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Title: Comparing High Performance Computing Accelerator Programming Models

Abstract

Accelerator devices are becoming a norm in High Performance Computing (HPC). With more systems opting for heterogeneous architectures, portable programming models like OpenMP and OpenACC are becoming increasingly important. The SPEC ACCEL 1.2 benchmark suite consists of comparable benchmarks in OpenCL, OpenMP 4.5, and OpenACC 2.5 that can be used to evaluate the performance and support for programming models and frameworks on heterogeneous platforms. In this paper we go beneath the normative metric of performance times and look at the individual kernels to study the usage, strengths, and weaknesses of the two prevalent portable heterogeneous programming models, OpenMP and OpenACC. From our analysis we identify that benchmarks like MRI-Q, SP and BT have better performance using OpenACC, while benchmarks like MiniGhost, LBM and LBDC do consistently better with the OpenMP programming model across supercomputers like Titan, and Summit.We deep dive into the kernels of select four benchmarks to answer questions like: Where does the benchmark spend most of its cycles? What is the parallelization strategy used? Why is one programming model more performant than the other? By identifying the similarities and dierences we want to contrast between the benchmark implementation strategies in the SPEC ACCEL 1.2 benchmarks and provide moremore » insights into the OpenMP and OpenACC programming models.« less

Authors:
ORCiD logo [1]; 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:
1559634
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: ISC High Performance (ISC HPC 2019) - Frankfurt, , Germany - 6/22/2019 8:00:00 AM-6/26/2019 8:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Pophale, Swaroop S., Boehm, Swen, and Melesse Vergara, Veronica. Comparing High Performance Computing Accelerator Programming Models. United States: N. p., 2019. Web.
Pophale, Swaroop S., Boehm, Swen, & Melesse Vergara, Veronica. Comparing High Performance Computing Accelerator Programming Models. United States.
Pophale, Swaroop S., Boehm, Swen, and Melesse Vergara, Veronica. Thu . "Comparing High Performance Computing Accelerator Programming Models". United States. https://www.osti.gov/servlets/purl/1559634.
@article{osti_1559634,
title = {Comparing High Performance Computing Accelerator Programming Models},
author = {Pophale, Swaroop S. and Boehm, Swen and Melesse Vergara, Veronica},
abstractNote = {Accelerator devices are becoming a norm in High Performance Computing (HPC). With more systems opting for heterogeneous architectures, portable programming models like OpenMP and OpenACC are becoming increasingly important. The SPEC ACCEL 1.2 benchmark suite consists of comparable benchmarks in OpenCL, OpenMP 4.5, and OpenACC 2.5 that can be used to evaluate the performance and support for programming models and frameworks on heterogeneous platforms. In this paper we go beneath the normative metric of performance times and look at the individual kernels to study the usage, strengths, and weaknesses of the two prevalent portable heterogeneous programming models, OpenMP and OpenACC. From our analysis we identify that benchmarks like MRI-Q, SP and BT have better performance using OpenACC, while benchmarks like MiniGhost, LBM and LBDC do consistently better with the OpenMP programming model across supercomputers like Titan, and Summit.We deep dive into the kernels of select four benchmarks to answer questions like: Where does the benchmark spend most of its cycles? What is the parallelization strategy used? Why is one programming model more performant than the other? By identifying the similarities and dierences we want to contrast between the benchmark implementation strategies in the SPEC ACCEL 1.2 benchmarks and provide more insights into the OpenMP and OpenACC programming models.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}

Conference:
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