Abstract

Laser energy cost is one of the primary energy budgets in integrated photonic switching systems. Traditional photonic switch testing injects random traffic to the switches, which only generates a “static” laser energy cost result. However, the laser's energy per bit performance fluctuates due to different process mapping scenarios of applications. In this paper, we did experiments to study the influence of the application's process mapping on the photonic switches' injection traces. Then we built a model to show the connection between the traces and the laser's energy per bit performance. To get the energy fluctuation results quickly and accurately, we propose a heuristic-based energy boundary searching methodology, with the model we built being considered. We also analyze the speedup and convergence of the methodology. Two photonic switches are studied under five kinds of application traces. The study shows an over 60% searching speedup and 90% accuracy in most cases, compared with the enumeration method, and the lasers' energy fluctuations vary from nearly 0% to over 150%. We further analyze the factors inducing such huge fluctuation variations, and a qualitative criterion that predicts the magnitude of the variations is proposed and discussed.

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