Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly parallel sparse solvers are essential for continuing advances in high-fidelity, multi-physics and multi-scale simulations, especially as we target exascale platforms. This paper describes the challenges, strategies and progress of the US Department of Energy Exascale Computing project towards providing sparse solvers for exascale computing platforms. We address the demands of systems with thousands of high-performance node devices where exposing concurrency, hiding latency and creating alternative algorithms become essential. The efforts described here are works in progress, highlighting current success and upcoming challenges. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.
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http://dx.doi.org/10.1098/rsta.2019.0053 | DOI Listing |
J Xray Sci Technol
December 2024
Department of Radiation and Cellular Oncology, University of Chicago, Chicago, IL, USA.
Background And Objective: Optimization based image reconstruction algorithm is an advanced algorithm in medical imaging. However, the corresponding solving algorithm is challenging because the model is usually large-scale and non-smooth. This work aims to devise a simple and convergent solver for optimization model.
View Article and Find Full Text PDFGenetics
November 2024
Corteva Agrisciences, 8305 NW 62nd Ave, Johnston, IA, USA 50131.
IEEE Trans Med Imaging
October 2024
Sci Rep
August 2024
School of Mathematics and Information, China West Normal University, Nanchong, 637009, China.
Seismic prospecting has been widely used in the exploration and development of underground geological resources, such as mineral products (e.x., coal, uranium deposit), oil and gas, groundwater, and so forth.
View Article and Find Full Text PDFIEEE Trans Vis Comput Graph
June 2024
We propose a new method for computing smooth and integrable cross fields on 2D and 3D surfaces. We first compute smooth cross fields by minimizing the Dirichlet energy. Unlike the existing optimization based approaches, our method determines the singularity configuration, i.
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