基于Abaqus软件的并行计算异构集群平台的搭建
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摘要
在异构集群上充分利用新、旧硬件资源调度计算任务是实现集群高性能并行计算的难点。通过测试已搭建集群服务器的CPU和内存对Abaqus软件计算速度的影响,发现CPU的主频对Abaqus/Explicit模块计算速度的影响大,CPU的缓存对Abaqus/Standard模块速度影响大;当内存满足计算任务的最小需求时,增加内存对计算速度无任何影响;当内存不足时,计算速度会大幅减慢。据此测试结果,新增4台服务器作为计算节点和一台Infiniband QDR交换机作为交换节点,搭建了新的异构集群,性能测试结果表明:相对于千兆以太网络交换机I,nfiniband QDR交换机的并行计算效率更好,且集群的计算节点越多越显著;Abaqus/Standard模块并行计算效率的提高幅度要比Abaqus/Explicit模块的稍高一些。针对异构集群硬件构架相差较大的2批新、旧硬件,设置了2个管理节点、2个网络节点、2个存储节点,充分利用了新、旧硬件资源,高效地实现了在一个异构集群平台上提交与下载任务。
Taking full advantage of new and old hardware resources on the heterogeneous cluster to schedule computing jobs is a difficult point in the realization of high performance parallel computing.The influence of servers' CPU and memory on computing speed of Abaqus software on the cluster which has been constructed is tested.The conclusions are drawn: CPU clock speed has a great effect on the computing speed of Abaqus/Explicit module and CPU internal cache has a great effect on computing speed of Abaqus/Standard module.When memory satisfies the minimum requirement of a computing job,increasing memory has no effect on the computing speed.When memory is insufficient,computing speed will slow down sharply.According to the testing results,four servers as the computing nodes and an Infiniband QDR switch as the network node are added,and then the heterogeneous cluster is constructed.Parallel computing speed of the Infiniband QDR switch is tested,and the result shows that the parallel effect of the Infiniband QDR switch is superior to the gigabit ethernet switch.The more the number of computing nodes is,the better the parallel effect is.Abaqus/Standard module's elevated range of parallel computing efficiency is slightly better than Abaqus/ Explicit module's.Specific to two groups of new and old equipment whose architectures are quite different,two management nodes,two network nodes and two storage nodes are set up.The new and old hardware resources are taken full advantage,then submission and download of jobs from the heterogeneous cluster platform is achieved efficiently.
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