I just ran across a great blog entry about SGE debuting topology-aware scheduling. Dan Templeton does a great job of describing the need for processor topology-aware job scheduling within a server. Many MPI jobs fit exactly within his description of applications that have “serious resource needs” — they typically require lots of CPU and/or network (or other I/O). Hence, scheduling an MPI job intelligently across not only the network, but also across the network and resources inside the server, is pretty darn important. It’s all about location, location, location!
Particularly as core counts in individual server are going up.
Particularly as networks get more complicated inside individual servers.
Particularly if heterogeneous computing inside a single server becomes popular.
Particularly as resources are now pretty much guaranteed to be non-uniform within an individual server.
These are exactly the reasons that, even though I’m a network middleware developer, I spend time with server-specific projects like hwloc — you really have to take a holistic approach in order to maximize performance.