article · IEEE Conference Anthology · 2013
A visualization method of performance data for large scale parallel application based on clustering of function characteristics
Yunchun Li, Yun Li, Jinlei Wang
Cited by 0Abstract and details only
Abstract
Obtaining performance data of parallel program and analyzing these data are the two basic steps for analysis of parallel program behavior and optimizing program design. With the rapid development of high-performance computers, unceasing expansion of the scale of parallel program, it will produce large scale performance data for each measurement. The problems that how to deal with and demonstrate these data to developers and how to assist the developers to find problems are more difficulty. Towards the profile performance data, this paper provides a visualization method based on clustering of function characteristics, which combines the function grouping with clustering of k-value optimization to process large scale performance data, so as to provide performance analysis support for developers.
Cite this paper
Li, Y., Li, Y., & Wang, J. (2013). A visualization method of performance data for large scale parallel application based on clustering of function characteristics. IEEE Conference Anthology, 1–5. https://doi.org/10.1109/anthology.2013.6784737
Li, Yunchun, et al. “A visualization method of performance data for large scale parallel application based on clustering of function characteristics.” IEEE Conference Anthology, 2013, pp. 1–5, https://doi.org/10.1109/anthology.2013.6784737.
Li, Yunchun, Yun Li, and Jinlei Wang. 2013. “A visualization method of performance data for large scale parallel application based on clustering of function characteristics.” IEEE Conference Anthology: 1–5. https://doi.org/10.1109/anthology.2013.6784737.
Li, Y., Li, Y. and Wang, J. (2013) ‘A visualization method of performance data for large scale parallel application based on clustering of function characteristics’, IEEE Conference Anthology, pp. 1–5. Available at: https://doi.org/10.1109/anthology.2013.6784737.
@article{li2013visualization,
title = {{A visualization method of performance data for large scale parallel application based on clustering of function characteristics}},
author = {Li, Yunchun and Li, Yun and Wang, Jinlei},
journal = {IEEE Conference Anthology},
pages = {1--5},
year = {2013},
doi = {10.1109/anthology.2013.6784737}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.
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