Ensuring performance of applications running on large-scale clusters is one of the primary focuses in HPC research. In this talk, we will show our strategies for performance analysis and optimization of applications in various fields of research using large-scale HPC clusters. Our strategies are designed to comprehensively analyze runtime features of applications, parallelisation strategies of physical models, algorithmic implementations, and other technical details. These three levels of strategy cover platform optimization, technological innovation, and model innovation, and targeted optimization based on these features. State-of-the-art CPU instructions, network communication patterns, and innovative parallel strategies have been optimized for various applications.
About the presenter
Dr. Liu is the Head of the HPC Application Support Team at Inspur. Since joining Inspur, he and his team have engaged primarily in the optimization and acceleration of large-scale scientific computing applications in the fields of meteorology, oceanography, climatology, physics, life sciences and chemistry. At Inspur, he has designed and developed the in-house software package “Teye” for monitoring and analyzing characteristics of HPC applications. In addition, he has refined and deepened the Inspur HPC application characterstics analysis method and also extracted a methodology for profiling computational science applications from perspectives of theory and algorithm. He and his team have been involved in the design and optimization of the core codes and algorithms for a number of research projects in to multi-disciplinary computational science. Dr. Liu received his PhD in Condensed Matter Physics at the Chinese Academy of Sciences in 2011.