Modeling a Photonic Network for Exascale Computing

Photonics technology has become a promising and viable alternative for both on-chip and off-chip computer networks of future Exascale systems. Nevertheless, this technology is not mature enough yet in this context, so research efforts focusing on photonic networks are still required to achieve realistic suitable network implementations. In this context, system-level photonic network simulators can help to guide designers to assess the multiple design choices.

Most current research is done on electrical network simulators, whose components work widely different from photonics components. Moreover, photonics technology adds new  components that are not present in electrical networks. This paper discusses how a photonics simulation tool can be built by extending an electrical simulation framework. We summarize and compare the working behavior of both technologies –electrical and photonics–, and discuss the rationale behind the proposed extensions. Among others, the devised extensions model optical routers, wavelength-division multiplexing, circuit switching, and specific routing algorithms.

This work is aimed to provide support to investigate offchip optical networks in the context of the European Exascale System Interconnect and Storage project (ExaNeSt) project. The experiments presented in this paper study multiple realistic photonic networks configurations and have been performed with excerpts of real traces. Experimental results show that, compared to electrical networks, optical networks can reduce the execution time of the workload by several orders of magnitude. Our study reveals that future optical technologies presenting a 3.2 Tbps aggregate link bandwidth will not provide additional performance benefits over state-of-the-art 1.6 Tbps optical links across the studied workloads, but 1.6 Tbps network links are enough to achieve the highest optical performance on computer networks. Regarding the link configuration, the bandwidth per optical channel is the parameter with highest impact on the network delay and so on the execution time, while for a given optical bandwidth per channel the better strategy is to reduce the phit size.