The solution is MPI, the Message Passing Interface. Developed over the last several decades as an alternative to shared memory architectures (such as OpenMP), MPI enables developers to efficiently program "tightly coupled"...
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The solution is MPI, the Message Passing Interface. Developed over the last several decades as an alternative to shared memory architectures (such as OpenMP), MPI enables developers to efficiently program "tightly coupled" algorithms which require nodes to communicate during the course of a computation. MPI consists of a standard set of API calls, usually implemented as a platform-independent communications library, that manage all aspects of inter-node communication and data transfer. MPI provides an abstraction that works with any networking infrastructure (e.g., Ethernet, Myrinet, InfiniBand), while being flexible and consistent enough for developers to port and run their code on any parallel platform with only a recompile. Different implementations can be run either standalone, or embedded within scheduling solutions like Xgrid. And while Xgrid supports MPI applications, implementing such applications takes some careful planning, so this article helps you get familiar with your options and what each can provide.
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