poster

Swift/T: scalable data flow programming for many-task applications

Authors:

Justin M. Wozniak,

Timothy G. Armstrong,

Michael Wilde,

Daniel S. Katz,

Ewing Lusk,

Ian T. FosterAuthors Info & Claims

PPoPP '13: Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming

Pages 309 - 310

https://doi.org/10.1145/2442516.2442559

Published: 23 February 2013 Publication History

Get Access

Abstract

Swift/T, a novel programming language implementation for highly scalable data flow programs, is presented.

References

[1]

R. L. Bocchino, Jr., V. S. Adve, S. V. Adve, M. Snir. Parallel programming must be deterministic by default. In Workshop Hot Topics in Parallelism: HotPar'09.

Digital Library

Google Scholar

[2]

J. T. Feo, D. C. Cann, R. R. Oldehoeft. A report on the Sisal language project. J. Parallel and Distributed Computing, 1990.

Digital Library

Google Scholar

[3]

M. Hategan, J. Wozniak, K. Maheshwari. Coasters: uniform resource provisioning and access for scientific computing on clouds and grids. In Proc. Utility and Cloud Computing.

Digital Library

Google Scholar

[4]

E. L. Lusk, S. C. Pieper, R. M. Butler. More scalability, less pain: A simple programming model and its implementation for extreme computing. SciDAC Review, 2010.

Google Scholar

[5]

K. R. Traub. A compiler for the MIT tagged-token dataflow architecture. Tech. rep., Massachusetts Institute of Technology, 1986.

Digital Library

Google Scholar

[6]

M. Wilde, M. Hategan, J. M. Wozniak, B. Clifford, D. S. Katz, I. Foster. Swift: A language for distributed parallel scripting. Par. Comp., 2011.

Digital Library

Google Scholar

[7]

J. M. Wozniak, T. G. Armstrong, E. L. Lusk, D. S. Katz, M. Wilde, I. T. Foster. Turbine: A distributed memory data flow engine for many-task applications. In Int'l Workshop Scalable Workflow Enactment Engines and Technologies (SWEET) 2012.

Digital Library

Google Scholar

Cited By

View all

Puckelwartz MPesce LHernandez EWebster GDellefave-Castillo LRussell MGeisler SKearns SKarthik FEtheridge SMonroe TPottinger TKannankeril PShoemaker MFountain DRoden DFaulkner MMacLeod HBurns KYandell MTristani-Firouzi MGeorge AMcNally E(2024)The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the youngGenome Medicine10.1186/s13073-024-01284-w16:1Online publication date: 16-Jan-2024
https://doi.org/10.1186/s13073-024-01284-w
Wozniak JLiu ZVescovi RChard RNicolae BFoster I(2022)Braid-DB: Toward AI-Driven Science with Machine Learning ProvenanceDriving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation10.1007/978-3-030-96498-6_14(247-261)Online publication date: 10-Mar-2022
https://doi.org/10.1007/978-3-030-96498-6_14
Nookala PDinda PHale KChard KRaicu I(2021)Enabling Extremely Fine-grained Parallelism via Scalable Concurrent Queues on Modern Many-core Architectures2021 29th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)10.1109/MASCOTS53633.2021.9614292(1-8)Online publication date: 3-Nov-2021
https://doi.org/10.1109/MASCOTS53633.2021.9614292
Show More Cited By

Index Terms

Swift/T: scalable data flow programming for many-task applications
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types
        Concurrent programming languages
        Data flow languages
        Distributed programming languages
        Parallel programming languages

Recommendations

How swift developers handle errors
MSR '18: Proceedings of the 15th International Conference on Mining Software Repositories

Swift is a new programming language developed by Apple as a replacement to Objective-C. It features a sophisticated error handling (EH) mechanism that provides the kind of separation of concerns afforded by exception handling mechanisms in other ...
A Swift Introduction to Swift App Development (Abstract Only)
SIGCSE '15: Proceedings of the 46th ACM Technical Symposium on Computer Science Education

Swift is a new programming language recently introduced by Apple as a replacement for Objective-C. Considering that Objective-C ranks third on the Tiobe Index and is the progenitor of virtually all the 1.2 million apps in the App Store, Swift is likely ...
Swift/T: scalable data flow programming for many-task applications
PPoPP '13

Swift/T, a novel programming language implementation for highly scalable data flow programs, is presented.

