The Novel Estimation Model of Parallel Minimum-Computing-Time Node Size
Yue Hu, Zhen Yan · 2022 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) · 2022
It is time-consuming to test parallel program, which has become one of the bottlenecks in applying parallel software. In this paper, we intensively study the essence of parallel program when it is running, and point out that the parallel computing time can be expressed by the amount of computation. Based on this, a mathematical estimation model is proposed. In this model, the parallel computing time function is expressed by mathematical formula, and the parallel node size can be calculated when the derivative is zero. The calculated parallel node size is the reference value when the parallel computing time is shortest. This model can greatly reduce parallel program running time, and can also supports platform-independent handling by calculating the derivative, which ignores the influence of the unit data computing time and the running system's software and hardware. The experimental results indicate the effectiveness of the discussions.