Publications

Export 1026 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 
G
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)
Gates, M., A. Charara, J. Kurzak, D. Sukkari, A. YarKhan, and J. Dongarra, SLATE Working Note 13: Implementing Singular Value and Symmetric Eigenvalue Solvers,” SLATE Working Notes, no. 13, ICL-UT-19-07: Innovative Computing Laboratory, University of Tennessee, September 2019.  (4.45 MB)
Gates, M., S. Tomov, and J. Dongarra, Accelerating the SVD Two Stage Bidiagonal Reduction and Divide and Conquer Using GPUs,” Parallel Computing, vol. 74, pp. 3–18, May 2018. DOI: 10.1016/j.parco.2017.10.004
Gates, M., MAGMA Tutorial , Atlanta, GA, Keeneland Workshop, February 2012.  (2.47 MB)
Gates, M., A. Charara, J. Kurzak, and J. Dongarra, SLATE Users' Guide,” SLATE Working Notes, no. 10, ICL-UT-19-01: Innovative Computing Laboratory, University of Tennessee, January 2019.
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)
Gates, M., A. Charara, J. Kurzak, A. YarKhan, I. Yamazaki, and J. Dongarra, Least Squares Performance Report,” SLATE Working Notes, no. 9, ICL-UT-18-10: Innovative Computing Laboratory, University of Tennessee, December 2018.  (1.76 MB)
Genet, D., A. Guermouche, and G. Bosilca, Assembly Operations for Multicore Architectures using Task-Based Runtime Systems,” Euro-Par 2014, Porto, Portugal, Springer International Publishing, August 2014.  (481.52 KB)
Gerndt, M., and K. Fürlinger, Specification and detection of performance problems with ASL,” Concurrency and Computation: Practice and Experience, vol. 19, no. 11: John Wiley and Sons Ltd., pp. 1451-1464, January 2007.
Ghysels, P., S. Li, A. YarKhan, and J. Dongarra, Initial Integration and Evaluation of SLATE and STRUMPACK,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-11: University of Tennessee, December 2018.  (249.78 KB)
Giraud, L., J. Langou, and G.. Sylvand, On the Parallel Solution of Large Industrial Wave Propagation Problems,” Journal of Computational Acoustics (to appear), January 2005.  (1.08 MB)
Giraud, L., J. Langou, M. Rozložník, and J. van den Eshof, Rounding Error Analysis of the Classical Gram-Schmidt Orthogonalization Process,” Numerische Mathematik, vol. 101, no. 1, pp. 87-100, January 2005.  (157.48 KB)
Giraud, L., A. Haidar, and Y. Saad, Sparse approximations of the Schur complement for parallel algebraic hybrid solvers in 3D,” Numerical Mathematics: Theory, Methods and Applications, vol. 3, no. 3, Beijing, Golbal Science Press, pp. 64-82, 00 2010.
