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DTSTAMP:20210916T132450Z
LOCATION:Mère Royaume
DTSTART;TZID=Europe/Stockholm:20210706T150000
DTEND;TZID=Europe/Stockholm:20210706T153000
UID:submissions.pasc-conference.org_PASC21_sess137_msa147@linklings.com
SUMMARY:Automatic and Transparent Scientific Data Management with Object A
 bstractions
DESCRIPTION:Minisymposium\n\nAutomatic and Transparent Scientific Data Man
 agement with Object Abstractions\n\nByna, Koziol, Tang\n\nThree trends are
  dominating scientific data management: (1) large volumes of data (2) mass
 ive concurrency of supercomputers, and (3) deepening hierarchy of heteroge
 neous memory and storage devices. For decades, storage systems have perfor
 med I/O with file-oriented approaches based on the POSIX and MPI-IO standa
 rds. However, these standards present fundamental challenges in the areas 
 of scalable data and metadata operations, asynchronous operations, and sup
 port for “eventual” consistency of distributed operations. To 
 overcome these challenges, we have developed a new object-centric abstract
 ion for efficient scientific data management, called Proactive Data Contai
 ners (PDC). The PDC runtime system provides a set of services that make in
 telligent data placement decisions in the memory and storage hierarchy and
  provide scalable metadata operations. PDC supports existing middleware I/
 O APIs, such as HDF5, and also provides a native, object-centric API for c
 apturing the intent of application I/O. The capabilities provided by the P
 DC API and its data movement operations have been tested with data from a 
 dark energy probe and simulations from plasma physics and cosmology. PDC&r
 squo;s metadata management performance is ~40X faster than that of the Lus
 tre file system and its data I/O is 5X - 30X faster than traditional POSIX
 -based I/O libraries, i.e., MPI-IO.\n\nDomain: CS and Math
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