This paper proposes new architecture LSIs based on wave-parallel computing to provide an essential solution to the interconnection problems in massively parallel processing. The basic concept is ferquency multiplexing of digital information, which enables us to utilize the parallelism of electrical (or optical) waves for parallel processing. This wave-parallel computing concept is capable of performing several independent binary funtions in parallel with a single module. In this paper, we discuss the design of wave-parallel image processing LSI to demonstrate the feasibility of reducing the number of interconnections among modules.

A new computer architecture using multiwavelength optoelectronic integrated circuits (OEICs) is proposed to attack the problems caused by interconnection complexity. Multiwavelength-OEIC architecures, where various wavelengths are employed as information carriers, provide the wavelength as an extra dimension of freedom for parallel processing, so that we can perform several independent computations in parallel in a single optical module using the wavelength space. This multiplex computing" enables us to reduce the wiring area required by a network and improve their complexity. In this paper, we discuss the efficient multiplexing of Batcher's bitonic sorting networks, highly parallel computing architectures that require global interconnections inherently. A systematic multiplexing of interconnection topology is presented using a binary representation of the connectivities of interconnection paths. It is shown that the wiring area can be reduced by a factor of 1/r2 using r kinds of wavelength components.