Giraud, L., A. Haidar, and S. Pralet, Using multiple levels of parallelism to enhance the performance of domain decomposition solvers,” Parallel Computing, vol. 36, no. 5-6: Elsevier journals, pp. 285-296, 00 2010.  (418.57 KB)
Graham, R. L., R. Brightwell, B. Barrett, G. Bosilca, and J. Pjesivac–Grbovic, An Evaluation of Open MPI's Matching Transport Layer on the Cray XT,” EuroPVM/MPI 2007, September 2007.  (369.01 KB)
Graham, R. L., G. M. Shipman, B. Barrett, R. Castain, G. Bosilca, and A. Lumsdaine, A High-Performance, Heterogeneous MPI,” HeteroPar 2006, Barcelona, Spain, September 2006.  (193.73 KB)
Graham, R. L., G. Bosilca, and J. Pjesivac–Grbovic, A Comparison of Application Performance Using Open MPI and Cray MPI,” Cray User Group, CUG 2007, May 2007.  (248.83 KB)
Gruetzmacher, T., T. Cojean, G. Flegar, F. Göbel, and H. Anzt, A Customized Precision Format Based on Mantissa Segmentation for Accelerating Sparse Linear Algebra,” Concurrency and Computation: Practice and Experience, vol. 40319, issue 262, January 2019. DOI: 10.1002/cpe.5418
Guidry, M., and A. Haidar, On the Design, Autotuning, and Optimization of GPU Kernels for Kinetic Network Simulations Using Fast Explicit Integration and GPU Batched Computation , Oak Ridge, TN, Joint Institute for Computational Sciences Seminar Series, Presentation, September 2015.  (17.25 MB)
Gustavson, F. G., J. Wasniewski, J. Dongarra, and J. Langou, Rectangular Full Packed Format for Cholesky's Algorithm: Factorization, Solution and Inversion,” ACM TOMS (to appear), 00 2009.  (896.03 KB)
Gustavson, F. G., J. Wasniewski, and J. Dongarra, Rectangular Full Packed Format for Cholesky's Algorithm: Factorization, Solution and Inversion,” University of Tennessee Computer Science Technical Report, UT-CS-08-614 (also LAPACK Working Note 199), April 2008.  (896.03 KB)
Gustavson, F. G., J. Wasniewski, J. Dongarra, J. Herrero, and J. Langou, Level-3 Cholesky Factorization Routines Improve Performance of Many Cholesky Algorithms,” ACM Transactions on Mathematical Software (TOMS), vol. 39, issue 2, February 2013. DOI: 10.1145/2427023.2427026  (439.46 KB)
Gustavson, F. G., J. Wasniewski, J. Dongarra, and J. Langou, Rectangular Full Packed Format for Cholesky's Algorithm: Factorization, Solution and Inversion,” ACM Transactions on Mathematical Software (TOMS), vol. 37, no. 2, April 2010.  (896.03 KB)
Gustavson, F. G., J. Wasniewski, J. Dongarra, and J. Langou, Rectangular Full Packed Format for Cholesky’s Algorithm: Factorization, Solution, and Inversion,” ACM Transactions on Mathematical Software (TOMS), vol. 37, no. 2, Atlanta, GA, April 2010.  (896.03 KB)
Gustavson, F. G., J. Wasniewski, and J. Dongarra, Level-3 Cholesky Kernel Subroutine of a Fully Portable High Performance Minimal Storage Hybrid Format Cholesky Algorithm,” ACM TOMS (submitted), also LAPACK Working Note (LAWN) 211, 00 2010.  (190.2 KB)
H
Hadri, B., H. Ltaeif, E. Agullo, and J. Dongarra, Tall and Skinny QR Matrix Factorization Using Tile Algorithms on Multicore Architectures,” Innovative Computing Laboratory Technical Report (also LAPACK Working Note 222 and CS Tech Report UT-CS-09-645), no. ICL-UT-09-03, September 2009.  (464.23 KB)
Hadri, B., H. Ltaeif, E. Agullo, and J. Dongarra, Tile QR Factorization with Parallel Panel Processing for Multicore Architectures,” accepted in 24th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2010), Atlanta, GA, December 2009.
Hadri, B., H. Ltaeif, E. Agullo, and J. Dongarra, Enhancing Parallelism of Tile QR Factorization for Multicore Architectures,” Submitted to Transaction on Parallel and Distributed Systems, December 2009.  (464.23 KB)
Hadri, B., E. Agullo, and J. Dongarra, Tile QR Factorization with Parallel Panel Processing for Multicore Architectures,” 24th IEEE International Parallel and Distributed Processing Symposium (submitted), 00 2010.  (313.98 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)
Haidar, A., S. Tomov, A. Abdelfattah, I. Yamazaki, and J. Dongarra, MAtrix, TEnsor, and Deep-learning Optimized Routines (MATEDOR) , Washington, DC, NSF PI Meeting, Poster, April 2018. DOI: 10.6084/m9.figshare.6174143.v3  (2.4 MB)
Haidar, A., S. Tomov, J. Dongarra, R. Solcà, and T. C. Schulthess, Leading Edge Hybrid Multi-GPU Algorithms for Generalized Eigenproblems in Electronic Structure Calculations,” International Supercomputing Conference (ISC), Lecture Notes in Computer Science, vol. 7905, Leipzig, Germany, Springer Berlin Heidelberg, pp. 67-80, June 2013. DOI: 10.1007/978-3-642-38750-0_6  (2.14 MB)
Haidar, A., H. Ltaeif, and J. Dongarra, Toward High Performance Divide and Conquer Eigensolver for Dense Symmetric Matrices.,” Submitted to SIAM Journal on Scientific Computing (SISC), 00 2011.
