Abstract: Based on the contemporary shared memory Symmetric Multi Processing parallel machines(SMP),and the directive parallel programming platform,this paper discusses optimization and parallelization of a sparse linear equations solver package MFS for reservoir simulation software with more than one million nodes.Firstly,with the high performance characteristics of contemporary microprocessors,we organize the optimization of MFS by adjusting both data and cycle structures for the Cache hit ratio,and improve the performance by 20% for R5000,and moreover,eliminate the potential Cache coherence collision during parallelization.Secondly,we parallelize the solver package MFS with the effective techniques such as cycle combination,domain decomposition and large granularity parallel pipeline.Finally,under POWER CHALLENGE R8000(6 CPUs) and R10000(8 CPUs),we organize the numerical experiments for some three-dimensional three-phase problem with half and one million nodes respectively,and the parallel efficiencies are all higher than 60%.

Key words: solver package, optimization, parallelization, numerical simulation, software

摘要： 在当前共享存储对称多处理(SMP)并行机上,基于指导语句的并行程序设计模式,讨论了多功能油藏数值模拟软件中求解超过百万节点规模的解法器(MFS)的并行和优化技术.首先,结合当前微处理器的高性能特征,为了提高Cache命中率,改进了数据和循环结构,并组织了MFS的性能优化,在R5000上获得了20%的性能提高,并消除了并行化将可能引入的Cache一致性冲突;然后,基于循环合并、区域分解和大粒度流水线并行技术,实现了MFS的并行化;最后,在POW-ERCHALLENGER8000的6台处理机和R10000的8台处理机上,对三维三相50万和100万节点规模问题,分别组织了数值实验,并取得了超过60%的并行效率.

关键词: 解法器, 优化, 并行化, 数值模拟, 软件