Swift (parallel scripting language)
|Paradigms||Dataflow, distributed, grid, concurrent, scientific workflow, scripting|
|Developers||University of Chicago,|
Argonne National Laboratory
0.96.2 / August 5, 2015
|C syntax, functional programming|
Swift is an implicitly parallel programming language that allows writing scripts that distribute program execution across distributed computing resources, including clusters, clouds, grids, and supercomputers. Swift implementations are open-source software under the Apache License, version 2.0.
A Swift script 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 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. A Message Passing Interface based implementation of the language supports very high task execution rates (e.g., 3000 tasks per second) on large clusters and supercomputers.
Area of applications
- Climate modelling
- Economic modelling
- Biochemical protein modelling
- Magnetic resonance imaging (MRI) analysis in neuroscience
- "Swift Home Page". swift-lang.org. Retrieved 2014-06-02.
- 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. doi:10.1016/j.parco.2011.05.005. Archived from the original (PDF) on 2014-06-06.
- 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
- 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.
- Case studies on the official site