问题描述
在我的实验室中，我们有几个用于模拟程序的服务器，但是它们是独立工作的.现在，我想使用MPICH将它们组合成一个集群，以使它们进行通信.但是存在一个问题，那就是这些服务器具有不同的操作系统.其中一些是Redhat，一些是Ubuntu.在MPICH的主页上，我看到这两个不同的操作系统的下载站点是不同的，那么是否有可能建立一个具有不同操作系统的集群?以及如何做到?
In my lab, we have several servers used for the simulation programs, but they worked independently. Now I want to combine them to become a cluster using MPICH to make them communicate. But there exists a problem, which is that these servers have different OSs. Some of them are Redhat, and some of them are Ubuntu. And on the homepage of MPICH, I saw that download sites of these two different operating systems are different, so will it be possible to set up a cluster with different operating system? And how to do it?
我不想重新安装这些服务器的原因是它们上的数据太多，当我问这个问题时，它们的使用量不足.
The reason why I don't want to reinstall these servers is that there are too many data on them and they are under used when I ask this question.
推荐答案
使其正常工作是不可行的.您应该能够获得在不同发行版上手动安装的相同版本的MPI实现.他们甚至可以正确地互相交谈.但是，一旦您尝试使用动态库运行实际的应用程序，就会遇到共享库，glibc等不同版本的麻烦.您将很容易静态链接所有内容或为不同的发行版构建不同的二进制文件.归根结底，您只会追逐遇到的一个问题.
It is not feasible to get this working properly. You should be able to get the same version of an MPI implementation manually installed on different distributions. They might even talk to each other properly. But as soon you try to run actual applications, with dynamic libraries, you will get into trouble with different versions of shared libraries, glibc etc. You will be tempted to link everything statically or build different binaries for the different distributions. At the end of the day, you will just chase one issue you run into after another.
作为边节点，将某些服务器与MPI组合在一起不会构成高性能计算集群.例如，HPC系统具有复杂的高性能互连和高性能并行文件系统.
As a side node, combining some servers together with MPI does not make a High Performance Computing cluster. For instance an HPC system has sophisticated high performance interconnects and a high performance parallel file system.
还请注意，典型的HPC应用程序将无法在异构硬件上运行(因为每个节点具有不同的CPU/内存配置).
Also note that your typical HPC application is going to run poorly on heterogeneous hardware (as in each node has different CPU / memory configurations).
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