Performance And Scalability Of Materials Science And Machine Learning Codes On The State-Of-Art Hybrid Supercomputer Architecture

SUPERCOMPUTING (RUSCDAYS 2019)(2019)

引用 10|浏览42
暂无评分
摘要
8 of top 10 supercomputers of Top500 list published in November 2018 consist of computing nodes with hybrid architectures that require special programming techniques. 5 systems among these are based on Nvidia GPUs. In this paper, we consider the benchmark results of the brand new hybrid supercomputer installed in March 2019 in NRU HSE. This system gives us the possibility to estimate the performance of several widely used material science and machine learning codes that we discuss in this work within the framework of the results available for older HPC systems.
更多
查看译文
关键词
MPI latency, MPI bandwidth, Gromacs, CP2K, VASP, Machine learning
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