A block-asynchronous relaxation method for graphics processing units
TL;DR: This paper develops asynchronous iteration algorithms in CUDA and compares them with parallel implementations of synchronous relaxation methods on CPU- or GPU-based systems and identifies the high potential of the asynchronous methods for Exascale computing.
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About: This article is published in Journal of Parallel and Distributed Computing. The article was published on 01 Dec 2013. and is currently open access. The article focuses on the topics: Asynchronous communication & CUDA.
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Figures
Table V: Variations of the convergence behavior for 100 solver runs on FV3. 
Figure 5: Convergence for test matrix FV1 
Figure 16: Average iteration timings of CPU/GPU implementations depending on total iteration number, test matrix FV3. 
Table VII: Average iteration timings in seconds. 
Figure 17: Time to solution for CHEM97ZTZ. 
Figure 18: Time to solution for FV1.
Citations
Self-stabilizing iterative solvers
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- 17 Nov 2013
TL;DR: It is shown how to use the idea of self-stabilization, which originates in the context of distributed control, to make fault-tolerant iterative solvers, and has promise to become a useful tool for constructing resilient solvers more generally.
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Iterative Sparse Triangular Solves for Preconditioning
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TL;DR: This work proposes using an iterative approach for solving sparse triangular systems when an approximation is suitable, and demonstrates the performance gains that this approach can have on GPUs in the context of solving sparse linear systems with a preconditioned Krylov subspace method.
Automatic Recognition of Acute Myelogenous Leukemia in Blood Microscopic Images Using K-means Clustering and Support Vector Machine.
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A Block-Asynchronous Relaxation Method for Graphics Processing Units
Hartwig Anzt,Stanimire Tomov,Jack Dongarra,Vincent Heuveline +3 more
- 21 May 2012
TL;DR: A set of asynchronous iteration algorithms in CUDA developed and compared with a parallel implementation of synchronous relaxation methods on CPU-based systems shows the high potential of the asynchronous methods not only as a stand alone numerical solver for linear systems of equations fulfilling certain convergence conditions but more importantly as a smoother in multigrid methods.
Linear Algebra Software for Large-Scale Accelerated Multicore Computing
Ahmad Abdelfattah,Hartwig Anzt,Jack Dongarra,Mark Gates,Azzam Haidar,Jakub Kurzak,Piotr Luszczek,Stanimire Tomov,Ichitaro Yamazaki,Asim YarKhan +9 more
TL;DR: The state-of-the-art design and implementation practices for the acceleration of the predominant linear algebra algorithms on large-scale accelerated multicore systems are presented and the development of innovativelinear algebra algorithms using three technologies – mixed precision arithmetic, batched operations, and asynchronous iterations – that are currently of high interest for accelerated multicores systems are emphasized.
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The International Exascale Software Project roadmap
Jack Dongarra,Pete Beckman,Terry Moore,Patrick Aerts,Giovanni Aloisio,Jean-Claude Andre,David Barkai,Jean-Yves Berthou,Taisuke Boku,Bertrand Braunschweig,Franck Cappello,Barbara Chapman,Xuebin Chi,Alok Choudhary,Sudip S. Dosanjh,Thom H. Dunning,Sandro Fiore,Al Geist,Bill Gropp,Robert W. Harrison,Mark Hereld,Michael A. Heroux,Adolfy Hoisie,Koh Hotta,Zhong Jin,Yutaka Ishikawa,Fred Johnson,Sanjay Kale,Richard Kenway,David E. Keyes,Bill Kramer,Jesús Labarta,Alain Lichnewsky,Thomas Lippert,Bob Lucas,Barney Maccabe,Satoshi Matsuoka,Paul Messina,Peter Michielse,Bernd Mohr,Matthias S. Mueller,Wolfgang E. Nagel,Hiroshi Nakashima,Michael E. Papka,Daniel A. Reed,Mitsuhisa Sato,Edward Seidel,John Shalf,David Skinner,Marc Snir,Thomas Sterling,Rick Stevens,Frederick H. Streitz,Bob Sugar,Shinji Sumimoto,William Tang,John Taylor,Rajeev Thakur,Anne E. Trefethen,Mateo Valero,Aad J. van der Steen,Jeffrey S. Vetter,Peg Williams,Robert W. Wisniewski,Katherine Yelick +64 more
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TL;DR: The work of the community to prepare for the challenges of exascale computing is described, ultimately combing their efforts in a coordinated International Exascale Software Project.
Multigrid Smoothers for Ultraparallel Computing
TL;DR: It is shown, in particular, that the popular hybrid GS algorithm has multigrid smoothing properties which are independent of the number of processors in many practical applications, provided that the problem size per processor is large enough.