In Situ Indexing and Query Processing of AMR Data

Technical Report · Fri Aug 31 04:00:00 EDT 2018

DOI:https://doi.org/10.2172/1502394· OSTI ID:1502394

Samatova, Nagiza Faridovna ^[1]

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1. North Carolina State Univ., Raleigh, NC (United States); North Carolina State University

We have developed the first, holistic, Adaptive Mesh Refinement (AMR) capable, in situ query framework to ensure the tractability of the current- and next-generation AMR simulation analysis on the path to extreme scale. We have addressed key issues pertaining to in situ analysis, memory hierarchy, generalized parallel indexing, index-compression, and real-time access pattern detection. We have published the following research papers in high profile peer reviewed computer science conferences: (a) Parallel In Situ Detection of Connected Components in Adaptive Mesh Refinement Data; (b) AMR-aware In Situ Indexing and Scalable Querying; (c) Pattern-driven dynamic data layout optimization; (d) In situ Storage Layout Optimization for AMR Spatio-temporal Read Accesses; (e) AMRZone: A Runtime AMR Data Sharing Framework for Scientific Applications; (f) Exploring Memory Hierarchy and Network Topology for Runtime AMR Data Sharing Across Scientific Applications.

• Research Organization: North Carolina State Univ., Raleigh, NC (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
• DOE Contract Number: SC0012389
• OSTI ID: 1502394
• Report Number(s): Final-report:-DOE:-NCSU:-DE--SC0012389
• Country of Publication: United States
• Language: English

Related Subjects

96 KNOWLEDGE MANAGEMENT AND PRESERVATION
97 MATHEMATICS AND COMPUTING
AMR data management
In situ indexing
data layout optimization
query processing