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A

Gates, M., H. Anzt, J. Kurzak, and J. Dongarra, “Accelerating Collaborative Filtering for Implicit Feedback Datasets using GPUs,” 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, IEEE, November 2015.

(1.02 MB)

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)

Baboulin, M., A. Buttari, J. Dongarra, J. Kurzak, J. Langou, J. Langou, P. Luszczek, and S. Tomov, “Accelerating Scientific Computations with Mixed Precision Algorithms,” Computer Physics Communications, vol. 180, issue 12, pp. 2526-2533, December 2009.

(402.69 KB)

Yamazaki, I., T. Mary, J. Kurzak, S. Tomov, and J. Dongarra, “Access-averse Framework for Computing Low-rank Matrix Approximations,” First International Workshop on High Performance Big Graph Data Management, Analysis, and Mining, Washington, DC, October 2014.

Donfack, S., J. Dongarra, M. Faverge, M. Gates, J. Kurzak, P. Luszczek, and I. Yamazaki, “On Algorithmic Variants of Parallel Gaussian Elimination: Comparison of Implementations in Terms of Performance and Numerical Properties,” University of Tennessee Computer Science Technical Report, no. UT-CS-13-715, July 2013, 2012.

(358.98 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.

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.

(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)

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.

(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.

(720.15 KB)

B

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.

(1.22 MB)

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. 04, 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. 02, ICL-UT-17-03: Innovative Computing Laboratory, University of Tennessee, June 2017.

(1.12 MB)

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)

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.

Buttari, A., J. Langou, J. Kurzak, and J. Dongarra, “A Class of Parallel Tiled Linear Algebra Algorithms for Multicore Architectures,” University of Tennessee Computer Science Technical Report, no. UT-CS-07-600 (also LAPACK Working Note 191), January 2007.

(274.74 KB)

Buttari, A., J. Langou, J. Kurzak, and J. Dongarra, “A Class of Parallel Tiled Linear Algebra Algorithms for Multicore Architectures,” Parallel Computing, vol. 35, pp. 38-53, 00 2009.

(274.74 KB)

Buttari, A., J. Langou, J. Kurzak, and J. Dongarra, “A Class of Parallel Tiled Linear Algebra Algorithms for Multicore Architectures,” Parallel Computing (to appear), 00 2010.

(612.23 KB)

D

Haidar, A., J. Kurzak, G. Pichon, and M. Faverge, “ A Data Flow Divide and Conquer Algorithm for Multicore Architecture,” 29th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Hyderabad, India, IEEE, May 2015.

(535.44 KB)

Dongarra, J., J. Kurzak, P. Luszczek, and S. Tomov, “Dense Linear Algebra on Accelerated Multicore Hardware,” High Performance Scientific Computing: Algorithms and Applications, London, UK, Springer-Verlag, 00 2012.

Kurzak, J., H. Ltaeif, J. Dongarra, and R. M. Badia, “Dependency-Driven Scheduling of Dense Matrix Factorizations on Shared-Memory Systems,” PPAM 2009, Poland, September 2009.

Yamazaki, I., J. Kurzak, P. Luszczek, and J. Dongarra, “Design and Implementation of a Large Scale Tree-Based QR Decomposition Using a 3D Virtual Systolic Array and a Lightweight Runtime,” Workshop on Large-Scale Parallel Processing, IPDPS 2014, Phoenix, AZ, IEEE, May 2014.

(398.16 KB)

Kurzak, J., P. Luszczek, I. Yamazaki, Y. Robert, and J. Dongarra, “Design and Implementation of the PULSAR Programming System for Large Scale Computing,” Supercomputing Frontiers and Innovations, vol. 4, issue 1, 2017.

(764.96 KB)

Kurzak, J., P. Wu, M. Gates, I. Yamazaki, P. Luszczek, G. Ragghianti, and J. Dongarra, “Designing SLATE: Software for Linear Algebra Targeting Exascale,” SLATE Working Notes, no. 03, ICL-UT-17-06: Innovative Computing Laboratory, University of Tennessee, October 2017.

