iPLAR: Towards Interactive Programming with Parallel Linear Algebra in R-Reference-Cited by-同舟云学术

iPLAR: Towards Interactive Programming with Parallel Linear Algebra in R

Published:2015 Issue: Volume: Page:104-117
ISSN:0302-9743
Container-title:Algorithms and Architectures for Parallel Processing
language:
Short-container-title:

Author:

Wang Zhaokang,Fan Shiqing,Gu Rong,Yuan Chunfeng,Huang Yihua

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-27140-8_8

Reference17 articles.

1. Adler, D., Glser, C., Nenadic, O., Oehlschlgel, J., Zucchini, W.: ff: memory-efficient storage of large data on disk and fast access functions (2014). https://cran.r-project.org/web/packages/ff/

2. Casanova, H., Dongarra, J.: Netsolve: a network-enabled server for solving computational science problems. Int. J. High Perform. Comput. Appl. 11(3), 212–223 (1997)

3. Choy, R., Edelman, A.: Parallel matlab: Doing it right. Proc. IEEE 93(2), 331–341 (2005)

4. Das, S., Sismanis, Y., Beyer, K.S., Gemulla, R., Haas, P.J., McPherson, J.: Ricardo: Integrating R and hadoop. In: Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data SIGMOD 2010, pp. 987–998. ACM, New York (2010)

5. Edelman, A.: The star-P high performance computing platform. In: 2007 IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP 2007, vol. 4, pp. IV-1197–IV-1200. IEEE Press, New York (2007)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Introducing a New Client/Server Framework for Big Data Analytics with the R Language;Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale;2016-07-17