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Performance evaluation and analysis of sparse matrix and graph kernels on heterogeneous processors
2019
CCF Transactions on High Performance Computing
We in this work evaluate and analyze eight sparse matrix and graph kernels on an AMD CPU-GPU heterogeneous processor by using 956 sparse matrices. ...
We finally discuss several challenges and opportunities for achieving higher performance for sparse matrix and graphs kernels on heterogeneous processors. ...
Acknowledgements This work has been partly supported by the National Natural Science Foundation of China (Grant nos. 61732014, 61802412, 61671151), Beijing Natural Science Foundation (no. 4172031), and ...
doi:10.1007/s42514-019-00008-6
fatcat:t3nfa446lbb6pb4azkfjowhijm
GPGPU-based Gaussian Filtering for Surface Metrological Data Processing
2008
2008 12th International Conference Information Visualisation
Thirdly, this thesis devised methods for carrying out result visualization directly on GPU by storing processed data in local GPU memory through making use of GPU's rendering device features to achieve ...
of stream processing pattern represented by the compute unified device architecture (CUDA) in which GPU is considered as iii not only a graphics device but a streaming coprocessor of CPU. ...
Similar to CUDA, OpenCL also employed the concepts of "host programs" and "kernels". ...
doi:10.1109/iv.2008.14
dblp:conf/iv/SuXJ08
fatcat:lpagxjxstjbj5lcdumztlpgolu
2015 Jahresbericht Annual Report
unpublished
Martin Rinard for his support and contribution to the organization of the seminar. We thank Sara Achour for her help with preparing the full report. ...
We would like to thank Dagmar Glaser and the staff at Schloss Dagstuhl for their continuous support and great hospitality which was the basis for the success of this seminar.
Acknowledgements. ...
What options of mapping stencil codes to a heterogeneous execution platform exist and how can an educated choice be made? ...
fatcat:tzkatxrngzbj7j3qvr7j7znvla