@inproceedings{5baa1387e9ad43d7a89dd77c07fa291f,
title = "Power and energy efficient routing for Mach-Zehnder interferometer based photonic switches",
abstract = "Silicon Photonic top-of-rack (ToR) switches are highly desirable for the datacenter (DC) and high-performance computing (HPC) domains for their potential high-bandwidth and energy efficiency. Recently, photonic Bene{\v s} switching fabrics based on Mach-Zehnder Interferometers (MZIs) have been proposed as a promising candidate for the internals of high-performance switches. However, state-of-the-art routing algorithms that control these switching fabrics are either computationally complex or unable to provide non-blocking, energy efficient routing permutations.To address this, we propose for the first time a combination of energy efficient routing algorithms and time-division multiplexing (TDM). We evaluate this approach by conducting a simulation-based performance evaluation of a 16x16 Bene{\v s} fabric, deployed as a ToR switch, when handling a set of 8 representative workloads from the DC and HPC domains. Our results show that state-of-the-art approaches (circuit switched energy efficient routing algorithms) introduce up to 23% contention in the switching fabric for some workloads, thereby increasing communication time. We show that augmenting the algorithms with TDM can ameliorate switch fabric contention by segmenting communication data and gracefully interleaving the segments, thus reducing communication time by up to 20% in the best case. We also discuss the impact of the TDM segment size, finding that although a 10KB segment size is the most beneficial in reducing communication time, a 100KB segment size offers similar performance while requiring a less stringent path-computation time window. Finally, we assess the impact of TDM on path-dependent insertion loss and switching energy consumption, finding it to be minimal in all cases.",
keywords = "Mach-Zehnder Interferometers, Photonic switches, Routing, TDM, Top-of-rack",
author = "Markos Kynigos and Jose Pascual and Javier Navaridas and John Goodacre and Mikel Luj{\'a}n",
note = "Funding Information: This work was partly funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No 754337, EuroEXA project. Prof. Mikel Lujan is funded by an Arm/RAEng Research Chair Award and a Royal Society Wolfson Fellowship. Dr. Javier Navaridas is funded by a Ram?n y Cajal RYC2018-024829-I from the Spanish Ministry of Science, Innovation and Universities. Publisher Copyright: {\textcopyright} 2021 Copyright held by the owner/author(s). Publication rights licensed to ACM.",
year = "2021",
month = jun,
day = "3",
doi = "10.1145/3447818.3460363",
language = "English",
series = "Proceedings of the International Conference on Supercomputing",
publisher = "Association for Computing Machinery",
pages = "177--189",
booktitle = "ICS 2021 - Proceedings of the 2021 ACM International Conference on Supercomputing",
address = "United States",
}