高性能并行可视化服务器的资源管理技术研究

Research on the Resources Management Technique of High-Performance Parallel Visualization Server

开发高性能并行可视化服务器可充分发挥高性能计算机的资源优势,实现基于高性能计算机的高效并行可视化服务,克服传统后处理模式科学可视化存在的效率低等问题。本文介绍了高性能并行可视化服务器的功能和组成结构,重点论述了在研究高性能并行可视化服务器资源管理技术中提出的基于任务属性的计算结点资源分配算法和基于线性回归的任务属性自适应维护算法,算法能够有效利用高性能计算机的计算资源完成科学计算可视化应用任务的计算节点分配,并具有良好的任务属性自适应维护功能。实验结果表明所提出的算法可针对大数据科学计算可视化任务特点,有效完成并行可视计算的任务调度和资源分配,提高科学计算可视化的效率。

Developing high-performance parallel visualization server can give full play to the advantages of resources in high-performance computer, provide efficient parallel visualization service based on high-performance computer, and overcome the low efficiency of after-treatment model in the tra-ditional visualization way. This thesis introduces the structure and functions of the high-perfor- mance parallel visualization server;focuses on the algorithm of resource allocation and optimizing in the high-performance parallel visualization server. The algorithm can allocate compute nodes with the resources of the high-performance computer for the scientific computation visualization application efficiently, and have a strong self-adapted ability. The result of the experiment indicates that our algorithm completed the allocation of computing resources efficiently according to the characteristics of big data scientific computation visualization tasks, and improved the efficiency of scientific computation visualization very much compared to the traditional visualization model.