  Modern heterogeneous supercomputing systems are comprised of CPUs, GPUs, and
high-speed network interconnects. Communication libraries supporting efficient
data transfers involving memory buffers from the GPU memory typically require
the CPU to orchestrate the data transfer operations. A new offload-friendly
communication strategy, stream-triggered (ST) communication, was explored to
allow offloading the synchronization and data movement operations from the CPU
to the GPU. A Message Passing Interface (MPI) one-sided active target
synchronization based implementation was used as an exemplar to illustrate the
proposed strategy. A latency-sensitive nearest neighbor microbenchmark was used
to explore the various performance aspects of the implementation. The offloaded
implementation shows significant on-node performance advantages over standard
MPI active RMA (36%) and point-to-point (61%) communication. The current
multi-node improvement is less (23% faster than standard active RMA but 11%
slower than point-to-point), but plans are in progress to purse further
improvements.
