Publications
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Filters: Author is Hartwig Anzt [Clear All Filters]
Variable-Size Batched Condition Number Calculation on GPUs,”
SBAC-PAD, Lyon, France, September 2018.
(509.3 KB)
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Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-σ formats on NVIDIA GPUs,”
University of Tennessee Computer Science Technical Report, no. UT-EECS-14-727: University of Tennessee, April 2014.
(578.11 KB)
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Accelerating the LOBPCG method on GPUs using a blocked Sparse Matrix Vector Product,”
Spring Simulation Multi-Conference 2015 (SpringSim'15), Alexandria, VA, SCS, April 2015.
(1.46 MB)
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Ginkgo: A High Performance Numerical Linear Algebra Library,”
Journal of Open Source Software, vol. 5, issue 52, August 2020.
(721.84 KB)
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Updating Incomplete Factorization Preconditioners for Model Order Reduction,”
Numerical Algorithms, vol. 73, issue 3, no. 3, pp. 611–630, February 2016.
(565.34 KB)
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Bringing High Performance Computing to Big Data Algorithms,”
Handbook of Big Data Technologies: Springer, 2017.
(1.22 MB)
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A Block-Asynchronous Relaxation Method for Graphics Processing Units,”
Journal of Parallel and Distributed Computing, vol. 73, issue 12, pp. 1613–1626, December 2013.
(1.08 MB)
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