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UID:submissions.supercomputing.org_SC23_sess303_rpost211@linklings.com
SUMMARY:Why Wait!?  Hades:  An Active, Content-Aware System for Precalcula
 ting Derived Quantities
DESCRIPTION:Jaime Cernuda, Luke Logan, Anthony Kougkas, and Xian-He Sum (I
 llinois Institute of Technology)\n\nModern scientific applications produce
  vast amounts of data, typically stored in monolithic files on parallel fi
 le systems (PFS). Analyzing these large files often results in inefficienc
 y due to I/O stalls. To mitigate these stalls, certain data can be pre-com
 puted during the production phase and queried during analysis. However, th
 is solution demands added storage capacity and an astute use of storage hi
 erarchies. In this context, we introduce Hades, an I/O engine seamlessly i
 ntegrated with the Adios2 framework. Hades offers hierarchical buffering, 
 which enables smart data placement and prefetching across the spectrum of 
 I/O devices. Additionally, it is adept at computing basic derived quantiti
 es required by I/O applications, such as the global and local min/max valu
 es. A notable feature of Hades is its memory-first metadata management str
 ategy, which is designed for querying derived data, significantly enhancin
 g system performance.\n\nTag: Artificial Intelligence/Machine Learning, Ar
 chitecture and Networks, Heterogeneous Computing, I/O and File Systems, Pe
 rformance Measurement, Modeling, and Tools, Post-Moore Computing, Programm
 ing Frameworks and System Software, Quantum Computing\n\nRegistration Cate
 gory: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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