Task scheduling based on swarm intelligence algorithms in high performance computing environment

The high-performance computing environment is a computing platform, which aggregates multiple distributed high-performance computers from indifferent organizations, providing users with unified access and usage patterns. Since the task scheduling strategy is lack of flexibility, an optimized task scheduling model in the high-performance computing environment is proposed in this paper, which introduces an improved swarm intelligence algorithm in task queues, refines the Core Scheduler for each task, and increases the configuration of task scheduling strategy. In core task scheduling, swarm intelligence algorithm is adopted to minimize the average scheduling time for completion tasks through optimal task allocation on each node. Simulation results show that the proposed scheduling algorithm is better than the traditional task scheduling algorithm. Therefore, according to the task scheduling strategy based on swarm intelligence algorithm, it can effectively reduce the task waiting, improve the system’s throughput, the task response and system resource utilization has a better effect.