We have developed an SIMD-type neural-network processor (NEURO4) and its software environment. With the SIMD architecture, the chip executes 24 operations in a clock cycle and achieves 1.2 GFLOPS peak performance. An accelerator board, which contains four NEURO4 chips, achieves 3.2 GFLOPS. In this paper we describe features of the neural network chip, accelerator board, software environment and performance evaluation for several neural network models (LVQ, BP and Hopfield). The 3.2 GFLOPS neural network accelerator board demonstrates 1.7 GCPS and 261 MCUPS for Hopfield networks.

This paper describes the operation and the test results of a novel comparator, called a differential voltage (ΔV) comparator, which detects the difference between two input signal voltages. This comparator utilizes variable threshold voltage inverters (VT-INVs) which can change a logic threshold continuously using a variable channel size MOSFETs (VS-MOSs). The circuit configuration is very simple, and has the potential to achieve high integration and low power consumption in mixed signal system LSIs.