  Nowadays, as the ever-increasing demand for more powerful computing resources
continues, alternative advanced computing paradigms are under extensive
investigation. Significant effort has been made to deviate from conventional
Von Neumann architectures. In-memory computing has emerged in the field of
electronics as a possible solution to the infamous bottleneck between memory
and computing processors, which reduces the effective throughput of data. In
photonics, novel schemes attempt to collocate the computing processor and
memory in a single device. Photonics offers the flexibility of multiplexing
streams of data not only spatially and in time, but also in frequency or,
equivalently, in wavelength, which makes it highly suitable for parallel
computing. Here, we numerically show the use of time and wavelength division
multiplexing (WDM) to solve four independent tasks at the same time in a single
photonic chip, serving as a proof of concept for our proposal. The system is a
time-delay reservoir computing (TDRC) based on a microring resonator (MRR). The
addressed tasks cover different applications: Time-series prediction, waveform
signal classification, wireless channel equalization, and radar signal
prediction. The system is also tested for simultaneous computing of up to 10
instances of the same task, exhibiting excellent performance. The footprint of
the system is reduced by using time-division multiplexing of the nodes that act
as the neurons of the studied neural network scheme. WDM is used for the
parallelization of wavelength channels, each addressing a single task. By
adjusting the input power and frequency of each optical channel, we can achieve
levels of performance for each of the tasks that are comparable to those quoted
in state-of-the-art reports focusing on single-task operation...
