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UID:submissions.supercomputing.org_SC24_sess417_tut143@linklings.com
SUMMARY:High-Performance Object Storage: I/O for the Exascale Era
DESCRIPTION:Adrian Jackson (University of Edinburgh, Scotland; EPCC, The U
 niversity of Edinburgh); Mohamad Chaarawi (Intel Corporation); Johann Lomb
 ardi (Independent); Nicolau Manubens (European Centre for Medium-Range Wea
 ther Forecasts (ECMWF)); and Dean Hildebrand (Google)\n\nRecently we have 
 seen a change in the diversity of applications utilizing high-performance 
 computing (HPC) from primarily computational simulation approaches, to a m
 ore varied application mix including machine learning and data analytics. 
 With this diversification in workloads, there has also been a diversificat
 ion in I/O patterns; the movements in, and requirements on, data storage a
 nd access. Data storage technologies in HPC have long been optimized for l
 arge scale bulk operations focused on high-bandwidth with relatively low v
 olumes of metadata operations. However, many applications now exhibit non-
 optimal I/O patterns for large scale parallel filesystems, with large amou
 nts of small I/O operations, non-contiguous data access, and increases in 
 read as well as write I/O loads.\nParallel filesystems, such as Lustre and
  Storage Scale, have been optimized and extended to provided higher metada
 ta performance and to better handle small I/O operations. However, the und
 erlying approach of POSIX-like I/O, with block-sized read and write operat
 ions, and file-level data storage, set limitations on the overall performa
 nce and functionality that such approaches can achieve. This tutorial will
  educate attendees in the design and usage of object stores, as alternativ
 es to filesystems, using Ceph and DAOS as examples, through hands-on exerc
 ise and lecture sessions.\n\nTag: Architecture, Emerging Technologies, I/O
 , Storage, Archive, Scalable Data Mining\n\nRegistration Category: Tutoria
 l Reg Pass\n\n
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