|KLIMEŠ Lubomír||Vysoké učení technické v Brně|
|Spoluautoři ŠTĚTINA Josef|
Nowadays, dynamic solidification models of continuously cast steel are commonly used in steelworks over the world to control both the caster and the casting process and to monitor the steel production. Moreover, these numerical models of 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 during steel casting. In order to solve these problems in real time, the parallel computing of dynamic solidification models can favourably be utilized. One of possible approaches is to use the parallel computing on graphics processing units (GPUs) that offer a great computing performance in comparison to ordinary computing on processors. The paper describes the implementation of the parallel dynamic solidification model with the use of the CUDA architecture and the NVIDIA GPUs. The comparison between the use of parallel and non-parallel models is presented and analysed. The results show that GPUs and parallel computing can considerably enhance the computing performance of dynamic solidification models and their use and efficiency in other tasks.