OpenACC Parallelization of Stochastic Simulations on GPUs
Summary :
We present an OpenACC-based parallelization implementation of stochastic algorithms for simulating biochemical reaction networks on modern GPUs (graphics processing units). To investigate the effectiveness of using OpenACC for leveraging the massive hardware parallelism of the GPU architecture, we carefully apply OpenACC's language constructs and mechanisms to implementing a parallel version of stochastic simulation algorithms on the GPU. Using our OpenACC implementation in comparison to both the NVidia CUDA and the CPU-based implementations, we report our initial experiences on OpenACC's performance and programming productivity in the context of GPU-accelerated scientific computing.
- Publication
- IEICE TRANSACTIONS on Information Vol.E102-D No.8 pp.1565-1568
- Publication Date
- 2019/08/01
- Publicized
- 2019/05/17
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2019EDL8032
- Type of Manuscript
- LETTER
- Category
- Fundamentals of Information Systems
Authors
Pilsung KANG
Sun Moon University
Keyword
Latest Issue
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Pilsung KANG, "OpenACC Parallelization of Stochastic Simulations on GPUs" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 8, pp. 1565-1568, August 2019, doi: 10.1587/transinf.2019EDL8032.
Abstract: We present an OpenACC-based parallelization implementation of stochastic algorithms for simulating biochemical reaction networks on modern GPUs (graphics processing units). To investigate the effectiveness of using OpenACC for leveraging the massive hardware parallelism of the GPU architecture, we carefully apply OpenACC's language constructs and mechanisms to implementing a parallel version of stochastic simulation algorithms on the GPU. Using our OpenACC implementation in comparison to both the NVidia CUDA and the CPU-based implementations, we report our initial experiences on OpenACC's performance and programming productivity in the context of GPU-accelerated scientific computing.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019EDL8032/_p
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@ARTICLE{e102-d_8_1565,
author={Pilsung KANG, },
journal={IEICE TRANSACTIONS on Information},
title={OpenACC Parallelization of Stochastic Simulations on GPUs},
year={2019},
volume={E102-D},
number={8},
pages={1565-1568},
abstract={We present an OpenACC-based parallelization implementation of stochastic algorithms for simulating biochemical reaction networks on modern GPUs (graphics processing units). To investigate the effectiveness of using OpenACC for leveraging the massive hardware parallelism of the GPU architecture, we carefully apply OpenACC's language constructs and mechanisms to implementing a parallel version of stochastic simulation algorithms on the GPU. Using our OpenACC implementation in comparison to both the NVidia CUDA and the CPU-based implementations, we report our initial experiences on OpenACC's performance and programming productivity in the context of GPU-accelerated scientific computing.},
keywords={},
doi={10.1587/transinf.2019EDL8032},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - OpenACC Parallelization of Stochastic Simulations on GPUs
T2 - IEICE TRANSACTIONS on Information
SP - 1565
EP - 1568
AU - Pilsung KANG
PY - 2019
DO - 10.1587/transinf.2019EDL8032
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2019
AB - We present an OpenACC-based parallelization implementation of stochastic algorithms for simulating biochemical reaction networks on modern GPUs (graphics processing units). To investigate the effectiveness of using OpenACC for leveraging the massive hardware parallelism of the GPU architecture, we carefully apply OpenACC's language constructs and mechanisms to implementing a parallel version of stochastic simulation algorithms on the GPU. Using our OpenACC implementation in comparison to both the NVidia CUDA and the CPU-based implementations, we report our initial experiences on OpenACC's performance and programming productivity in the context of GPU-accelerated scientific computing.
ER -
English
