Title :
Decoupled I/O for Data-Intensive High Performance Computing
Author :
Chao Chen ; Yong Chen ; Kun Feng ; Yanlong Yin ; Eslami, Hassan ; Thakur, Rajeev ; Xian-He Sun ; Gropp, William D.
Author_Institution :
Dept. of Comput. Sci., Texas Tech Univ., Lubbock, TX, USA
Abstract :
The I/O bottleneck issue has been acknowledged as one of main performance issues of high performance computing (HPC) systems for data-intensive scientific applications, and has attracted intensive studies in recent years. With the enlarging gap between the computing bandwidth and I/O bandwidth in projected next-generation HPC systems, this issue will become even worse. In this paper, we present a novel decoupled I/O to address the fundamental I/O bottleneck issue. The decoupled I/O is a software stack including MPI extensions, compiler improvements, and runtime library support, based one decoupled HPC system architecture. It allows users to treat the computing of data-intensive operations and the traditional I/O operation as an ensemble and offload them into dedicated data nodes, which are near to the data source, to reduce the overhead of data movement and improve the I/O bandwidth usage. The decoupled I/O is user-friendly and requires little changes in application codes. Experiments were conducted to evaluate the performance of the decoupled I/O, and the results show that it outperforms existing solutions (such as active storage I/O) and provides an attractive I/O solution for data-intensive high performance computing.
Keywords :
input-output programs; parallel processing; HPC system; MPI extension; compiler improvement; computing bandwidth; data-intensive high performance computing; data-intensive scientific application; decoupled input-output bottleneck; input-output bandwidth; message passing interface; runtime library support; software stack; Bandwidth; Computational modeling; Computer architecture; Data processing; High performance computing; Libraries; Runtime; Decoupled I/O; data-intensive computing; high performance computing; parallel I/O; storage;
Conference_Titel :
Parallel Processing Workshops (ICCPW), 2014 43rd International Conference on
DOI :
10.1109/ICPPW.2014.48