Publications

Export 1111 results:
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
A
Mucci, P., J. Dongarra, R. Kufrin, S. Moore, F. Song, and F. Wolf, Automating the Large-Scale Collection and Analysis of Performance,” 5th LCI International Conference on Linux Clusters: The HPC Revolution, Austin, Texas, May 2004.  (511.6 KB)
You, H., B. Rekapalli, Q. Liu, and S. Moore, Autotuned Parallel I/O for Highly Scalable Biosequence Analysis,” TeraGrid'11, Salt Lake City, Utah, July 2011.  (275.34 KB)
Gates, M., J. Kurzak, P. Luszczek, Y. Pei, and J. Dongarra, Autotuning Batch Cholesky Factorization in CUDA with Interleaved Layout of Matrices,” Parallel and Distributed Processing Symposium Workshops (IPDPSW), Orlando, FL, IEEE, June 2017. DOI: 10.1109/IPDPSW.2017.18
Nath, R., S. Tomov, E. Agullo, and J. Dongarra, Autotuning Dense Linear Algebra Libraries on GPUs , Basel, Switzerland, Sixth International Workshop on Parallel Matrix Algorithms and Applications (PMAA 2010), June 2010.  (579.44 KB)
Kurzak, J., S. Tomov, and J. Dongarra, Autotuning GEMM Kernels for the Fermi GPU,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 11, November 2012. DOI: 10.1109/TPDS.2011.311  (742.5 KB)
Kurzak, J., S. Tomov, and J. Dongarra, Autotuning GEMMs for Fermi,” University of Tennessee Computer Science Technical Report, UT-CS-11-671, (also Lawn 245), April 2011.  (397.45 KB)
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. DOI: 10.1109/JPROC.2018.2841200  (2.5 MB)
Dongarra, J., M. Gates, J. Kurzak, P. Luszczek, and Y. Tsai, Autotuning Numerical Dense Linear Algebra for Batched Computation With GPU Hardware Accelerators,” Proceedings of the IEEE, vol. 106, issue 11, pp. 2040–2055, November 2018. DOI: 10.1109/JPROC.2018.2868961  (2.53 MB)
Luszczek, P., J. Kurzak, I. Yamazaki, D. Keffer, V. Maroulas, and J. Dongarra, Autotuning Techniques for Performance-Portable Point Set Registration in 3D,” Supercomputing Frontiers and Innovations, vol. 5, no. 4, December 2018. DOI: 10.14529/jsfi180404  (720.15 KB)
B
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)
Basic Linear Algebra Subprograms Technical (BLAST) Forum Standard,” International Journal of High Performance Computing Applications: Special Issue - Part I & II, vol. 16, no. 1-2, pp. 1-199, January 2002.
Basic Linear Algebra Subprograms Technical (BLAST) Forum Standard , January 2001.
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., J. Dongarra, G. Flegar, and E. S. Quintana-Orti, Batched Gauss-Jordan Elimination for Block-Jacobi Preconditioner Generation on GPUs,” Proceedings of the 8th International Workshop on Programming Models and Applications for Multicores and Manycores, New York, NY, USA, ACM, pp. 1–10, February 2017. DOI: 10.1145/3026937.3026940  (552.62 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. DOI: 10.1109/ScalA.2016.11
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. DOI: 10.1177/1094342014567546  (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. DOI: 10.1016/j.jocs.2018.01.005  (3.73 MB)
BDEC Pathways to Convergence: Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-08: University of Tennessee, November 2017.
Gamblin, T., P. Beckman, K. Keahey, K. Sato, M. Kondo, and G. Balazs, BDEC2 Platform White Paper,” Innovative Computing Laboratory Technical Report, no. ICL-UT-19-11: University of Tennessee, September 2019.  (30.16 KB)
McCraw, H., D. Terpstra, J. Dongarra, K. Davis, and R. Musselman, Beyond the CPU: Hardware Performance Counter Monitoring on Blue Gene/Q,” International Supercomputing Conference 2013 (ISC'13), Leipzig, Germany, Springer, June 2013.  (624.58 KB)
Dongarra, J., H. Meuer, H. D. Simon, and E. Strohmaier, Biannual Top-500 Computer Lists Track Changing Environments for Scientific Computing,” SIAM News, vol. 34, no. 9, October 2002.  (2.62 MB)
Marques, O., J. Demmel, and P. B. Vasconcelos, Bidiagonal SVD Computation via an Associated Tridiagonal Eigenproblem,” LAPACK Working Note, no. LAWN 295, ICL-UT-18-02: University of Tennessee, April 2018.  (1.53 MB)
Faverge, M., J. Langou, Y. Robert, and J. Dongarra, Bidiagonalization and R-Bidiagonalization: Parallel Tiled Algorithms, Critical Paths and Distributed-Memory Implementation,” IEEE International Parallel and Distributed Processing Symposium (IPDPS), Orlando, FL, IEEE, May 2017. DOI: 10.1109/IPDPS.2017.46  (328.15 KB)
Asch, M., T. Moore, R. M. Badia, M. Beck, P. Beckman, T. Bidot, F. Bodin, F. Cappello, A. Choudhary, B. R. de Supinski, et al., Big Data and Extreme-Scale Computing: Pathways to Convergence - Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry,” The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 435–479, July 2018. DOI: 10.1177/1094342018778123  (1.29 MB)
Angskun, T., G. Bosilca, and J. Dongarra, Binomial Graph: A Scalable and Fault- Tolerant Logical Network Topology,” Proceedings of The Fifth International Symposium on Parallel and Distributed Processing and Applications (ISPA07), Niagara Falls, Canada, Springer, August 2007.  (480.47 KB)
Dongarra, J., E. Jeannot, E. Saule, and Z. Shi, Bi-objective Scheduling Algorithms for Optimizing Makespan and Reliability on Heterogeneous Systems,” 19th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA) (submitted), San Diego, CA, June 2007.  (223.82 KB)
YarKhan, A., and J. Dongarra, Biological Sequence Alignment on the Computational Grid Using the GrADS Framework,” Future Generation Computing Systems, vol. 21, no. 6: Elsevier, pp. 980-986, June 2005.  (147.29 KB)
Danalis, A., P. Luszczek, G. Marin, J. Vetter, and J. Dongarra, BlackjackBench: Hardware Characterization with Portable Micro-Benchmarks and Automatic Statistical Analysis of Results,” IEEE International Parallel and Distributed Processing Symposium (submitted), Anchorage, AK, May 2011.
