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ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management
- Source :
- SoftwareX, Vol 12, Iss, Pp 100561-(2020)
- Publication Year :
- 2020
- Publisher :
- Elsevier, 2020.
-
Abstract
- Author(s): Godoy, WF; Podhorszki, N; Wang, R; Atkins, C; Eisenhauer, G; Gu, J; Davis, P; Choi, J; Germaschewski, K; Huck, K; Huebl, A; Kim, M; Kress, J; Kurc, T; Liu, Q; Logan, J; Mehta, K; Ostrouchov, G; Parashar, M; Poeschel, F; Pugmire, D; Suchyta, E; Takahashi, K; Thompson, N; Tsutsumi, S; Wan, L; Wolf, M; Wu, K; Klasky, S | Abstract: We present ADIOS 2, the latest version of the Adaptable Input Output (I/O) System. ADIOS 2 addresses scientific data management needs ranging from scalable I/O in supercomputers, to data analysis in personal computer and cloud systems. Version 2 introduces a unified application programming interface (API) that enables seamless data movement through files, wide-area-networks, and direct memory access, as well as high-level APIs for data analysis. The internal architecture provides a set of reusable and extendable components for managing data presentation and transport mechanisms for new applications. ADIOS 2 bindings are available in C++11, C, Fortran, Python, and Matlab and are currently used across different scientific communities. ADIOS 2 provides a communal framework to tackle data management challenges as we approach the exascale era of supercomputing.
- Subjects :
- Staging
Computer science
Fortran
Data management
Scalable I/O
computer.software_genre
01 natural sciences
Data science
03 medical and health sciences
Exascale computing
Luster GPFS file systems
0103 physical sciences
010306 general physics
MATLAB
030304 developmental biology
computer.programming_language
lcsh:Computer software
0303 health sciences
Application programming interface
business.industry
Programming language
In-situ
Python (programming language)
Supercomputer
Computer Science Applications
lcsh:QA76.75-76.765
Personal computer
RDMA
business
High-performance computing (HPC)
computer
Software
Subjects
Details
- Language :
- English
- ISSN :
- 23527110
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- SoftwareX
- Accession number :
- edsair.doi.dedup.....03d66b05c664daf066d0e00bc89f8916