This paper describes the MM32k, a massively-parallel SIMD com(cid:173) puter which is easy to program, high in performance, low in cost and effective for implementing highly parallel neural network ar(cid:173) chitectures. The MM32k has 32768 bit serial processing elements, each of which has 512 bits of memory, and all of which are inter(cid:173) connected by a switching network. The entire system resides on a single PC-AT compatible card. It is programmed from the host computer using a C language class library which abstracts the parallel processor in terms of fast arithmetic operators for vectors of variable precision integers.

Many well known neural network techniques for adaptive pattern classification and function approximation are inherently highly parallel, and thus have proven difficult to implement for real-time applications at a reasonable cost.

Many well known neural network techniques for adaptive pattern classification and function approximation are inherently highly parallel, and thus have proven difficult to implement for real-time applications at a reasonable cost.

Many well known neural network techniques for adaptive pattern classification and function approximation are inherently highly parallel, and thus have proven difficult toimplement for real-time applications at a reasonable cost.