(2.8 MB)

Bosilca, G., A. Bouteiller, A. Danalis, M. Faverge, A. Haidar, T. Herault, J. Kurzak, J. Langou, P. Lemariner, H. Ltaeif, et al., “Distributed Dense Numerical Linear Algebra Algorithms on Massively Parallel Architectures: DPLASMA,” University of Tennessee Computer Science Technical Report, UT-CS-10-660, September 2010.

(366.26 KB)

Bosilca, G., A. Bouteiller, A. Danalis, M. Faverge, A. Haidar, T. Herault, J. Kurzak, J. Langou, P. Lemariner, H. Ltaeif, et al., “Distributed-Memory Task Execution and Dependence Tracking within DAGuE and the DPLASMA Project,” Innovative Computing Laboratory Technical Report, no. ICL-UT-10-02, 00 2010.

(400.75 KB)

E

YarKhan, A., J. Kurzak, A. Abdelfattah, and J. Dongarra, “An Empirical View of SLATE Algorithms on Scalable Hybrid System,” Innovative Computing Laboratory Technical Report, no. ICL-UT-19-08: University of Tennessee, Knoxville, September 2019.

(441.16 KB)

Anzt, H., B. Haugen, J. Kurzak, P. Luszczek, and J. Dongarra, “Experiences in autotuning matrix multiplication for energy minimization on GPUs,” Concurrency in Computation: Practice and Experience, vol. 27, issue 17, pp. 5096-5113, December 2015.

(1.98 MB)

Anzt, H., B. Haugen, J. Kurzak, P. Luszczek, and J. Dongarra, “Experiences in Autotuning Matrix Multiplication for Energy Minimization on GPUs,” Concurrency and Computation: Practice and Experience, vol. 27, issue 17, pp. 5096 - 5113, Oct 12, 2015.

(1.99 MB)

Buttari, A., J. Dongarra, J. Kurzak, J. Langou, J. Langou, P. Luszczek, and S. Tomov, “Exploiting Mixed Precision Floating Point Hardware in Scientific Computations,” In High Performance Computing and Grids in Action (to appear), Amsterdam, IOS Press, 00 2007.

(122.01 KB)

Buttari, A., J. Dongarra, J. Kurzak, J. Langou, J. Langou, P. Luszczek, and S. Tomov, “Exploiting Mixed Precision Floating Point Hardware in Scientific Computations,” in High Performance Computing and Grids in Action, Amsterdam, IOS Press, January 2008.

(92.95 KB)

Langou, J., J. Langou, P. Luszczek, J. Kurzak, A. Buttari, and J. Dongarra, “Exploiting the Performance of 32 bit Floating Point Arithmetic in Obtaining 64 bit Accuracy,” University of Tennessee Computer Science Tech Report, no. UT-CS-06-574, LAPACK Working Note #175, April 2006.

(221.39 KB)

F

Alvaro, W., J. Kurzak, and J. Dongarra, “Fast and Small Short Vector SIMD Matrix Multiplication Kernels for the CELL Processor,” University of Tennessee Computer Science Technical Report, no. UT-CS-08-609, (also LAPACK Working Note 189), January 2008.

(500.99 KB)

Bosilca, G., A. Bouteiller, A. Danalis, M. Faverge, A. Haidar, T. Herault, J. Kurzak, J. Langou, P. Lemariner, H. Ltaeif, et al., “Flexible Development of Dense Linear Algebra Algorithms on Massively Parallel Architectures with DPLASMA,” Proceedings of the Workshops of the 25th IEEE International Symposium on Parallel and Distributed Processing (IPDPS 2011 Workshops), Anchorage, Alaska, USA, IEEE, pp. 1432-1441, May 2011.

(1.26 MB)

Kurzak, J., and J. Dongarra, “Fully Dynamic Scheduler for Numerical Computing on Multicore Processors,” University of Tennessee Computer Science Department Technical Report, UT-CS-09-643 (Also LAPACK Working Note 220), 00 2009.

