Exascale I/O initiatives will require new and fully integrated I/O models which are capable of providing straightforward functionality, fault tolerance and efficiency. One solution is the Distributed Asynchronous Object Storage (DAOS) technology, which is primarily designed to handle the next generation NVRAM and NVMe technologies envisioned for providing a high bandwidth/IOPS storage tier close to the compute nodes in an HPC system. In conjunction with DAOS, the HDF5 library, an I/O library for scientific applications, will support end-to-end data integrity, fault tolerance, object mapping, index building and querying. This paper details the implementation and performance of the HDF5 library built over DAOS by using three representative scientific application codes.
@article{arxiv.1712.00423,
title = {DAOS for Extreme-scale Systems in Scientific Applications},
author = {M. Scot Breitenfeld and Neil Fortner and Jordan Henderson and Jerome Soumagne and Mohamad Chaarawi and Johann Lombardi and Quincey Koziol},
journal= {arXiv preprint arXiv:1712.00423},
year = {2017}
}
Comments
Submitted to HiPC-2017 on Jun 30 2017, accepted for publication on Sep 8 2017, withdrawn on Oct 20 2017 b/c no author was able to present