Yi Yang

Gupta, S., Xiang, P., Yang, Y., & Zhou, H. (2013). Locality principle revisited: A probability-based quantitative approach. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 73(7), 1011–1027. https://doi.org/10.1016/j.jpdc.2013.01.010

Yang, Y., & Zhou, H. (2013). The Implementation of a High Performance GPGPU Compiler. INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING, 41(6), 768–781. https://doi.org/10.1007/s10766-012-0228-3

Yang, Y., Xiang, P., Kong, J., Mantor, M., & Zhou, H. (2012). A Unified Optimizing Compiler Framework for Different GPGPU Architectures. ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION, 9(2). https://doi.org/10.1145/2207222.2207225

Yang, Y., Xiang, P., Mantor, M., & Zhou, H. Y. (2012). CPU-assisted GPGPU on fused CPU-GPU architectures. International symposium on high-performance computer, 103–114.

Gupta, S., Xiang, P., Yang, Y., & Huiyang. (2012). Locality principle revisited: A probability-based quantitative approach. 2012 ieee 26th international parallel and distributed processing symposium (ipdps), 995–1009. https://doi.org/10.1109/ipdps.2012.93

Yang, Y., Xiang, P., Kong, J., & Zhou, H. (2010, May). An Optimizing Compiler for GPGPU Programs with Input-Data Sharing. ACM SIGPLAN NOTICES, Vol. 45, pp. 343–344. https://doi.org/10.1145/1837853.1693505

Yang, Y., Xiang, P., Kong, J., & Zhou, H. (2010). An Optimizing Compiler for GPGPU Programs with Input-Data Sharing. PPOPP 2010: PROCEEDINGS OF THE 2010 ACM SIGPLAN SYMPOSIUM ON PRINCIPLES AND PRACTICE OF PARALLEL PROGRAMMING, pp. 343–344. https://doi.org/10.1145/1693453.1693505