  The discovery of the spin torque effect has made magnetic nanodevices
realistic candidates for active elements of memory devices and applications.
Magnetoresistive effects allow the read-out of increasingly small magnetic
bits, and the spin torque provides an efficient tool to manipulate - precisely,
rapidly and at low energy cost - the magnetic state, which is in turn the
central information medium of spintronic devices. By keeping the same magnetic
stack, but by tuning a device's shape and bias conditions, the spin torque can
be engineered to build a variety of advanced magnetic nanodevices. Here we show
that by assembling these nanodevices as building blocks with different
functionalities, novel types of computing architectures can be envisisaged. We
focus in particular on recent concepts such as magnonics and spintronic neural
networks.
