Publication detail

Parallel dynamic solidification model of continuous steel casting on GPU

KLIMEŠ, L. ŠTĚTINA, J.

Original Title

Parallel dynamic solidification model of continuous steel casting on GPU

English Title

Parallel dynamic solidification model of continuous steel casting on GPU

Type

conference paper

Language

en

Original Abstract

Nowadays, dynamic solidification models of continuously cast steel are commonly used in steelworks over the world to control the casting process and to monitor the steel production. Moreover, these models of transient temperature field can also be utilized for optimization of continuous casting, its on-line regulation, or may help operators to solve non-standard or breakdown situations that can occur when casting. In order to solve these problems in real time, parallel computing of dynamic solidification models can favourably be utilized. One of possible approaches is to use parallel computing on graphics processing units (GPUs) that offer a great computing performance in comparison to ordinary computing on CPUs. The paper describes an implementation of the parallel dynamic solidification model with the use of the CUDA architecture and NVIDIA GPUs. A comparison between the use of parallel and non-parallel models is presented and analysed. Results show that parallel computing on GPUs can considerably enhance the computing performance of solidification models and their use and efficiency in other tasks.

English abstract

Nowadays, dynamic solidification models of continuously cast steel are commonly used in steelworks over the world to control the casting process and to monitor the steel production. Moreover, these models of transient temperature field can also be utilized for optimization of continuous casting, its on-line regulation, or may help operators to solve non-standard or breakdown situations that can occur when casting. In order to solve these problems in real time, parallel computing of dynamic solidification models can favourably be utilized. One of possible approaches is to use parallel computing on graphics processing units (GPUs) that offer a great computing performance in comparison to ordinary computing on CPUs. The paper describes an implementation of the parallel dynamic solidification model with the use of the CUDA architecture and NVIDIA GPUs. A comparison between the use of parallel and non-parallel models is presented and analysed. Results show that parallel computing on GPUs can considerably enhance the computing performance of solidification models and their use and efficiency in other tasks.

Keywords

dynamic solidification model, continuous casting, GPU, GPGPU, parallel computing

RIV year

2013

Released

15.05.2013

Publisher

Tanger, s.r.o.

Location

Ostrava

ISBN

978-80-87294-39-0

Book

Conference proceedings of 22nd Conference on metallurgy and materials

Edition

první

Edition number

1

Pages from

34

Pages to

39

Pages count

6

Documents

BibTex


@inproceedings{BUT99671,
  author="Lubomír {Klimeš} and Josef {Štětina}",
  title="Parallel dynamic solidification model of continuous steel casting on GPU",
  annote="Nowadays, dynamic solidification models of continuously cast steel are commonly used in steelworks over the world to control the casting process and to monitor the steel production. Moreover, these models of transient temperature field can also be utilized for optimization of continuous casting, its on-line regulation, or may help operators to solve non-standard or breakdown situations that can occur when casting. In order to solve these problems in real time, parallel computing of dynamic solidification models can favourably be utilized. One of possible approaches is to use parallel computing on graphics processing units (GPUs) that offer a great computing performance in comparison to ordinary computing on CPUs. The paper describes an implementation of the parallel dynamic solidification model with the use of the CUDA architecture and NVIDIA GPUs. A comparison between the use of parallel and non-parallel models is presented and analysed. Results show that parallel computing on GPUs can considerably enhance the computing performance of solidification models and their use and efficiency in other tasks.",
  address="Tanger, s.r.o.",
  booktitle="Conference proceedings of 22nd Conference on metallurgy and materials",
  chapter="99671",
  edition="první",
  howpublished="electronic, physical medium",
  institution="Tanger, s.r.o.",
  year="2013",
  month="may",
  pages="34--39",
  publisher="Tanger, s.r.o.",
  type="conference paper"
}