The U-Machine: A Model of Generalized Computation
Bruce J. MacLennan
We argue that post-Moore’s Law computing technology will require the exploitation of new physical processes for computational purposes, which will be facilitated by new models of computation. After a brief discussion of computation in the broad sense, we present a model of generalized computation, and a corresponding machine model, which can be applied to massively-parallel nanocomputation in bulk materials. The machine is able to implement quite general transformations on a broad class of topological spaces by means of Hilbert-space representations. Neural morphogenesis provides a model for the physical structure of the machine and means by which it may be configured, a process that involves the definition of signal pathways between two-dimensional data areas and the setting of interconnection strengths within them. This approach also provides a very flexible means of reconfiguring the internal structure of the machine.
Keywords: Analog computers, analog systems, diffusion processes, digital systems, neural network hardware, reconfigurable architectures, memory architecture, nanotechnology, neural network architecture, neural networks.