(488.24 KB)

I

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)

Kurzak, J., H. Anzt, M. Gates, and J. Dongarra, “Implementation and Tuning of Batched Cholesky Factorization and Solve for NVIDIA GPUs,” IEEE Transactions on Parallel and Distributed Systems, no. 1045-9219, November 2015.

Kurzak, J., and J. Dongarra, “Implementation of Mixed Precision in Solving Systems of Linear Equations on the Cell Processor,” Concurrency and Computation: Practice and Experience, vol. 19, no. 10, pp. 1371-1385, July 2007.

(453.78 KB)

Abdelfattah, A., M. Gates, J. Kurzak, P. Luszczek, and J. Dongarra, “Implementation of the C++ API for Batch BLAS,” SLATE Working Notes, no. 07, ICL-UT-18-04: Innovative Computing Laboratory, University of Tennessee, June 2018.

(1.07 MB)

Kurzak, J., and J. Dongarra, “Implementation of the Mixed-Precision High Performance LINPACK Benchmark on the CELL Processor,” University of Tennessee Computer Science Tech Report, no. UT-CS-06-580, LAPACK Working Note #177, September 2006.

(506.18 KB)

Kurzak, J., R. Nath, P. Du, and J. Dongarra, “An Implementation of the Tile QR Factorization for a GPU and Multiple CPUs,” Applied Parallel and Scientific Computing, vol. 7133, pp. 248-257, 00 2012.

(623.5 KB)

Aupy, G., M. Faverge, Y. Robert, J. Kurzak, P. Luszczek, and J. Dongarra, “Implementing a systolic algorithm for QR factorization on multicore clusters with PaRSEC,” Lawn 277, no. UT-CS-13-709, May 2013.

(298.63 KB)

Kurzak, J., and J. Dongarra, “Implementing Linear Algebra Routines on Multi-Core Processors with Pipelining and a Look Ahead,” University of Tennessee Computer Science Tech Report, UT-CS-06-581, LAPACK Working Note #178, January 2006.

(304.4 KB)

Haidar, A., P. Luszczek, J. Kurzak, and J. Dongarra, “An Improved Parallel Singular Value Algorithm and Its Implementation for Multicore Hardware,” Supercomputing 2013, Denver, CO, November 2013.

Haidar, A., P. Luszczek, J. Kurzak, and J. Dongarra, “An Improved Parallel Singular Value Algorithm and Its Implementation for Multicore Hardware,” University of Tennessee Computer Science Technical Report (also LAWN 283), no. ut-eecs-13-720: University of Tennessee, October 2013.

(1.23 MB)

L

Gates, M., A. Charara, J. Kurzak, A. YarKhan, I. Yamazaki, and J. Dongarra, “Least Squares Performance Report,” SLATE Working Notes, no. 09, ICL-UT-18-10: Innovative Computing Laboratory, University of Tennessee, December 2018.

(1.76 MB)

Kurzak, J., M. Gates, A. Charara, A. YarKhan, and J. Dongarra, “Least Squares Solvers for Distributed-Memory Machines with GPU Accelerators,” ACM International Conference on Supercomputing (ICS '19), Phoenix, Arizona, ACM, pp. 117–126, June 2019.

(1.63 MB)

Buttari, A., J. Dongarra, and J. Kurzak, “Limitations of the Playstation 3 for High Performance Cluster Computing,” University of Tennessee Computer Science Technical Report, UT-CS-07-597 (Also LAPACK Working Note 185), 00 2007.

(171.01 KB)

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.

Kurzak, J., M. Gates, I. Yamazaki, A. Charara, A. YarKhan, J. Finney, G. Ragghianti, P. Luszczek, and J. Dongarra, “Linear Systems Performance Report,” SLATE Working Notes, no. 08, ICL-UT-18-08: Innovative Computing Laboratory, University of Tennessee, September 2018.

(1.64 MB)

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