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Title: Early Evaluation of Directive-Based GPU Programming Models for Productive Exascale Computing

Abstract

Graphics Processing Unit (GPU)-based parallel computer architectures have shown increased popularity as a building block for high performance computing, and possibly for future Exascale computing. However, their programming complexity remains as a major hurdle for their widespread adoption. To provide better abstractions for programming GPU architectures, researchers and vendors have proposed several directive-based GPU programming models. These directive-based models provide different levels of abstraction, and required different levels of programming effort to port and optimize applications. Understanding these differences among these new models provides valuable insights on their applicability and performance potential. In this paper, we evaluate existing directive-based models by porting thirteen application kernels from various scientific domains to use CUDA GPUs, which, in turn, allows us to identify important issues in the functionality, scalability, tunability, and debuggability of the existing models. Our evaluation shows that directive-based models can achieve reasonable performance, compared to hand-written GPU codes.

Authors:
ORCiD logo [1]; ORCiD logo [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1261389
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: SC12: ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis - Salt Lake City, Utah, United States of America - 11/10/2012 12:00:00 AM-11/16/2012 12:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Lee, Seyong, and Vetter, Jeffrey S. Early Evaluation of Directive-Based GPU Programming Models for Productive Exascale Computing. United States: N. p., 2012. Web. doi:10.1109/SC.2012.51.
Lee, Seyong, & Vetter, Jeffrey S. Early Evaluation of Directive-Based GPU Programming Models for Productive Exascale Computing. United States. doi:10.1109/SC.2012.51.
Lee, Seyong, and Vetter, Jeffrey S. Thu . "Early Evaluation of Directive-Based GPU Programming Models for Productive Exascale Computing". United States. doi:10.1109/SC.2012.51.
@article{osti_1261389,
title = {Early Evaluation of Directive-Based GPU Programming Models for Productive Exascale Computing},
author = {Lee, Seyong and Vetter, Jeffrey S.},
abstractNote = {Graphics Processing Unit (GPU)-based parallel computer architectures have shown increased popularity as a building block for high performance computing, and possibly for future Exascale computing. However, their programming complexity remains as a major hurdle for their widespread adoption. To provide better abstractions for programming GPU architectures, researchers and vendors have proposed several directive-based GPU programming models. These directive-based models provide different levels of abstraction, and required different levels of programming effort to port and optimize applications. Understanding these differences among these new models provides valuable insights on their applicability and performance potential. In this paper, we evaluate existing directive-based models by porting thirteen application kernels from various scientific domains to use CUDA GPUs, which, in turn, allows us to identify important issues in the functionality, scalability, tunability, and debuggability of the existing models. Our evaluation shows that directive-based models can achieve reasonable performance, compared to hand-written GPU codes.},
doi = {10.1109/SC.2012.51},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {11}
}

Conference:
Other availability
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