Danalis, A., P. Luszczek, G. Marin, J. Vetter, and J. Dongarra, BlackjackBench: Portable Hardware Characterization with Automated Results Analysis,” The Computer Journal, March 2013. DOI: 10.1093/comjnl/bxt057  (408.45 KB)
Nath, R., S. Tomov, and J. Dongarra, Blas for GPUs,” Scientific Computing with Multicore and Accelerators, Boca Raton, Florida, CRC Press, 2010.  (1.05 MB)
Anzt, H., E. Chow, and J. Dongarra, On block-asynchronous execution on GPUs,” LAPACK Working Note, no. 291, November 2016.  (1.05 MB)
Anzt, H., S. Tomov, M. Gates, J. Dongarra, and V. Heuveline, Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems , no. UT-CS-11-689, December 2011.  (608.95 KB)
Anzt, H., S. Tomov, M. Gates, J. Dongarra, and V. Heuveline, Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems,” ICCS 2012, Omaha, NE, June 2012.  (608.95 KB)
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)
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., 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  (1.22 MB)
Caniou, Y., E. Caron, A K W. Chang, and Y. Robert, Budget-Aware Scheduling Algorithms for Scientific Workflows with Stochastic Task Weights on Heterogeneous IaaS Cloud Platforms,” 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Vancouver, BC, Canada, IEEE, May 2018. DOI: 10.1109/IPDPSW.2018.00014  (1.31 MB)
Fagg, G., and J. Dongarra, Building and using a Fault Tolerant MPI implementation,” International Journal of High Performance Applications and Supercomputing (to appear), 00 2004.
C
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)
Gates, M., P. Luszczek, A. Abdelfattah, J. Kurzak, J. Dongarra, K. Arturov, C. Cecka, and C. Freitag, C++ API for BLAS and LAPACK,” SLATE Working Notes, no. 2, ICL-UT-17-03: Innovative Computing Laboratory, University of Tennessee, June 2017.  (1.12 MB)
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)
Fürlinger, K., and S. Moore, Capturing and Analyzing the Execution Control Flow of OpenMP Applications,” International Journal of Parallel Programming, vol. 37, no. 3, pp. 266-276, 00 2009.
Fayad, D., J. Kurzak, P. Luszczek, P. Wu, and J. Dongarra, The Case for Directive Programming for Accelerator Autotuner Optimization,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-07: University of Tennessee, October 2017.  (341.52 KB)
Kolev, T., P. Fischer, A. Abdelfattah, S. Ananthan, V. Barra, N. Beams, R. Bleile, J. Brown, R. Carson, J-S. Camier, et al., CEED ECP Milestone Report: Improve Performance and Capabilities of CEED-Enabled ECP Applications on Summit/Sierra,” ECP Milestone Reports: Zenodo, May 2020. DOI: 10.5281/zenodo.3860804  (28.12 MB)
Tomov, S., A. Abdelfattah, V. Barra, N. Beams, J. Brown, J-S. Camier, V. Dobrev, J. Dongarra, Y. Dudouit, P. Fischer, et al., CEED ECP Milestone Report: Performance Tuning of CEED Software and 1st and 2nd Wave Apps : Zenodo, October 2019. DOI: 10.5281/zenodo.3477618  (8.31 MB)
Brown, J., A. Abdelfattah, V. Barra, V. Dobrev, Y. Dudouit, P. Fischer, T. Kolev, D. Medina, M. Min, T. Ratnayaka, et al., CEED ECP Milestone Report: Public release of CEED 2.0 : Zenodo, April 2019. DOI: 10.5281/zenodo.2641316  (4.98 MB)
Luszczek, P., J. Kurzak, and J. Dongarra, Changes in Dense Linear Algebra Kernels - Decades Long Perspective,” in Solving the Schrodinger Equation: Has everything been tried? (to appear): Imperial College Press, 00 2011.
Davis, J., T. Gao, S. Chandrasekaran, H. Jagode, A. Danalis, P. Balaji, J. Dongarra, and M. Taufer, Characterization of Power Usage and Performance in Data-Intensive Applications using MapReduce over MPI,” 2019 International Conference on Parallel Computing (ParCo2019), Prague, Czech Republic, September 2019.

Pages