Search Results - "Two-sided factorization algorithms"

Performance Analysis and Optimisation of Two-sided Factorization Algorithms for Heterogeneous Platform

Authors: Jack Dongarra Azzam Haidar Khairul Kabir et al.

Source: Procedia Computer Science. 51:180-190

Subject Terms: Xeon Phi, Multicore, Eigensolver, 0101 mathematics, 01 natural sciences, Task-based programming

Access URL: https://core.ac.uk/display/82115526
http://www.sciencedirect.com/science/article/pii/S1877050915010303
http://icl.cs.utk.edu/news_pub/submissions/magma_mic_two_sided.pdf
https://dblp.uni-trier.de/db/conf/iccS/iccS2015.html#KabirHTD15
https://www.sciencedirect.com/science/article/pii/S1877050915010303
http://www.netlib.org/utk/people/JackDongarra/PAPERS/1-s2.0-S1877050915010303-main.pdf

Performance Analysis and Optimisation of Two-sided Factorization Algorithms for Heterogeneous Platform.

Authors: Kabir, Khairul Haidar, Azzam Tomov, Stanimire et al.

Source: Procedia Computer Science. 2015, Vol. 51, p180-190. 11p.

Subject Terms: Factorization, Performance evaluation, Nanostructures, Mathematical optimization, Algorithms, Singular value decomposition

Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices

Authors: Jack Dongarra Tingxing Dong Stanimire Tomov et al.

Source: Dong, T, Haidar, A, Tomov, S & Dongarra, J 2017, Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices. in Procedia Computer Science. vol. 108, pp. 1008-1018. https://doi.org/10.1016/j.procs.2017.05.237

Subject Terms: two-sided factorization algorithms, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Hardware accelerators, 0101 mathematics, batched, Singular Value Problems, 01 natural sciences

File Description: application/pdf

Access URL: https://research.manchester.ac.uk/en/publications/d652df67-1aa0-4b67-b45c-8b7f9db562d6
https://doi.org/10.1016/j.procs.2017.05.237
https://www.sciencedirect.com/science/article/pii/S1877050917308645
https://www.icl.utk.edu/publications/optimizing-svd-bidiagonalization-process-batch-small-matrices
https://www.icl.utk.edu/files/publications/2017/icl-utk-953-2017.pdf
https://www.research.manchester.ac.uk/portal/files/57088796/optimizing_the_svd.pdf
https://core.ac.uk/display/83923148
https://www.sciencedirect.com/science/article/abs/pii/S1877050917308645
https://research.manchester.ac.uk/en/publications/d652df67-1aa0-4b67-b45c-8b7f9db562d6
https://pure.manchester.ac.uk/ws/files/57088796/optimizing_the_svd.pdf
https://doi.org/10.1016/j.procs.2017.05.237

Accelerating the SVD bi-diagonalization of a batch of small matrices using GPUs

Authors: Tingxing Dong Azzam Haidar Jack Dongarra et al.

Source: Dong, T, Haidar, A, Tomov, S & Dongarra, J 2018, 'Accelerating the SVD Bidiagonalization of a Batch of Small Matrices using GPUs', Journal of Computational Science, vol. 26, pp. 237-245. https://doi.org/10.1016/j.jocs.2018.01.007

Subject Terms: Batched, Numerical linear algebra, 0202 electrical engineering, electronic engineering, information engineering, Two-sided factorization algorithms, 02 engineering and technology, Hardware accelerators, Eigenvalue and singular value problems

File Description: application/pdf

Access URL: https://www.research.manchester.ac.uk/portal/files/65822562/1_s2.0_S187775031731150X_main.pdf
https://www.research.manchester.ac.uk/portal/files/65822562/1_s2.0_S187775031731150X_main.pdf
https://www.sciencedirect.com/science/article/pii/S187775031731150X#!
https://www.research.manchester.ac.uk/portal/en/publications/accelerating-the-svd-bidiagonalization-of-a-batch-of-small-matrices-using-gpus(52d77474-7ce1-47eb-9ae2-c010a09f2355).html
https://www.sciencedirect.com/science/article/pii/S187775031731150X
https://doi.org/10.1016/j.jocs.2018.01.007
https://www.icl.utk.edu/publications/accelerating-svd-bi-diagonalization-batch-small-matrices-using-gpus

Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices.

Authors: Dong, Tingxing Haidar, Azzam Tomov, Stanimire et al.

Source: Procedia Computer Science. 2017, Vol. 108, p1008-1018. 11p.

Subject Terms: Graphics processing units, Singular value decomposition, Mathematical optimization, Factorization, Linear algebra, Subroutines (Computer programs)

Accelerating the SVD bi-diagonalization of a batch of small matrices using GPUs.

Authors: Dong, Tingxing Haidar, Azzam Tomov, Stanimire et al.

Source: Journal of Computational Science. May2018, Vol. 26, p237-245. 9p.

Subject Terms: Singular value decomposition, Graphics processing units, Software versioning, Linear algebra, Factorization

Silent Data Corruption Resilient Two-sided Matrix Factorizations

Authors: Zizhong Chen Xin Liang Qiang Guan et al.

Source: Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. :415-427

Subject Terms: 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences

Similarity ( range and kNN) queries processing on an Intel Xeon Phi coprocessor.

Authors: Toledo, Carlos Barrientos, Ricardo Ávila, Andrés

Source: Cluster Computing; Mar2016, Vol. 19 Issue 1, p57-71, 15p

Subject Terms: INFORMATION technology research, METRIC spaces, COMPUTER scheduling, GRAPHICS processing units

Company/Entity: NVIDIA Corp.

Tridiagonalization of a Symmetric Dense Matrix on a GPU Cluster.

Authors: Yamazaki, Ichitaro Dong, Tingxing Tomov, Stanimire et al.

Source: 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops & Phd Forum; 2013, p1070-1079, 10p

Silent Data Corruption Resilient Two-sided Matrix Factorizations

Authors: Wu, Panruo DeBardeleben, Nathan Guan, Qiang et al.

Contributors: Wu, Panruo DeBardeleben, Nathan Guan, Qiang et al.

Source: ACM SIGPLAN Notices ; volume 52, issue 8, page 415-427 ; ISSN 0362-1340 1558-1160

Availability: https://doi.org/10.1145/3155284.3018750
https://dl.acm.org/doi/10.1145/3155284.3018750
https://dl.acm.org/doi/pdf/10.1145/3155284.3018750

Scientific Computing with Multicore and Accelerators

Authors: Jakub Kurzak David A. Bader Jack Dongarra

Resource Type: eBook.

Subjects: Engineering--Data processing, Science--Data processing, Multiprocessors, High performance computing

Categories: COMPUTERS / General, COMPUTERS / Programming / Games, MATHEMATICS / Arithmetic, MATHEMATICS / Number Systems