Network Optimization for Distributed Memory File System on High Performance Computers

DOI

10.2991/eeeis-16.2017.93How to use a DOI?

Keywords

high-performance computing; distributed file system; memory; RDMA; network optimization.

Abstract

On high performance computers, each compute node's demand for memory may be different. Building a distributed file system in idle memory can improve the memory utilization of the whole system. When memory takes place of disk, the Socket-based communication becomes the main bottleneck. As most of current high performance computers support RDMA, RBP (RDMA Buffer Pool) was referred to optimize the network performance of such an in-memory file system. MooseFS was adopted by RBP and deployed in TH-1A supercomputer. The experiment results showed that the RBP-based method could improve the speed of clients and the aggregate bandwidth of servers for sequential read and write significantly. For a single client, it increased the speeds of sequential read and write by a factor of 2.0~2.6. For a single server, it increased the collective bandwidths of sequential read and write by a factor of 2.0~2.4.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Chun-Jia Wu
AU  - Guang-Ming Liu
AU  - Xin Liu
PY  - 2016/12
DA  - 2016/12
TI  - Network Optimization for Distributed Memory File System on High Performance Computers
BT  - Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
PB  - Atlantis Press
SP  - 758
EP  - 763
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-16.2017.93
DO  - 10.2991/eeeis-16.2017.93
ID  - Wu2016/12
ER  -