Guojing Cong, David A. Bader
Journal of Parallel and Distributed Computing
To fully utilize the power of current high performance computing systems, high productivity to the end user is critical. It is a challenge to map an application to the target architecture efficiently. Tuning an application for high performance remains a daunting task, and frequently involves manual changes to the program. Recently refactoring techniques are proposed to rewrite or reorganize programs for various software engineering purposes. In our research we explore combining performance analysis with refactoring techniques for automated tuning that we expect to greatly improve the productivity of application deployment. We seek to build a system that can apply appropriate refactoring according to the bottleneck discovered. We demonstrate the effectiveness of this approach through the tuning of several scientific applications and kernels. © 2010 IEEE.
Guojing Cong, David A. Bader
Journal of Parallel and Distributed Computing
Ming Hung Chen, Jyun-Yan Ciou, et al.
HPC Asia 2018
Guojing Cong, Konstantin Makarychev
IPDPS 2011
Fan Zhou, Guojing Cong
IJCAI 2018