1. Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., Kudlur, M., Levenberg, J., Monga, R., Moore, S., Murray, D. G., Steiner, B., Tucker, P., Vasudevan, V., Warden, P., Wicke, M., Yu, Y., and Zheng, X. Tensorflow: A system for large-scale machine learning. In 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16) (Savannah, GA, Nov. 2016), USENIX Association, pp. 265--283.
2. Babakol, T., Canino, A., and Liu, Y. D. Eflect: Porting energy-aware applications to shared environments. ICSE '22, Association for Computing Machinery, p. 823--834.
3. Babakol, T., Canino, A., Mahmoud, K., Saxena, R., and Liu, Y. D. Calm energy accounting for multi-threaded java applications. FSE '20.
4. Banerjee, A., Chong, L. K., Chattopadhyay, S., and Roychoudhury, A. Detecting energy bugs and hotspots in mobile apps. In Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (2014), FSE 2014, p. 588--598.
5. Green Streams for data-intensive software