  Information processing has reached the era of big data. Big data challenges
are difficult to address with traditional Von Neumann or Turing approach. Hence
implementation of new computational techniques is highly essential.
Nanophotonics with its remarkable speed and multiplexing capability is a
promising candidate for such implementations. This paper proposes a novel
photonic computing system made-up of Mach-Zehnder interferometer and an optical
fiber spool to emulate a powerful machine learning technique called reservoir
computing. The proposed system is also integrated with a
time-division-multiplexing circuit to facilitate parallel computation of
multiple tasks which is first of its kind. The proposed design performs
large-scale tasks like spoken digit recognition, channel equalization, and
time-series prediction. Experimental results with standard photonic simulator
demonstrate significant performance in terms of speed and accuracy compared to
state of the art digital and software implementations.
