GitLab

(i) Adding sampling for dragonfly compute node LPs (ii) Adding file I/O reader that translates the binary format to text

Torus model revision: adding bubble flow control for deadlock prevention and updated congestion control

Changing the hash function to bj_hash_little2, more additions to the MPI Sim layer operation matching

NOTE: caused an event size bump - you may need to update config files

Updated congestion control in dragonfly: now messages are saved in a waiting list at the routers in case of buffer overflows

Updating torus network model: now generates one chunk at a time and holds off another until the previous one is sent

Adding group level mapping in the dragonfly: multiple routers can now be specified in the config file

1) Adding dragonfly adaptive and prog-adaptive routing algorithms--- still testing with more workloads and crosschecking the computation 2) Two bug fixes in credit-based flow control

Tired of explaining that it's not a good representation of a WAN. Instead, it's
now a simple point-to-point latency/bandwidth model.

Rather than model-net LPs directly sending messages to other model-net LPs, LPs
can route the intended message through the scheduler interface to be queued up
for reception by the receiver (see the diff of loggp.c). This has the benefit of
    enabling things like priority and fairness for N->1 communication patterns.
    Currently, no packetizing is supported, and I haven't yet wrote checks for
    it - beware.

Loggp is currently the only supported model. simplenet could also be supported
without much trouble, but I doubt there's any demand for it at the moment.  This
should NOT be used by the dragonfly/torus models, as they have their own routing
backend.

Adding collective modeling functions in model-net (currently only dragonfly/torus models support it)