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Titlebook: High Performance Computing; 30th International C Julian M. Kunkel,Thomas Ludwig Conference proceedings 2015 Springer International Publishi

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21#
發(fā)表于 2025-3-25 03:33:01 | 只看該作者
22#
發(fā)表于 2025-3-25 11:02:38 | 只看該作者
Parallel Efficient Sparse Matrix-Matrix Multiplication on Multicore Platforms,rform the best published GPU implementation of SpGEMM on nVidia GTX Titan and on AMD Radeon HD 7970 by up?to 7.3X and 4.5X, respectively on their published datasets. We demonstrate good multi-core scalability (geomean speedup of 18.2X using 28 threads) as compared to MKL which gets 7.5X scaling on 28 threads.
23#
發(fā)表于 2025-3-25 12:07:53 | 只看該作者
Large-Scale Neo-Heterogeneous Programming and Optimization of SNP Detection on Tianhe-2,rst SNP detection tool empowered by Xeon Phi. We achieved a 45x speedup on a single node of Tianhe-2, without any loss in precision. Moreover, mSNP showed promising scalability on 4,096 nodes on Tianhe-2.
24#
發(fā)表于 2025-3-25 16:22:54 | 只看該作者
25#
發(fā)表于 2025-3-25 22:14:19 | 只看該作者
26#
發(fā)表于 2025-3-26 00:13:15 | 只看該作者
On the Design, Development, and Analysis of Optimized Matrix-Vector Multiplication Routines for Cop coprocessors, and to show significant performance improvements compared to existing state-of-the-art implementations. Therefore, in addition to the new optimization strategies, analysis, and optimal performance results, we finally present the significance of using these routines/strategies to accel
27#
發(fā)表于 2025-3-26 08:22:39 | 只看該作者
Dtree: Dynamic Task Scheduling at Petascale,an essential and expensive step in quantum chemistry codes. For ParaBLe, we show improved performance while eliminating the complexity of managing heterogeneity. For GTFock, we match the most recently published performance without using any application-specific optimizations for data access patterns
28#
發(fā)表于 2025-3-26 11:09:26 | 只看該作者
29#
發(fā)表于 2025-3-26 16:14:57 | 只看該作者
30#
發(fā)表于 2025-3-26 18:37:19 | 只看該作者
Lattice-CSC: Optimizing and Building an Efficient Supercomputer for Lattice-QCD and to Achieve Firsrior power efficiency. The November?2014 Green500 list awarded L-CSC the most power-efficient supercomputer in the world with?5270?MFLOPS/W in the Linpack benchmark. This paper presents optimizations to our Linpack implementation HPL-GPU and other power efficiency improvements which helped L-CSC rea
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