Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms

Jacob Lambert; Mohammad Alaul Haque Monil; Seyong Lee; Allen D. Malony; Jeffrey S. Vetter

doi:10.1109/P3HPC56579.2022.00007

Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms

Jacob Lambert, Mohammad Alaul Haque Monil, Seyong Lee, Allen D. Malony, Jeffrey S. Vetter

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

1 Scopus citations

Abstract

Accelerator-based heterogeneous computing is the de facto standard in current and upcoming exascale machines. These heterogeneous resources empower computational scientists to select a machine or platform well-suited to their domain or applications. However, this diversity of machines also poses challenges related to programming model selection: inconsistent availability of programming models across different exascale systems, lack of performance portability for those programming models that do span several systems, and inconsistent performance between different models on a single platform. We explore these challenges on exascale-similar hardware, including AMD MI100 and NVIDIA A100 GPUs. By extending the sourceto-source compiler OpenARC, we demonstrate the power of automated translation of applications written in a single frontend programming model (OpenACC) into a variety of backend models (OpenMP, OpenCL, CUDA, HIP) that span the upcoming exascale environments. This translation enables us to compare performance within and across devices and to analyze programming model behavior with profiling tools.

Original language	English
Title of host publication	Proceedings of P3HPC 2022
Subtitle of host publication	2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	14-25
Number of pages	12
ISBN (Electronic)	9781665460217
DOIs	https://doi.org/10.1109/P3HPC56579.2022.00007
State	Published - 2022
Event	5th IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC, P3HPC 2022 - Dallas, United States Duration: Nov 13 2022 → Nov 18 2022

Publication series

Name	Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference	5th IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC, P3HPC 2022
Country/Territory	United States
City	Dallas
Period	11/13/22 → 11/18/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

CCAMP
CUDA
HIP
OpenACC
OpenARC
OpenCL
OpenMP

Access to Document

10.1109/P3HPC56579.2022.00007

Cite this

Lambert, J., Monil, M. A. H., Lee, S., Malony, A. D., & Vetter, J. S. (2022). Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms. In Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 14-25). (Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/P3HPC56579.2022.00007

Lambert, Jacob ; Monil, Mohammad Alaul Haque ; Lee, Seyong et al. / Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms. Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 14-25 (Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis).

@inproceedings{bda4e790649d4ddeb35482c170c5e7b0,

title = "Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms",

abstract = "Accelerator-based heterogeneous computing is the de facto standard in current and upcoming exascale machines. These heterogeneous resources empower computational scientists to select a machine or platform well-suited to their domain or applications. However, this diversity of machines also poses challenges related to programming model selection: inconsistent availability of programming models across different exascale systems, lack of performance portability for those programming models that do span several systems, and inconsistent performance between different models on a single platform. We explore these challenges on exascale-similar hardware, including AMD MI100 and NVIDIA A100 GPUs. By extending the sourceto-source compiler OpenARC, we demonstrate the power of automated translation of applications written in a single frontend programming model (OpenACC) into a variety of backend models (OpenMP, OpenCL, CUDA, HIP) that span the upcoming exascale environments. This translation enables us to compare performance within and across devices and to analyze programming model behavior with profiling tools.",

keywords = "CCAMP, CUDA, HIP, OpenACC, OpenARC, OpenCL, OpenMP",

author = "Jacob Lambert and Monil, {Mohammad Alaul Haque} and Seyong Lee and Malony, {Allen D.} and Vetter, {Jeffrey S.}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC, P3HPC 2022 ; Conference date: 13-11-2022 Through 18-11-2022",

year = "2022",

doi = "10.1109/P3HPC56579.2022.00007",

language = "English",

series = "Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "14--25",

booktitle = "Proceedings of P3HPC 2022",

}

Lambert, J, Monil, MAH , Lee, S, Malony, AD & Vetter, JS 2022, Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms. in Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis. Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis, Institute of Electrical and Electronics Engineers Inc., pp. 14-25, 5th IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC, P3HPC 2022, Dallas, United States, 11/13/22. https://doi.org/10.1109/P3HPC56579.2022.00007

Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms. / Lambert, Jacob; Monil, Mohammad Alaul Haque ; Lee, Seyong et al.
Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers Inc., 2022. p. 14-25 (Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis).

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

TY - GEN

T1 - Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms

AU - Lambert, Jacob

AU - Monil, Mohammad Alaul Haque

AU - Lee, Seyong

AU - Malony, Allen D.

AU - Vetter, Jeffrey S.

PY - 2022

Y1 - 2022

N2 - Accelerator-based heterogeneous computing is the de facto standard in current and upcoming exascale machines. These heterogeneous resources empower computational scientists to select a machine or platform well-suited to their domain or applications. However, this diversity of machines also poses challenges related to programming model selection: inconsistent availability of programming models across different exascale systems, lack of performance portability for those programming models that do span several systems, and inconsistent performance between different models on a single platform. We explore these challenges on exascale-similar hardware, including AMD MI100 and NVIDIA A100 GPUs. By extending the sourceto-source compiler OpenARC, we demonstrate the power of automated translation of applications written in a single frontend programming model (OpenACC) into a variety of backend models (OpenMP, OpenCL, CUDA, HIP) that span the upcoming exascale environments. This translation enables us to compare performance within and across devices and to analyze programming model behavior with profiling tools.

AB - Accelerator-based heterogeneous computing is the de facto standard in current and upcoming exascale machines. These heterogeneous resources empower computational scientists to select a machine or platform well-suited to their domain or applications. However, this diversity of machines also poses challenges related to programming model selection: inconsistent availability of programming models across different exascale systems, lack of performance portability for those programming models that do span several systems, and inconsistent performance between different models on a single platform. We explore these challenges on exascale-similar hardware, including AMD MI100 and NVIDIA A100 GPUs. By extending the sourceto-source compiler OpenARC, we demonstrate the power of automated translation of applications written in a single frontend programming model (OpenACC) into a variety of backend models (OpenMP, OpenCL, CUDA, HIP) that span the upcoming exascale environments. This translation enables us to compare performance within and across devices and to analyze programming model behavior with profiling tools.

KW - CCAMP

KW - CUDA

KW - HIP

KW - OpenACC

KW - OpenARC

KW - OpenCL

KW - OpenMP

UR - http://www.scopus.com/inward/record.url?scp=85147963838&partnerID=8YFLogxK

U2 - 10.1109/P3HPC56579.2022.00007

DO - 10.1109/P3HPC56579.2022.00007

M3 - Conference contribution

AN - SCOPUS:85147963838

T3 - Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis

SP - 14

EP - 25

BT - Proceedings of P3HPC 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC, P3HPC 2022

Y2 - 13 November 2022 through 18 November 2022

ER -

Lambert J, Monil MAH , Lee S, Malony AD, Vetter JS. Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms. In Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis. Institute of Electrical and Electronics Engineers Inc. 2022. p. 14-25. (Proceedings of P3HPC 2022: 2022 International Workshop on Performance, Portability and Productivity in HPC, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis). doi: 10.1109/P3HPC56579.2022.00007

Leveraging Compiler-Based Translation to Evaluate a Diversity of Exascale Platforms

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this