Mr. Boyan Li Profile

Boyan Li

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Proceedings Article | 21 July 2023 Paper

Research on topology mapping strategy based on improved genetic algorithm

Hang Yang, Boyan Li, Zhan Yang, Zhuoheng Lv, Tao Zhang

Proceedings Volume 12717, 127171Y (2023) https://doi.org/10.1117/12.2685327

KEYWORDS: Genetic algorithms, Mathematical optimization, Algorithm development, Modeling, Particle swarm optimization, Spine, Simulations, Genetics

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The progress of scientific development requires the use of high-performance computers for large-scale simulations, resulting in a significant communication overhead and thereby constraining the computer's performance. To address this issue, optimizing the topological mapping of application processes to computing nodes is essential for enhancing the communication performance of high-performance computers. However, this topic has not been extensively explored in the literature. In order to reduce the communication overhead of high-performance applications, this study formulates the optimization of topological mapping from application processes to computing nodes as a quadratic allocation problem. The proposed method collects communication features to assess the communication intimacy between processes and considers the communication relationship between application processes and network topology. To overcome the limitations of traditional genetic algorithms, this study introduces elite learning and adaptive selection into the mutation operator. In this algorithm, individuals undergoing mutation learn from fragments of the best individuals in the current population. Additionally, three functions are selected to control the probability of selecting the elite learning mutation during the mutation process, thereby enhancing the algorithm's efficiency and accuracy. The results of the experiments demonstrate that the suggested methodology yields a noteworthy enhancement in communication performance compared to the widely adopted round-robin approach in NPB test suites. Furthermore, the enhanced genetic algorithm displays superior optimization efficiency in comparison to conventional genetic algorithms and other heuristic approaches.

Proceedings Article | 13 April 2023 Paper

Research on application containerized deployment workflow for high performance computing environment

Boyan Li, Lei Zhang, Menglong Hu, Hang Yang, Zhuoheng Lv

Proceedings Volume 12605, 126050S (2023) https://doi.org/10.1117/12.2673281

KEYWORDS: Parallel computing, Parallel processing, Operating systems, Computing systems, Computer simulations

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The deployment of scientific computing software in a high-performance computing environment is very complicated and often requires many dependent libraries. How to quickly build a scientific computing environment is very important. Containers provide a flexible way to deploy software due to their lightweight and easy portability. Taking the deployment of material simulation software VASP as an example, this paper proposes a standardized process for building HPC containerized applications. Use Docker and Singularity container technology to realize containerized packaging of applications, solve complex application deployment, and realize the goal of "manufacture once, run anywhere". Based on the original Slurm workload on HPC, combined with the message passing interface technology, it can realize multi-machine parallel processing of containerized jobs in a high-performance environment without changing the user's habit of submitting jobs. The lab part starts with HPL benchmarks and then evaluates the performance of VASP applications on containers and physical machines. Experimental results show that the containerization process is feasible and flexible, and the performance overhead after containerization is within 4%. This research is expected to provide an effective solution for the construction and operation of containerized applications in the high-performance computing field.

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