Cargando…
Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators
Recent developments in modern computational accelerators like Graphics Processing Units (GPUs) and coprocessors provide great opportunities for making scientific applications run faster than ever before. However, efficient parallelization of scientific code using new programming tools like CUDA requ...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907428/ https://www.ncbi.nlm.nih.gov/pubmed/24497950 http://dx.doi.org/10.1371/journal.pone.0086484 |
_version_ | 1782301600014925824 |
---|---|
author | Wang, Wei Xu, Lifan Cavazos, John Huang, Howie H. Kay, Matthew |
author_facet | Wang, Wei Xu, Lifan Cavazos, John Huang, Howie H. Kay, Matthew |
author_sort | Wang, Wei |
collection | PubMed |
description | Recent developments in modern computational accelerators like Graphics Processing Units (GPUs) and coprocessors provide great opportunities for making scientific applications run faster than ever before. However, efficient parallelization of scientific code using new programming tools like CUDA requires a high level of expertise that is not available to many scientists. This, plus the fact that parallelized code is usually not portable to different architectures, creates major challenges for exploiting the full capabilities of modern computational accelerators. In this work, we sought to overcome these challenges by studying how to achieve both automated parallelization using OpenACC and enhanced portability using OpenCL. We applied our parallelization schemes using GPUs as well as Intel Many Integrated Core (MIC) coprocessor to reduce the run time of wave propagation simulations. We used a well-established 2D cardiac action potential model as a specific case-study. To the best of our knowledge, we are the first to study auto-parallelization of 2D cardiac wave propagation simulations using OpenACC. Our results identify several approaches that provide substantial speedups. The OpenACC-generated GPU code achieved more than [Image: see text] speedup above the sequential implementation and required the addition of only a few OpenACC pragmas to the code. An OpenCL implementation provided speedups on GPUs of at least [Image: see text] faster than the sequential implementation and [Image: see text] faster than a parallelized OpenMP implementation. An implementation of OpenMP on Intel MIC coprocessor provided speedups of [Image: see text] with only a few code changes to the sequential implementation. We highlight that OpenACC provides an automatic, efficient, and portable approach to achieve parallelization of 2D cardiac wave simulations on GPUs. Our approach of using OpenACC, OpenCL, and OpenMP to parallelize this particular model on modern computational accelerators should be applicable to other computational models of wave propagation in multi-dimensional media. |
format | Online Article Text |
id | pubmed-3907428 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39074282014-02-04 Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators Wang, Wei Xu, Lifan Cavazos, John Huang, Howie H. Kay, Matthew PLoS One Research Article Recent developments in modern computational accelerators like Graphics Processing Units (GPUs) and coprocessors provide great opportunities for making scientific applications run faster than ever before. However, efficient parallelization of scientific code using new programming tools like CUDA requires a high level of expertise that is not available to many scientists. This, plus the fact that parallelized code is usually not portable to different architectures, creates major challenges for exploiting the full capabilities of modern computational accelerators. In this work, we sought to overcome these challenges by studying how to achieve both automated parallelization using OpenACC and enhanced portability using OpenCL. We applied our parallelization schemes using GPUs as well as Intel Many Integrated Core (MIC) coprocessor to reduce the run time of wave propagation simulations. We used a well-established 2D cardiac action potential model as a specific case-study. To the best of our knowledge, we are the first to study auto-parallelization of 2D cardiac wave propagation simulations using OpenACC. Our results identify several approaches that provide substantial speedups. The OpenACC-generated GPU code achieved more than [Image: see text] speedup above the sequential implementation and required the addition of only a few OpenACC pragmas to the code. An OpenCL implementation provided speedups on GPUs of at least [Image: see text] faster than the sequential implementation and [Image: see text] faster than a parallelized OpenMP implementation. An implementation of OpenMP on Intel MIC coprocessor provided speedups of [Image: see text] with only a few code changes to the sequential implementation. We highlight that OpenACC provides an automatic, efficient, and portable approach to achieve parallelization of 2D cardiac wave simulations on GPUs. Our approach of using OpenACC, OpenCL, and OpenMP to parallelize this particular model on modern computational accelerators should be applicable to other computational models of wave propagation in multi-dimensional media. Public Library of Science 2014-01-30 /pmc/articles/PMC3907428/ /pubmed/24497950 http://dx.doi.org/10.1371/journal.pone.0086484 Text en © 2014 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Wang, Wei Xu, Lifan Cavazos, John Huang, Howie H. Kay, Matthew Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators |
title | Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators |
title_full | Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators |
title_fullStr | Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators |
title_full_unstemmed | Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators |
title_short | Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators |
title_sort | fast acceleration of 2d wave propagation simulations using modern computational accelerators |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907428/ https://www.ncbi.nlm.nih.gov/pubmed/24497950 http://dx.doi.org/10.1371/journal.pone.0086484 |
work_keys_str_mv | AT wangwei fastaccelerationof2dwavepropagationsimulationsusingmoderncomputationalaccelerators AT xulifan fastaccelerationof2dwavepropagationsimulationsusingmoderncomputationalaccelerators AT cavazosjohn fastaccelerationof2dwavepropagationsimulationsusingmoderncomputationalaccelerators AT huanghowieh fastaccelerationof2dwavepropagationsimulationsusingmoderncomputationalaccelerators AT kaymatthew fastaccelerationof2dwavepropagationsimulationsusingmoderncomputationalaccelerators |