  In-materia reservoir computing (RC) leverages the intrinsic physical
responses of functional materials to perform complex computational tasks.
Magnetic metamaterials are exciting candidates for RC due to their huge state
space, nonlinear emergent dynamics, and non-volatile memory. However, to be
suitable for a broad range of tasks, the material system is required to exhibit
a broad range of properties, and isolating these behaviours experimentally can
often prove difficult. By using an electrically accessible device consisting of
an array of interconnected magnetic nanorings -- a system shown to exhibit
complex emergent dynamics -- here we show how reconfiguring the reservoir
architecture allows exploitation of different aspects the system's dynamical
behaviours. This is evidenced through state-of-the-art performance in diverse
benchmark tasks with very different computational requirements, highlighting
the additional computational configurability that can be obtained by altering
the input/output architecture around the material system.
