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Haidar, A., L. Giraud, H. Ben-Hadj-Ali, F. Sourbier, S. Operto, and J. Virieux, “3-D parallel frequency-domain visco-acoustic wave modelling based on a hybrid direct/iterative solver,” 73rd EAGE Conference & Exhibition incorporating SPE EUROPEC 2011, Vienna, Austria, 23-26 May, 00 2011.
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Gates, M., A. Haidar, and J. Dongarra, “Accelerating Eigenvector Computation in the Nonsymmetric Eigenvalue Problem,” VECPAR 2014, Eugene, OR, June 2014.  (199.44 KB)
Ayala, A., S. Tomov, A. Haidar, M.. Stoyanov, S. Cayrols, J. Li, G. Bosilca, and J. Dongarra, Accelerating FFT towards Exascale Computing : NVIDIA GPU Technology Conference (GTC2021), 2021.  (27.23 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)
Baboulin, M., J. Dongarra, J. Herrmann, and S. Tomov, “Accelerating Linear System Solutions Using Randomization Techniques,” INRIA RR-7616 / LAWN #246 (presented at International AMMCS’11), Waterloo, Ontario, Canada, July 2011.  (358.79 KB)
Baboulin, M., J. Dongarra, J. Herrmann, and S. Tomov, “Accelerating Linear System Solutions Using Randomization Techniques,” ACM Transactions on Mathematical Software (also LAWN 246), vol. 39, issue 2, February 2013.  (358.79 KB)
Ayala, A., S. Tomov, M. Stoyanov, A. Haidar, and J. Dongarra, “Accelerating Multi - Process Communication for Parallel 3-D FFT,” 2021 Workshop on Exascale MPI (ExaMPI), St. Louis, MO, USA, IEEE, December 2021.
Dongarra, J., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and I. Yamazaki, “Accelerating Numerical Dense Linear Algebra Calculations with GPUs,” Numerical Computations with GPUs: Springer International Publishing, pp. 3-28, 2014.  (1.06 MB)
Haidar, A., A. Abdelfattah, V. Dobrev, I. Karlin, T. Kolev, S. Tomov, and J. Dongarra, Accelerating Tensor Contractions for High-Order FEM on CPUs, GPUs, and KNLs , Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC16), Poster, September 2016.  (4.29 MB)
Abdelfattah, A., M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, T. Kolev, I. Masliah, et al., Accelerating Tensor Contractions in High-Order FEM with MAGMA Batched , Atlanta, GA, SIAM Conference on Computer Science and Engineering (SIAM CSE17), Presentation, March 2017.  (9.29 MB)
Anzt, H., M. Baboulin, J. Dongarra, Y. Fournier, F. Hulsemann, A. Khabou, and Y. Wang, “Accelerating the Conjugate Gradient Algorithm with GPU in CFD Simulations,” VECPAR, 2016.
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, “Accelerating the SVD Bi-Diagonalization of a Batch of Small Matrices using GPUs,” Journal of Computational Science, vol. 26, pp. 237–245, May 2018.  (2.18 MB)
Beck, M., J. Dongarra, J. Huang, T. Moore, and J. Plank, “Active Logistical State Management in the GridSolve/L,” 4th International Symposium on Cluster Computing and the Grid (CCGrid 2004)(submitted), Chicago, Illinois, January 2004.  (123.69 KB)
Moore, S., A.J.. Baker, J. Dongarra, C. Halloy, and C. Ng, “Active Netlib: An Active Mathematical Software Collection for Inquiry-based Computational Science and Engineering Education,” Journal of Digital Information special issue on Interactivity in Digital Libraries, vol. 2, no. 4, 00 2002.  (182.59 KB)
Anzt, H., J. Dongarra, G. Flegar, N. J. Higham, and E. S. Quintana-Orti, “Adaptive Precision in Block-Jacobi Preconditioning for Iterative Sparse Linear System Solvers,” Concurrency and Computation: Practice and Experience, vol. 31, no. 6, pp. e4460, March 2019.  (341.54 KB)
Thiyagalingam, J., G. von Laszewski, J. Yin, M. Emani, J. Papay, G. Barrett, P. Luszczek, A. Tsaris, C. Kirkpatrick, F. Wang, et al., “AI Benchmarking for Science: Efforts from the MLCommons Science Working Group,” Lecture Notes in Computer Science, vol. 13387: Springer International Publishing, pp. 47 - 64, January 2023.
Agullo, E., L. Giraud, A. Guermouche, A. Haidar, S. Lanteri, and J. Roman, “Algebraic Schwarz Preconditioning for the Schur Complement: Application to the Time-Harmonic Maxwell Equations Discretized by a Discontinuous Galerkin Method.,” The Twentieth International Conference on Domain Decomposition Methods, La Jolla, California, February 2011.
