Swift (parallel scripting language)
| Paradigms | Dataflow, distributed, grid, concurrent, scientific workflow, scripting |
|---|---|
| Developers | University of Chicago, Argonne National Laboratory |
| First appeared | 2007; 18 years ago (2007) |
| Stable release | 0.96.2
/ August 5, 2015; 9 years ago (2015年08月05日) |
| Typing discipline | Strong |
| Platform | Cross-platform: Java |
| OS | Cross-platform: Java |
| License | Apache 2.0 |
| Website | swift-lang |
| Influenced by | |
| C syntax, functional programming | |
| Influenced | |
| Cuneiform | |
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Swift[1] is an implicitly parallel programming language that allows writing scripts that distribute program execution across distributed computing resources,[2] including clusters, clouds, grids, and supercomputers. Swift implementations are open-source software under the Apache License, version 2.0.
Language features
[edit ]A Swift script[3] describes strongly typed data, application components, invocations of applications components, and the interrelations in the dataflow between those invocations. The program statements will automatically run in parallel unless there is a data dependency between them, given sufficient computing resources. The design of the language guarantees that results of a computation are deterministic, even though the order in which statements executes may vary. A special file data type is built into Swift. It allows command-line programs to be integrated into a program as typed functions. This allows programmers to write programs that treat command-line programs and files in the same way as regular functions and variables. A concept of mapping [4] is used to store and exchange complex data structures using a file system structure with files and directories.
Rapid dispatch of parallel tasks to a wide range of resources is implemented through a mechanism called Coasters task dispatch.[5] A Message Passing Interface based implementation of the language[6] supports very high task execution rates (e.g., 3000 tasks per second)[7] on large clusters and supercomputers.
Area of applications
[edit ]- Energy modelling
- Climate modelling
- Economic modelling
- Biochemical protein modelling
- Magnetic resonance imaging (MRI) analysis in neuroscience
- Glass structure modelling
See also
[edit ]References
[edit ]- ^ "Swift Home Page". swift-lang.org. Retrieved 2014年06月02日.
- ^ Wilde, Michael; Hategan, Mihael; Wozniak, Justin M.; Clifford, Ben; Katz, Daniel S.; Foster, Ian (2011). "Swift: A language for distributed parallel scripting" (PDF). Parallel Computing. 37 (9): 633–652. CiteSeerX 10.1.1.658.8990 . doi:10.1016/j.parco.201105005. Archived from the original (PDF) on 2014年06月06日.
- ^ Reference manual, chapter 2
- ^ Reference manual, chapter 3
- ^ Hategan, Mihael; Wozniak, Justin; Maheshwari, Ketan (2011). "Coasters: uniform resource provisioning and access for scientific computing on clouds and grids" (PDF). Proceedings Utility and Cloud Computing.
- ^ Wozniak, Justin M., Timothy G. Armstrong, Michael Wilde, Daniel S. Katz, Ewing Lusk, and Ian T. Foster. "Swift/T: Large-scale Application Composition via Distributed-memory Dataflow Processing." In Cluster, Cloud and Grid Computing (CCGrid), 2013 13th IEEE/ACM International Symposium on, pp. 95-102. IEEE, 2013
- ^ a b Wilde, Michael; Foster, Ian; Iskra, Kamil; Beckman, Pete; Zhang, Zhao; Espinosa, Allan; Hategan, Mihael; Clifford, Ben; Raicu, Ioan (2009). "Parallel Scripting for Applications at the Petascale and Beyond" (PDF). Computer. 42 (11): 50–60. doi:10.1109/mc.2009.365. S2CID 5271623. Archived from the original (PDF) on 2014年07月12日.
- ^ Case studies on the official site