Implementing the OpenACC data model

Michael Wolfe; Seyong Lee; Jungwon Kim; Xiaonan Tian; Rengan Xu; Sunita Chandrasekaran; Barbara Chapman

doi:10.1109/IPDPSW.2017.85

Implementing the OpenACC data model

Michael Wolfe, Seyong Lee, Jungwon Kim, Xiaonan Tian, Rengan Xu, Sunita Chandrasekaran, Barbara Chapman

Programming Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

Programming accelerators today usually requires managing separate virtual and physical memories, such as allocating space in and copying data between host and device memories. The OpenACC API provides data directives and clauses to control this behavior where it is required. This paper describes how the data model is supported in current OpenACC implementations, ranging from research compilers (OpenUH and OpenARC) to a commercial compiler (the PGI OpenACC compiler). This includes implementation of the data directives and clauses, testing whether the data is already present on the device, OpenCL support, managing asynchronous data trans- fers and memory allocations, handling aliased data, reusing device memory, managing partially present data, and support for shared memory between host and device. Lastly, it also discusses on-going work to manage large, complex dynamic data structures.

Original language	English
Title of host publication	Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	662-672
Number of pages	11
ISBN (Electronic)	9781538634080
DOIs	https://doi.org/10.1109/IPDPSW.2017.85
State	Published - Jun 30 2017
Event	31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017 - Orlando, United States Duration: May 29 2017 → Jun 2 2017

Publication series

Name	Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017

Conference

Conference	31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017
Country/Territory	United States
City	Orlando
Period	05/29/17 → 06/2/17

Funding

ACKNOWLEDGMENT This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy.

Keywords

Accelerator
GPGPU

Access to Document

10.1109/IPDPSW.2017.85

Cite this

Wolfe, M., Lee, S., Kim, J., Tian, X., Xu, R., Chandrasekaran, S., & Chapman, B. (2017). Implementing the OpenACC data model. In Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017 (pp. 662-672). Article 7965108 (Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPDPSW.2017.85

Wolfe, Michael ; Lee, Seyong ; Kim, Jungwon et al. / Implementing the OpenACC data model. Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 662-672 (Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017).

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abstract = "Programming accelerators today usually requires managing separate virtual and physical memories, such as allocating space in and copying data between host and device memories. The OpenACC API provides data directives and clauses to control this behavior where it is required. This paper describes how the data model is supported in current OpenACC implementations, ranging from research compilers (OpenUH and OpenARC) to a commercial compiler (the PGI OpenACC compiler). This includes implementation of the data directives and clauses, testing whether the data is already present on the device, OpenCL support, managing asynchronous data trans- fers and memory allocations, handling aliased data, reusing device memory, managing partially present data, and support for shared memory between host and device. Lastly, it also discusses on-going work to manage large, complex dynamic data structures.",

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Wolfe, M, Lee, S, Kim, J, Tian, X, Xu, R, Chandrasekaran, S & Chapman, B 2017, Implementing the OpenACC data model. in Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017., 7965108, Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017, Institute of Electrical and Electronics Engineers Inc., pp. 662-672, 31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017, Orlando, United States, 05/29/17. https://doi.org/10.1109/IPDPSW.2017.85

Implementing the OpenACC data model. / Wolfe, Michael; Lee, Seyong; Kim, Jungwon et al.
Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 662-672 7965108 (Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2017/6/30

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AB - Programming accelerators today usually requires managing separate virtual and physical memories, such as allocating space in and copying data between host and device memories. The OpenACC API provides data directives and clauses to control this behavior where it is required. This paper describes how the data model is supported in current OpenACC implementations, ranging from research compilers (OpenUH and OpenARC) to a commercial compiler (the PGI OpenACC compiler). This includes implementation of the data directives and clauses, testing whether the data is already present on the device, OpenCL support, managing asynchronous data trans- fers and memory allocations, handling aliased data, reusing device memory, managing partially present data, and support for shared memory between host and device. Lastly, it also discusses on-going work to manage large, complex dynamic data structures.

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Wolfe M, Lee S, Kim J, Tian X, Xu R, Chandrasekaran S et al. Implementing the OpenACC data model. In Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 662-672. 7965108. (Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017). doi: 10.1109/IPDPSW.2017.85

Implementing the OpenACC data model

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