Du, P., A. Bouteiller, G. Bosilca, T. Herault, and J. Dongarra, “Algorithm-Based Fault Tolerance for Dense Matrix Factorization,” Proceedings of the 17th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP 2012, New Orleans, LA, USA, ACM, pp. 225-234, February 2012.  (865.79 KB)
Du, P., A. Bouteiller, G. Bosilca, T. Herault, and J. Dongarra, “Algorithm-based Fault Tolerance for Dense Matrix Factorizations,” University of Tennessee Computer Science Technical Report, no. UT-CS-11-676, Knoxville, TN, August 2011.  (865.79 KB)
Bouteiller, A., T. Herault, G. Bosilca, P. Du, and J. Dongarra, “Algorithm-based Fault Tolerance for Dense Matrix Factorizations, Multiple Failures, and Accuracy,” ACM Transactions on Parallel Computing, vol. 1, issue 2, no. 10, pp. 10:1-10:28, January 2015.  (1.14 MB)
Masliah, I., A. Abdelfattah, A. Haidar, S. Tomov, M. Baboulin, J. Falcou, and J. Dongarra, “Algorithms and Optimization Techniques for High-Performance Matrix-Matrix Multiplications of Very Small Matrices,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-09: Innovative Computing Laboratory, University of Tennessee, September 2018.  (3.74 MB)
Masliah, I., A. Abdelfattah, A. Haidar, S. Tomov, M. Baboulin, J. Falcou, and J. Dongarra, “Algorithms and Optimization Techniques for High-Performance Matrix-Matrix Multiplications of Very Small Matrices,” Parallel Computing, vol. 81, pp. 1–21, January 2019.  (3.27 MB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, “Analysis and Design Techniques towards High-Performance and Energy-Efficient Dense Linear Solvers on GPUs,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 12, pp. 2700–2712, December 2018.  (2.53 MB)
Haidar, A., H. Ltaeif, A. YarKhan, and J. Dongarra, “Analysis of Dynamically Scheduled Tile Algorithms for Dense Linear Algebra on Multicore Architectures,” Submitted to Concurrency and Computations: Practice and Experience, November 2010.  (1.65 MB)
Haidar, A., H. Ltaeif, A. YarKhan, and J. Dongarra, “Analysis of Dynamically Scheduled Tile Algorithms for Dense Linear Algebra on Multicore Architectures,” University of Tennessee Computer Science Technical Report, UT-CS-11-666, (also Lawn 243), March 2011.  (1.65 MB)
Seo, S., A. Amer, P. Balaji, C. Bordage, G. Bosilca, A. Brooks, P. Carns, A. Castello, D. Genet, T. Herault, et al., “Argobots: A Lightweight Low-Level Threading and Tasking Framework,” IEEE Transactions on Parallel and Distributed Systems, October 2017.
Hendrickson, B., P. Messina, B. Bland, J. Chen, P. Colella, E. Dart, J. Dongarra, T. Dunning, I. Foster, R. Gerber, et al., ASCR@40: Four Decades of Department of Energy Leadership in Advanced Scientific Computing Research : Advanced Scientific Computing Advisory Committee (ASCAC), US Department of Energy, August 2020.
Hendrickson, B., P. Messina, B. Bland, J. Chen, P. Colella, E. Dart, J. Dongarra, T. Dunning, I. Foster, R. Gerber, et al., ASCR@40: Four Decades of Department of Energy Leadership in Advanced Scientific Computing Research : Advanced Scientific Computing Advisory Committee (ASCAC), US Department of Energy, August 2020.
Hendrickson, B., P. Messina, B. Bland, J. Chen, P. Colella, E. Dart, J. Dongarra, T. Dunning, I. Foster, R. Gerber, et al., ASCR@40: Four Decades of Department of Energy Leadership in Advanced Scientific Computing Research : Advanced Scientific Computing Advisory Committee (ASCAC), US Department of Energy, August 2020.
Hendrickson, B., P. Messina, B. Bland, J. Chen, P. Colella, E. Dart, J. Dongarra, T. Dunning, I. Foster, R. Gerber, et al., ASCR@40: Highlights and Impacts of ASCR’s Programs : US Department of Energy’s Office of Advanced Scientific Computing Research, June 2020.
Hendrickson, B., P. Messina, B. Bland, J. Chen, P. Colella, E. Dart, J. Dongarra, T. Dunning, I. Foster, R. Gerber, et al., ASCR@40: Highlights and Impacts of ASCR’s Programs : US Department of Energy’s Office of Advanced Scientific Computing Research, June 2020.
