We present a single-chip array of 100 biologically-based electronic neuron models interconnected to each other and the outside environment through 30,000 synapses. The chip was fabricated in a standard 350 nm CMOS IC process. Our approach used dense circuit models of synaptic behavior, including biological computation and learning, as well as transistor channel models. We use Address-Event Representation (AER) spike communication for inputs and outputs to this IC. We present the IC architecture and infrastructure, including IC chip, configuration tools, and testing platform. We present measurement of small network of neurons, measurement of STDP neuron dynamics, and measurement from a compiled spiking neuron WTA topology, all compiled into this IC.

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Analog circuits and systems research and education can benefit from the flexibility provided by large-scale Field Programmable Analog Arrays (FPAAs). This paper presents the hardware and software infrastructure supporting the use of a family of floating-gate based FPAAs being developed at Georgia Tech. This infrastructure is compact and portable and provides the user with a comprehensive set of tools for custom analog circuit design and implementation. The infrastructure includes the FPAA IC, discrete ADC, DAC and amplifier ICs, a 32-Bit ARM based microcontroller for interfacing the FPAA with the user's computer, and Matlab and targeting software. The FPAA hardware communicates with Matlab over a USB connection. The USB connection also provides the hardware's power. The software tools include three major systems: a Matlab Simulink FPAA program, a SPICE to FPAA compiler called GRASPER, and a visualization tool called RAT. The hardware consists of two custom PCB designs which include a main board used to program and control an FPAA IC and an FPAA IC adaptor board used to interface a QFP packaged FPAA IC with the 100 pin ZIF socket on the main programming and control board.