Abstract
The current temperature field model of plate rolling process is generally based on CPU programming, due to the influence of computer performance, the accuracy and speed of the model can not be improved at the same time. To solve this problem, this paper studies the temperature field model with particle swarm optimization to modify the heat transfer coefficients, and the parallel program of this model is written under CUDA architecture, on premise of ensuring the accuracy of the model, the computation speed of the model is improved. To get the best acceleration, this paper analyzes the factors affecting GPU performance, the accuracy and speed of the temperature field model before and after modification are compared under the best acceleration configuration. Final temperature field model calculation error reduced to an average of 15.57 °C, better than the model based on the empirical formula, the computing speed is also improved, which is 1.78 times that of CPU.
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