12 Advanced parallelism with teams, events, and collectives
This chapter covers
- Forming teams of parallel images for different tasks
- Synchronizing execution by posting and waiting for events
- Exchanging data across images using collectives
Parallel programming is ubiquitous in many applications in science and engineering, such as aerodynamics, weather and ocean prediction, and machine learning. Parallel programming lets you distribute work between many CPUs, allowing the program to finish sooner. Distributing the work also reduces the amount of memory needed by the program, so parallelism allows running large programs that otherwise wouldn’t fit into the memory of a single computer. Fortran is natively parallel, which means that the syntax ...
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