A multi-aspect online tuning framework for HPC applications

Software Quality Journal(2017)

引用 6|浏览82
暂无评分
摘要
Developing software applications for high-performance computing (HPC) requires careful optimizations targeting a myriad of increasingly complex, highly interrelated software, hardware and system components. The demands placed on minimizing energy consumption on extreme-scale HPC systems and the associated shift towards hete rogeneous architectures add yet another level of complexity to program development and optimization. As a result, the software optimization process is often seen as daunting, cumbersome and time-consuming by software developers wishing to fully exploit HPC resources. To address these challenges, we have developed the Periscope Tuning Framework (PTF), an online automatic integrated tuning framework that combines both performance analysis and performance tuning with respect to the myriad of tuning parameters available to today’s software developer on modern HPC systems. This work introduces the architecture, tuning model and main infrastructure components of PTF as well as the main tuning plugins of PTF and their evaluation.
更多
查看译文
关键词
Automatic performance tuning,High-performance computing,Performance optimization,Parallel architectures,Energy tuning,OpenCL
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要