  The IBM Neural Computer (INC) is a highly flexible, re-configurable parallel
processing system that is intended as a research and development platform for
emerging machine intelligence algorithms and computational neuroscience. It
consists of hundreds of programmable nodes, primarily based on Xilinx's Field
Programmable Gate Array (FPGA) technology. The nodes are interconnected in a
scalable 3d mesh topology. We overview INC, emphasizing unique features such as
flexibility and scalability both in the types of computations performed and in
the available modes of communication, enabling new machine intelligence
approaches and learning strategies not well suited to the matrix
manipulation/SIMD libraries that GPUs are optimized for. This paper describes
the architecture of the machine and applications are to be described in detail
elsewhere.