Hendrickson, B., P. Messina, B. Bland, J. Chen, P. Colella, E. Dart, J. Dongarra, T. Dunning, I. Foster, R. Gerber, et al., ASCR@40: Highlights and Impacts of ASCR’s Programs : US Department of Energy’s Office of Advanced Scientific Computing Research, June 2020.
Herrmann, J., G. Bosilca, T. Herault, L. Marchal, Y. Robert, and J. Dongarra, “Assessing the Cost of Redistribution followed by a Computational Kernel: Complexity and Performance Results,” Parallel Computing, vol. 52, pp. 22-41, February 2016.  (2.06 MB)
Herrmann, J., G. Bosilca, T. Herault, L. Marchal, Y. Robert, and J. Dongarra, “Assessing the Cost of Redistribution followed by a Computational Kernel: Complexity and Performance Results,” Parallel Computing, vol. 52, pp. 22-41, February 2016.  (2.06 MB)
Bosilca, G., A. Bouteiller, T. Herault, Y. Robert, and J. Dongarra, “Assessing the impact of ABFT and Checkpoint composite strategies,” University of Tennessee Computer Science Technical Report, no. ICL-UT-13-03, 2013.  (968.47 KB)
Bosilca, G., A. Bouteiller, T. Herault, Y. Robert, and J. Dongarra, “Assessing the Impact of ABFT and Checkpoint Composite Strategies,” 16th Workshop on Advances in Parallel and Distributed Computational Models, IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (1.02 MB)
Balaprakash, P., J. Dongarra, T. Gamblin, M. Hall, J. Hollingsworth, B. Norris, and R. Vuduc, “Autotuning in High-Performance Computing Applications,” Proceedings of the IEEE, vol. 106, issue 11, pp. 2068–2083, November 2018.  (2.5 MB)
Balaprakash, P., J. Dongarra, T. Gamblin, M. Hall, J. Hollingsworth, B. Norris, and R. Vuduc, “Autotuning in High-Performance Computing Applications,” Proceedings of the IEEE, vol. 106, issue 11, pp. 2068–2083, November 2018.  (2.5 MB)
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Blackford, S., J. Demmel, J. Dongarra, I. Duff, S. Hammarling, G. Henry, M. Heroux, L. Kaufman, A. Lumsdaine, A. Petitet, et al., “Basic Linear Algebra Subprograms (BLAS),” (an update), submitted to ACM TOMS, February 2001.  (228.33 KB)
Blackford, S., J. Demmel, J. Dongarra, I. Duff, S. Hammarling, G. Henry, M. Heroux, L. Kaufman, A. Lumsdaine, A. Petitet, et al., “Basic Linear Algebra Subprograms (BLAS),” (an update), submitted to ACM TOMS, February 2001.  (228.33 KB)
Blackford, S., J. Demmel, J. Dongarra, I. Duff, S. Hammarling, G. Henry, M. Heroux, L. Kaufman, A. Lumsdaine, A. Petitet, et al., “Basic Linear Algebra Subprograms (BLAS),” (an update), submitted to ACM TOMS, February 2001.  (228.33 KB)
Dongarra, J., I. Duff, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Hogg, P. Valero Lara, P. Luszczek, M. Zounon, et al., Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification , July 2018.  (483.05 KB)
Dongarra, J., I. Duff, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Hogg, P. Valero Lara, P. Luszczek, M. Zounon, et al., Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification , July 2018.  (483.05 KB)
Dongarra, J., I. Duff, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Hogg, P. Valero Lara, P. Luszczek, M. Zounon, et al., Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification , July 2018.  (483.05 KB)
Dongarra, J., I. Duff, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Hogg, P. Valero Lara, P. Luszczek, M. Zounon, et al., Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification , July 2018.  (483.05 KB)
Anzt, H., E. Chow, T. Huckle, and J. Dongarra, “Batched Generation of Incomplete Sparse Approximate Inverses on GPUs,” Proceedings of the 7th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, pp. 49–56, November 2016.
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, “Batched Matrix Computations on Hardware Accelerators,” EuroMPI/Asia 2015 Workshop, Bordeaux, France, September 2015.  (589.05 KB)
Haidar, A., T. Dong, P. Luszczek, S. Tomov, and J. Dongarra, “Batched matrix computations on hardware accelerators based on GPUs,” International Journal of High Performance Computing Applications, February 2015.  (2.16 MB)
Haidar, A., A. Abdelfattah, S. Tomov, and J. Dongarra, “Batched Matrix Computations on Hardware Accelerators Based on GPUs,” 2015 SIAM Conference on Applied Linear Algebra (SIAM LA), Atlanta, GA, SIAM, October 2015.  (9.36 MB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, “Batched One-Sided Factorizations of Tiny Matrices Using GPUs: Challenges and Countermeasures,” Journal of Computational Science, vol. 26, pp. 226–236, May 2018.  (3.73 MB)

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