I have a question for those who have parallelized programs. It seems like MPI is the obvious architecture when scaling a program to multiple machines. Let's assume that we implement a program that has that capability.
Now, it is possible to use MPI for scaling *within* a compute node. For example, on a 4-core machine we could run four processes and use MPI to synchronize them. That policy has the obvious downside that the shared memory on a multi-core box is fragmented, and some portion of the tree is duplicated even within processes, which seems wasteful. For this reason I have assumed that programs would use a thread-safe shared-memory design within a multi-core box, and only use MPI to scale to clusters. But there are downsides to that design as well. Like the extra complexity of having two models for parallel programming. And I don't really know the cost of duplicating nodes. Maybe the tree splits so much that different processes share relatively few nodes. Or maybe you can allocate trials so that is the case. And now my question: what do you actually do: MPI, thread-safe, both, or something else? And can you share any observations about your choices? Thanks, Brian _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
