MPI stands for Message Passing Interface, which is a standardized messaging protocol and programming model used for parallel computing in cluster and distributed computing environments. It is designed to facilitate communication and coordination among multiple processes that run simultaneously and independently on different nodes or computers in a cluster.
In the context of high-performance computing, MPI allows for the exchange of messages and data between processes, enabling them to cooperate and collectively solve computational problems that may require significant processing power. It provides a set of functions and libraries that programmers can use to create parallel applications by composing separate processes that exchange data and synchronize execution.
MPI provides a flexible and scalable approach to parallel programming, making it possible to utilize the computational resources of a cluster effectively. It supports various communication modes, including point-to-point communication, collective communication, and one-sided remote memory access, allowing for efficient communication patterns in diverse parallel algorithms.
The MPI programming model includes notions such as communicators, groups, ranks, and message passing operations. This enables the organization of processes into logical groups, identification of processes within a group, and exchange of data through send and receive operations. Additionally, MPI supports various data types and allows for custom data structures to be defined and transmitted.
Through its extensive set of features and robustness, MPI has become widely adopted and supported in the HPC community, providing a standard interface for inter-process communication that enables the development of scalable and efficient parallel applications.
