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Titlebook: Euro-Par 2016: Parallel Processing Workshops; Euro-Par 2016 Intern Frédéric Desprez,Pierre-Fran?ois Dutot,Josef Weide Conference proceeding

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樓主: Sentry
21#
發(fā)表于 2025-3-25 04:27:54 | 只看該作者
Das endliche, am Ende offene Kabel, providing a level of automation necessary for scaling the course to a large number of students. In contrast to other solutions, the exploited Platform as a Service model provides the ability to quickly reuse this approach by other PDC educators without installation of the platform.
22#
發(fā)表于 2025-3-25 09:58:45 | 只看該作者
Karl-Heinz Hellwege,Werner Knappe approach in the context of the dense Cholesky factorization kernel implemented on top of the StarPU task-based runtime system. We present experimental results showing that our solution outperforms state of the art implementations.
23#
發(fā)表于 2025-3-25 13:20:19 | 只看該作者
24#
發(fā)表于 2025-3-25 19:04:13 | 只看該作者
25#
發(fā)表于 2025-3-25 20:13:05 | 只看該作者
https://doi.org/10.1007/978-3-663-05957-8ters. We discuss various methods to effectively exploit the available on-node parallelism to increase parallel efficiency and provide detailed performance analysis on two leading Cray supercomputers. In addition, we also present performance results obtained on the Intel Knights Landing processor.
26#
發(fā)表于 2025-3-26 01:45:47 | 只看該作者
Using Everest Platform for Teaching Parallel and Distributed Computing providing a level of automation necessary for scaling the course to a large number of students. In contrast to other solutions, the exploited Platform as a Service model provides the ability to quickly reuse this approach by other PDC educators without installation of the platform.
27#
發(fā)表于 2025-3-26 05:46:24 | 只看該作者
Resource Aggregation for Task-Based Cholesky Factorization on Top of Heterogeneous Machines approach in the context of the dense Cholesky factorization kernel implemented on top of the StarPU task-based runtime system. We present experimental results showing that our solution outperforms state of the art implementations.
28#
發(fā)表于 2025-3-26 11:27:34 | 只看該作者
29#
發(fā)表于 2025-3-26 12:55:02 | 只看該作者
A Data-Parallel ILUPACK for Sparse General and Symmetric Indefinite Linear Systems SQMR method for sparse symmetric indefinite problems in ILUPACK. The evaluation on a NVIDIA Kepler GPU shows a sensible reduction of the execution time, while maintaining the convergence rate and numerical properties of the original ILUPACK solver.
30#
發(fā)表于 2025-3-26 16:55:54 | 只看該作者
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