17.8 MB)
Tomov, S., W. Lu, J. Bernholc, S. Moore, and J. Dongarra, Performance evaluation for petascale quantum simulation tools,” Proceedings of CUG09, Atlanta, GA, May 2009.  (1.09 MB)
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)
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., 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)
Tomov, S., G. Bosilca, and C. Augonnet, Accelerating Linear Algebra on Heterogeneous Architectures of Multicore and GPUs using MAGMA and DPLASMA and StarPU Schedulers : 2010 Symposium on Application Accelerators in. High-Performance Computing (SAAHPC'10), Tutorial, July 2010.  (499.51 KB)
Tomov, S., and A. Haidar, MAGMA Tensors and Batched Computing for Accelerating Applications on GPUs , San Jose, CA, GPU Technology Conference (GTC17), Presentation in Session S7728, May 2017.  (11.12 MB)
Tomov, S., MATEDOR: MAtrix, TEnsor, and Deep-learning Optimized Routines , Seattle, WA, 2020 NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) Principal Investigator Meeting, February 2020.  (2.28 MB)
Tomov, S., Matrix Algebra on GPU and Multicore Architectures , Basel, Switzerland, Workshop on GPU-enabled Numerical Libraries, Presentation, May 2011.  (49.27 MB)
Recent Advances in the Message Passing Interface: 19th European MPI Users' Group Meeting, EuroMPI 2012,” Lecture Notes in Computer Science, vol. 7490, Vienna, Austria, 00 2012.
Tsai, Y-H. M., T. Cojean, and H. Anzt, Providing performance portable numerics for Intel GPUs,” Concurrency and Computation: Practice and Experience, vol. 17, October 2022.  (3.16 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)
Tsai, Y-H. Mike, N. Beams, and H. Anzt, Three-precision algebraic multigrid on GPUs,” Future Generation Computer Systems, July 2023.
Tsai, Y. M., P. Luszczek, and J. Dongarra, Mixed-Precision Algorithm for Finding Selected Eigenvalues and Eigenvectors of Symmetric and Hermitian Matrices,” ICL Technical Report, no. ICL-UT-21-05, August 2021.  (3.93 MB)
Tsai, Y. M., T. Cojean, and H. Anzt, Sparse Linear Algebra on AMD and NVIDIA GPUs—The Race is On,” ISC High Performance: Springer, June 2020.  (5.63 MB)
Tseng, S-M., B. Nicolae, G. Bosilca, E. Jeannot, A. Chandramowlishwaran, and F. Cappello, Towards Portable Online Prediction of Network Utilization Using MPI-Level Monitoring,” 2019 European Conference on Parallel Processing (Euro-Par 2019), Göttingen, Germany, Springer, August 2019.  (1.07 MB)
Turchenko, V., L. Grandinetti, G. Bosilca, and J. Dongarra, Improvement of parallelization efficiency of batch pattern BP training algorithm using Open MPI,” Proceedings of International Conference on Computational Science, ICCS 2010 (to appear), Amsterdam The Netherlands, Elsevier, June 2010.  (125.01 KB)
Turchenko, V., G. Bosilca, A. Bouteiller, and J. Dongarra, Efficient Parallelization of Batch Pattern Training Algorithm on Many-core and Cluster Architectures,” 7th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, Berlin, Germany, September 2013.  (102.51 KB)
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Vadhiyar, S., J. Dongarra, and A. YarKhan, GrADSolve - RPC for High Performance Computing on the Grid,” Lecture Notes in Computer Science, Proceedings of the 9th International Euro-Par Conference, vol. 2790, Klagenfurt, Austria, Springer-Verlag, Berlin, pp. 394-403, January 2003.  (125.96 KB)
Vadhiyar, S., G. Fagg, and J. Dongarra, Performance Modeling for Self Adapting Collective Communications for MPI,” LACSI Symposium 2001, Santa Fe, NM, October 2001.  (105.49 KB)
Vadhiyar, S., and J. Dongarra, A Metascheduler For The Grid,” Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing (HPDC 2002), Edinburgh, Scotland, IEEE Computer Society, pp. 343-351, July 2002.  (99.53 KB)
Vadhiyar, S., and J. Dongarra, Self Adaptability in Grid Computing,” Concurrency: Practice and Experience (submitted), March 2003.  (258.89 KB)
Vadhiyar, S., G. Fagg, and J. Dongarra, Towards an Accurate Model for Collective Communications,” International Journal of High Performance Applications, Special Issue: Automatic Performance Tuning, vol. 18, no. 1, pp. 159-167, January 2004.  (250.73 KB)