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)
Haidar, A., H. Ltaeif, and J. Dongarra, Toward High Performance Divide and Conquer Eigensolver for Dense Symmetric Matrices,” SIAM Journal on Scientific Computing (Accepted), July 2012.
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, Efficient Eigensolver Algorithms on Accelerator Based Architectures,” 2015 SIAM Conference on Applied Linear Algebra (SIAM LA), Atlanta, GA, SIAM, October 2015.  (6.98 MB)
Haidar, A., K. Kabir, D. Fayad, S. Tomov, and J. Dongarra, Out of Memory SVD Solver for Big Data,” 2017 IEEE High Performance Extreme Computing Conference (HPEC'17), Waltham, MA, IEEE, September 2017.  (1.33 MB)
Haidar, A., T. Dong, P. Luszczek, S. Tomov, and J. Dongarra, Optimization for Performance and Energy for Batched Matrix Computations on GPUs,” 8th Workshop on General Purpose Processing Using GPUs (GPGPU 8), San Francisco, CA, ACM, February 2015. DOI: 10.1145/2716282.2716288  (699.5 KB)
Haidar, A., P. Luszczek, and J. Dongarra, New Algorithm for Computing Eigenvectors of the Symmetric Eigenvalue Problem,” Workshop on Parallel and Distributed Scientific and Engineering Computing, IPDPS 2014 (Best Paper), Phoenix, AZ, IEEE, May 2014. DOI: 10.1109/IPDPSW.2014.130  (2.33 MB)
Haidar, A., H. Ltaeif, and J. Dongarra, Parallel Reduction to Condensed Forms for Symmetric Eigenvalue Problems using Aggregated Fine-Grained and Memory-Aware Kernels,” University of Tennessee Computer Science Technical Report, UT-CS-11-677, (also Lawn254), August 2011.  (636.01 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)
Haidar, A., B. Brock, S. Tomov, M. Guidry, J. Jay Billings, D. Shyles, and J. Dongarra, Performance Analysis and Acceleration of Explicit Integration for Large Kinetic Networks using Batched GPU Computations,” 2016 IEEE High Performance Extreme Computing Conference (HPEC ‘16), Waltham, MA, IEEE, September 2016.  (480.29 KB)
Haidar, A., H. Ltaeif, and J. Dongarra, Parallel Reduction to Condensed Forms for Symmetric Eigenvalue Problems using Aggregated Fine-Grained and Memory-Aware Kernels,” Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC11), Seattle, WA, November 2011.  (636.01 KB)
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., 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 , Frankfurt, Germany, ISC High Performance (ISC18), Best Poster Award, June 2018.  (3.01 MB)
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., P. Luszczek, S. Tomov, and J. Dongarra, Heterogeneous Acceleration for Linear Algebra in Mulit-Coprocessor Environments,” VECPAR 2014, Eugene, OR, June 2014.  (276.52 KB)
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., S. Tomov, K. Arturov, M. Guney, S. Story, and J. Dongarra, LU, QR, and Cholesky Factorizations: Programming Model, Performance Analysis and Optimization Techniques for the Intel Knights Landing Xeon Phi,” IEEE High Performance Extreme Computing Conference (HPEC'16), Waltham, MA, IEEE, September 2016.  (943.23 KB)
Haidar, A., P. Wu, S. Tomov, and J. Dongarra, Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers,” ScalA17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, ACM.  (766.35 KB)

Pages