针对共享内存SPMD程序的通信流依赖分析方法

Method of communication flow dependence analysis for shared-memory SPMD program

传统数据流依赖分析方法在处理共享内存单指令多数据(SPMD)程序时,不能识别共享数据访问语句所属的处理节点,也不能消除执行顺序不定的控制流对共享数据流依赖造成的影响,从而在分析共享数据依赖时产生精度较低的结果。根据共享内存SPMD程序的共享数据别名特性,提出了一种可扩展的共享数据通信流依赖分析方法,并将其应用于一个编译后端分析器原型中。实验表明,该方法较传统分析方法可发现更多精确的共享数据通信流依赖。

The traditional analysis methods of data flow dependence cannot recognize the processing nodes to which the statements for accessing shared data should belong and also cannot avoid the impact caused by the control flow whose sequence is non-deterministic while dealing with shared memory Single Program Multiple Data（SPMD）program,thus generating the results with a lower accuracy when they analyze shared data dependence.A scalable analysis method of shared data communication-flow dependence was presented according to the alias feature of shared data in shared-memory SPMD program,which was applied in a prototype of back-end analyzer.The experimental results show that the new method can find more accurate shared data communication-flow dependence than the traditional method.