Comments

Information & Contributors

Information

Published In

PPoPP '13: Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming

February 2013

332 pages

ISBN:9781450319225

DOI:10.1145/2442516

General Chairs:
Alex Nicolau
University of California, Irvine, USA
,
Xiaowei Shen
IBM Research, China
,
Program Chairs:
Saman Amarasinghe
Massachusetts Institute of Technology, USA
,
Richard Vuduc
Georgia Institute of Technology, USA

ACM SIGPLAN Notices Volume 48, Issue 8
PPoPP '13
August 2013
309 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/2517327
Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 February 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Poster

Conference

PPoPP '13

Sponsor:

SIGPLAN

PPoPP '13: ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

February 23 - 27, 2013

Shenzhen, China

Acceptance Rates

Overall Acceptance Rate 230 of 1,014 submissions, 23%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

31
Total Citations
View Citations
435
Total Downloads

Downloads (Last 12 months)13
Downloads (Last 6 weeks)0

Reflects downloads up to 14 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Puckelwartz MPesce LHernandez EWebster GDellefave-Castillo LRussell MGeisler SKearns SKarthik FEtheridge SMonroe TPottinger TKannankeril PShoemaker MFountain DRoden DFaulkner MMacLeod HBurns KYandell MTristani-Firouzi MGeorge AMcNally E(2024)The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the youngGenome Medicine10.1186/s13073-024-01284-w16:1Online publication date: 16-Jan-2024
https://doi.org/10.1186/s13073-024-01284-w
Wozniak JLiu ZVescovi RChard RNicolae BFoster I(2022)Braid-DB: Toward AI-Driven Science with Machine Learning ProvenanceDriving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation10.1007/978-3-030-96498-6_14(247-261)Online publication date: 10-Mar-2022
https://doi.org/10.1007/978-3-030-96498-6_14
Nookala PDinda PHale KChard KRaicu I(2021)Enabling Extremely Fine-grained Parallelism via Scalable Concurrent Queues on Modern Many-core Architectures2021 29th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)10.1109/MASCOTS53633.2021.9614292(1-8)Online publication date: 3-Nov-2021
https://doi.org/10.1109/MASCOTS53633.2021.9614292
Wolf MLogan JMehta KJacobson DCashman MWalker AEisenhauer GWidener PClif A(2021)Reusability First: Toward FAIR Workflows2021 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/Cluster48925.2021.00053(444-455)Online publication date: Sep-2021
https://doi.org/10.1109/Cluster48925.2021.00053
Liu JPineda LPacitti ECostan AValduriez PAntoniu GMattoso M(2019)Efficient Scheduling of Scientific Workflows Using Hot Metadata in a Multisite CloudIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.286785731:10(1940-1953)Online publication date: 1-Oct-2019
https://doi.org/10.1109/TKDE.2018.2867857
Ponce EStephenson BLenhart SDay JPeterson GSanielevici S(2018)PaPaSProceedings of the Practice and Experience on Advanced Research Computing10.1145/3219104.3229289(1-8)Online publication date: 22-Jul-2018
https://dl.acm.org/doi/10.1145/3219104.3229289
Searles RChandrasekaran SJoubert WHernandez O(2018)Abstractions and Directives for Adapting Wavefront Algorithms to Future ArchitecturesProceedings of the Platform for Advanced Scientific Computing Conference10.1145/3218176.3218228(1-10)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3218176.3218228
Fu YLi FSong FChen ZZhao MChandra ARamakrishnan L(2018)Performance analysis and optimization of in-situ integration of simulation with data analysisProceedings of the 27th International Symposium on High-Performance Parallel and Distributed Computing10.1145/3208040.3208049(192-205)Online publication date: 11-Jun-2018
https://dl.acm.org/doi/10.1145/3208040.3208049
Paduraru CMelemciuc M(2018)Parallelism in C++ Using Sequential Communicating Processes2018 17th International Symposium on Parallel and Distributed Computing (ISPDC)10.1109/ISPDC2018.2018.00030(157-163)Online publication date: Jun-2018
https://doi.org/10.1109/ISPDC2018.2018.00030
Hahnfeld JTerboven CPrice JPflug HMüller M(2018)Evaluation of Asynchronous Offloading Capabilities of Accelerator Programming Models for Multiple DevicesAccelerator Programming Using Directives10.1007/978-3-319-74896-2_9(160-182)Online publication date: 31-Jan-2018
https://doi.org/10.1007/978-3-319-74896-2_9
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

How swift developers handle errors

A Swift Introduction to Swift App Development (Abstract Only)

Swift/T: scalable data flow programming for many-task applications