A case study in using massively parallel simulation for extreme-scale torus network codesign

Abstract

A high-bandwidth, low-latency interconnect will be a critical component of future exascale systems. The torus network topology, which uses multidimensional network links to improve path diversity and exploit locality between nodes, is a potential candidate for exascale interconnects. The communication behavior of large-scale scientific applications running on future exascale networks is particularly important and analytical/algorithmic models alone cannot deduce it. Therefore, before building systems, it is important to explore the design space and performance of candidate exascale interconnects by using simulation. We improve upon previous work in this area and present a methodology for modeling and simulating a high-fidelity, validated, and scalable torus network topology at a packet-chunk level detail using the Rensselaer Optimistic Simulation System (ROSS). We execute various configurations of a 1.3 million node torus network model in order to examine the effect of torus dimensionality on network performance with relevant HPC traffic patterns. To the best of our knowledge, these are the largest torus network simulations that are carried out at such a detailed fidelity. In terms of simulation performance, a 1.3 million node, 9-D torus network model is shown to process a simulated exascale-class workload of nearest-neighbor traffic with 100 million message injections per second per node using 65,536 Blue Gene/Q cores in a simulation run-time of only 25 seconds. We also demonstrate that massive-scale simulations are a critical tool in exascale system design since small-scale torus simulations are not always indicative of the network behavior at an exascale size. The take-away message from this case study is that massively parallel simulation is a key enabler for effective extreme-scale network codesign.