Exploration of Supervised Machine Learning Techniques for Runtime Selection of CPU vs. GPU Execution in Java Programs

Author:

Kim Gloria Y. K.ORCID,Hayashi AkihiroORCID,Sarkar Vivek

Publisher

Springer International Publishing

Reference31 articles.

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2. Dubach, C., Cheng, P., Rabbah, R., Bacon, D.F., Fink, S.J.: Compiling a high-level language for gpus: (via language support for architectures and compilers). In: Proceedings of the 33rd ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2012, pp. 1–12. ACM, New York (2012). http://doi.acm.org/10.1145/2254064.2254066

3. Fumero, J.J., Remmelg, T., Steuwer, M., Dubach, C.: Runtime code generation and data management for heterogeneous computing in Java. In: Proceedings of the Principles and Practices of Programming on the Java Platform, PPPJ 2015, pp. 16–26. ACM, New York (2015). http://doi.acm.org/10.1145/2807426.2807428

4. Fumero, J.J., Steuwer, M., Dubach, C.: A composable array function interface for heterogeneous computing in Java. In: Proceedings of ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming, ARRAY 2014, pp. 44:44–44:49. ACM, New York (2014). http://doi.acm.org/10.1145/2627373.2627381

5. Grcevski, N., Kielstra, A., Stoodley, K., Stoodley, M., Sundaresan, V.: JavaTM just-in-time compiler and virtual machine improvements for server and middleware applications. In: Proceedings of the 3rd Conference on Virtual Machine Research And Technology Symposium, VM 2004, vol. 3. p. 12. USENIX Association, Berkeley (2004). http://dl.acm.org/citation.cfm?id=1267242.1267254

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