Swift (parallel scripting language)

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.

Swift
ParadigmsDataflow, distributed, grid, concurrent, scientific workflow, scripting
DevelopersUniversity of Chicago,
Argonne National Laboratory
First appeared2007 (2007)
Stable release
0.96.2 / August 5, 2015 (2015-08-05)
Typing disciplineStrong
PlatformCross-platform: Java
OSCross-platform: Java
LicenseApache 2.0
Websiteswift-lang.org
Influenced by
C syntax, functional programming

Language features

A Swift script[3] describes strongly typed data, application components, invocations of applications components, and the inter-relations 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

Application examples:[7][8]

  • Energy modelling
  • Climate modelling
  • Economic modelling
  • Biochemical protein modelling
  • Magnetic resonance imaging (MRI) analysis in neuroscience
  • Glass structure modelling

See also

References
  1. "Swift Home Page". swift-lang.org. Retrieved 2014-06-02.
  2. 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.2011.05.005. Archived from the original (PDF) on 2014-06-06.
  3. Reference manual, chapter 2
  4. Reference manual, chapter 3
  5. 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.
  6. 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
  7. 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. Archived from the original (PDF) on 2014-07-12.
  8. Case studies on the official site
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