Publications

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2013
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)
Dongarra, J., M. Faverge, T. Herault, M. Jacquelin, J. Langou, and Y. Robert, “Hierarchical QR Factorization Algorithms for Multi-core Cluster Systems,” Parallel Computing, vol. 39, issue 4-5, pp. 212-232, May 2013.  (1.43 MB)
2015
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., J. Dongarra, K. Kabir, M. Gates, P. Luszczek, S. Tomov, and Y. Jia, “HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi,” Scientific Programming, vol. 23, issue 1, January 2015.  (553.94 KB)
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.  (699.5 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)
2017
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.
2018
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)
2020
Brown, C., A. Abdelfattah, S. Tomov, and J. Dongarra, “Design, Optimization, and Benchmarking of Dense Linear Algebra Algorithms on AMD GPUs,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-12: University of Tennessee, August 2020.  (476.36 KB)
Lopez, F., and T. Mary, “Mixed Precision LU Factorization on GPU Tensor Cores: Reducing Data Movement and Memory Footprint,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-13: University of Tennessee, September 2020.  (409 KB)