Authors
Jialin Liu, Quincey Koziol, Gregory F Butler, Neil Fortner, Mohamad Chaarawi, Houjun Tang, Suren Byna, Glenn K Lockwood, Ravi Cheema, Kristy A Kallback-Rose, Damian Hazen, Mr Prabhat
Publication date
2018/11/12
Conference
2018 IEEE/ACM 3rd International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems (PDSW-DISCS)
Pages
24-34
Publisher
IEEE
Description
POSIX-based parallel file systems provide strong consistency semantics, which many modern HPC applications do not need and do not want. Object store technologies avoid POSIX consistency and are designed to be extremely scalable, for use in cloud computing and similar commercial environments. In this work, we evaluate three object store systems: Intel DAOS, Ceph RADOS, and Openstack Swift, and evaluate them with three HPC applications: VPIC, H5Boss, and BDCATS. We have developed virtual object layer (VOL) plugins for HDF5 that can redirect the applications' HDF5 calls to the underlying object storage systems' APIs, with minimum application code change. Through our evaluation, we found that object stores have better scalability in many cases than POSIX file systems, but are not optimized for common HPC use cases, such as collective I/O. Understanding current object store I/O details and …
Total citations
201920202021202220232024351373
Scholar articles
J Liu, Q Koziol, GF Butler, N Fortner, M Chaarawi… - 2018 IEEE/ACM 3rd International Workshop on Parallel …, 2018