ektrules said:Or is there some structure where a node will receive data from a few other nodes, perform a reduction, then pass the intermediate results to other nodes?
If comm is an intracommunicator, MPI_ALLREDUCE behaves the same as MPI_REDUCE except that the result appears in the receive buffer of all the group members.
MPI collective operations involve multiple processes communicating and coordinating with each other to perform a collective action, such as sending or receiving data from a group of processes.
The purpose of MPI collective operations is to improve the performance of parallel programs by allowing multiple processes to work together and share data efficiently.
Yes, MPI collective operations typically involve multiple hops, meaning that data is passed through multiple processes before reaching its final destination.
The use of multiple hops in MPI collective operations can impact performance, as it adds overhead and increases the time it takes for data to be transferred between processes. However, this can be minimized by using efficient algorithms and optimizing the communication patterns.
There are alternatives to using MPI collective operations with multiple hops, such as point-to-point communication where data is sent directly between two processes. However, this may not be as efficient for certain collective actions, and the use of multiple hops can still be optimized for better performance.