Vadhiyar, S., A Performance Oriented Migration Framework for the Grid,” Proceedings of the 3rd International Symposium on Cluster Computing and the Grid, Tokyo, Japan, pp. 130-137, May 2003.  (113.6 KB)
Vadhiyar, S., and J. Dongarra, GrADSolve - A Grid-based RPC System for Remote Invocation of Parallel Software,” Journal of Parallel and Distributed Computing (submitted), March 2003.  (241.3 KB)
Vadhiyar, S., G. Fagg, and J. Dongarra, Automatically Tuned Collective Communications,” Proceedings of SuperComputing 2000 (SC'2000), Dallas, TX, November 2000.  (232.69 KB)
Vadhiyar, S., and J. Dongarra, Self Adaptivity in Grid Computing,” Concurrency and Computation: Practice and Experience, Special Issue: Grid Performance, vol. 17, no. 2-4, pp. 235-257, 00 2005.  (394.66 KB)
Vadhiyar, S., G. Fagg, and J. Dongarra, Towards an Accurate Model for Collective Communications,” ICL Technical Report, no. ICL-UT-05-03, January 2005.  (250.73 KB)
Vadhiyar, S., and J. Dongarra, SRS - A Framework for Developing Malleable and Migratable Parallel Software,” Parallel Processing Letters, vol. 13, no. 2, pp. 291-312, June 2003.  (211.6 KB)
Valeev, E. F., R. J. Harrison, A. A. Holmes, C. C. Peterson, and D. A. Penchoff, Direct Determination of Optimal Real-Space Orbitals for Correlated Electronic Structure of Molecules,” Journal of Chemical Theory and Computation, vol. 19, issue 20, pp. 7230 - 7241, October 2023.
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)
Vetter, J., R. Glassbrook, J. Dongarra, K. Schwan, B. Loftis, S. McNally, J. Meredith, J. Rogers, P. Roth, K. Spafford, et al., Keeneland: Bringing Heterogeneous GPU Computing to the Computational Science Community,” IEEE Computing in Science & Engineering, vol. 13, issue 5, pp. 90-95, August 2011.  (932.57 KB)
Vetter, J., R. Glassbrook, K. Schwan, S. Yalamanchili, M. Horton, A. Gavrilovska, M. Slawinska, J. Dongarra, J. Meredith, P. Roth, et al., Keeneland: Computational Science Using Heterogeneous GPU Computing,” Contemporary High Performance Computing: From Petascale Toward Exascale, Boca Raton, FL, Taylor and Francis, 2013.  (2.7 MB)
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)
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, 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.
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, 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.
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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.  (4.72 MB)
Wang, Y., M. Baboulin, J. Falcou, Y. Fraigneau, and O. Le Maître, A Parallel Solver for Incompressible Fluid Flows,” International Conference on Computational Science (ICCS 2013), Barcelona, Spain, Elsevier B.V., June 2013.  (588.79 KB)
Weaver, V., D. Terpstra, and S. Moore, Non-Determinism and Overcount on Modern Hardware Performance Counter Implementations,” 2013 IEEE International Symposium on Performance Analysis of Systems and Software, Austin, TX, IEEE, April 2013.  (307.24 KB)
Weaver, V. M., and J. Dongarra, Can Hardware Performance Counters Produce Expected, Deterministic Results?,” 3rd Workshop on Functionality of Hardware Performance Monitoring, Atlanta, GA, December 2010.  (392.71 KB)
Weaver, V. M., M. Johnson, K. Kasichayanula, J. Ralph, P. Luszczek, D. Terpstra, and S. Moore, Measuring Energy and Power with PAPI,” International Workshop on Power-Aware Systems and Architectures, Pittsburgh, PA, September 2012.  (146.79 KB)
Weaver, V., D. Terpstra, H. McCraw, M. Johnson, K. Kasichayanula, J. Ralph, J. Nelson, P. Mucci, T. Mohan, and S. Moore, PAPI 5: Measuring Power, Energy, and the Cloud , Austin, TX, 2013 IEEE International Symposium on Performance Analysis of Systems and Software, April 2013.  (78.39 KB)
Whaley, C., and J. Dongarra, Automatically Tuned Linear Algebra Software,” 1998 ACM/IEEE conference on Supercomputing (SC '98), Orlando, FL, IEEE Computer Society, November 1998.

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