A plug-and-play model for evaluating wavefront computations on parallel architectures

This paper develops a plug-and-play reusable LogGP model that can be used to predict the runtime and scaling behavior of different MPI-based pipelined wavefront applications running on modern parallel platforms with multi-core nodes. A key new feature of the model is that it requires only a few simple input parameters to project performance for wavefront codes with different structure to the sweeps in each iteration as well as different behavior during each wavefront computation and/or between iterations. We apply the model to three key benchmark applications that are used in high performance computing procurement, illustrating that the model parameters yield insight into the key differences among the codes. We also develop new, simple and highly accurate models of MPI send, receive, and group communication primitives on the dual-core Cray XT system. We validate the reusable model applied to each benchmark on up to 8192 processors on the XT3/XT4. Results show excellent accuracy for all high performance application and platform configurations that we were able to measure. Finally we use the model to assess application and hardware configurations, develop new metrics for procurement and configuration, identify bottlenecks, and assess new application design modifications that, to our knowledge, have not previously been explored.