Prospects for Improving the Performance of Parallel Computing Using Python Subinterpreter Technology

The problem of the impact of global interpreter locking on the performance of multithreaded applications in Python is considered. The concept of subinterpreters is described as a solution that circumvents the limitations of the GIL and ensure efficient parallel code execution. A comparative analysis of subinterpreters with traditional methods of parallel computing, such as the use of processes and threads, is carried out. Experimental results have shown that subinterpreters significantly increase performance in conditions of high computing loads. In addition, the possibilities of using subinterpreters in web development are explored. The advantages of using this approach for query processing and resource management in modern web applications are indicated, which can significantly improve their scalability and responsiveness. The novelty of this research lies in the in-depth analysis of subinterpreters in the context of specific use cases, which had not previously received sufficient coverage in the scientific literature. The results of the work emphasize the need for further study of subinterpreters as an alternative approach in Python and the interest of developers and researchers in the field of high-performance computing in this.